Miracle-dz/UniFAR-FTUs huggingface dataset:
Juvenile offenders: an examination of distance-to-crime and crime clusters

The current study focuses on crime location characteristics of juvenile offenders. Based on the argument that juveniles have limited routine activities that restrict their awareness space, where juvenile offenders commit crimes becomes important to understand. Specifically, the current study examines the distance juveniles travel to specific crime types. As juveniles age towards 18 years, it is expected that the distance traveled to commit crime increases based on a greater awareness space/access to transportation. Additionally, we examine the clustering of crime incidents that were committed by juveniles to understand the spatial relationship between crime clusters and characteristics of the built environments (i.e. businesses). The current study utilizes arrest data that contain incident and home addresses in Little Rock, Arkansas to study juvenile distance-to-crime and crime clusters. The results of the analyses are discussed in relation to juveniles’ routine activities and possible changes in routine activities as they age.
Twitter's Algorithm: Amplifying Anger, Animosity, and Affective Polarization

As social media continues to have a significant influence on public opinion, understanding the impact of the machine learning algorithms that filter and curate content is crucial. However, existing studies have yielded inconsistent results, potentially due to limitations such as reliance on observational methods, use of simulated rather than real users, restriction to specific types of content, or internal access requirements that may create conflicts of interest. To overcome these issues, we conducted a pre-registered controlled experiment on Twitter’s algorithm without internal access. The key to our design was to, for a large group of active Twitter users, simultaneously collect (a) the tweets the personalized algorithm shows, and (b) the tweets the user would have seen if they were just shown the latest tweets from people they follow; we then surveyed users about both sets of tweets in a random order. Our results indicate that the algorithm amplifies emotional content, and especially those tweets that express anger and out-group animosity. Furthermore, political tweets from the algorithm lead readers to perceive their political in-group more positively and their political out-group more negatively. Interestingly, while readers generally say they prefer tweets curated by the algorithm, they are less likely to prefer algorithm-selected political tweets. Overall, our study provides important insights into the impact of social media ranking algorithms, with implications for shaping public discourse and democratic engagement.
The Pleistocene-Recent Tonga-Kermadec Arc Lavas: Interpretation of New Isotopic and Rare Earth Data in Terms of a Depleted Mantle Source Model

New REE data, and new Nd, O, Sr, and Pb isotopic data are presented and integrated with previous data for this low-K intra-oceanic arc suite. Geochemically, the arc tholeiites and basaltic andesites range from extremely HFS element depleted (northern Tonga) to near N-MORB-like HFS element abundances in L'Esperance (southern Kermadecs). LIL elements (Sr, Rb, K, Rb, Ba, Th) show the characteristic selective enrichment generally recognized in arc magmas, and thus indicate decoupling of the HFS and LIL elements. Modelling suggests a compositionally variable source (mantle wedge) along the arc, ranging from restite after remelting an N-type MORB source (northern end), to progressively less depleted, MORB-like sources southwards. Thus, the low HFS/LIL element ratios are interpreted in terms of HFS depletion followed by LIL element enrichment associated with subduction; broad correlations occur between Zr/Ba and Sr/Nd ratios (fractionation corrected) and 87Sr/86Sr and Nd/Nd ratios.Derivation of the arc magmas from depleted peridotote requires superimposed fractional crystallization, which has been modelled thermodynamically using SILMIN (Ghiorso, 1985), utilizing experimentally produced partial melts from depleted lherzolite (Jaques & Green, 1980). It is shown that the arc tholeiites and basaltic andesites (and also high Mg-andesites) are potentially developed at low pressures ≤ 5 kb), from parental magmas also generated at relatively low pressure (≤ 10 kb). These data further suggest that a southward increasing depth of magma segregation (correlating with Benioff Zone geometry) could account for differences in chemistry between the Tonga and Kermadec arc segments.The mechanism of LILE enrichment is still highly problematic, but it is suggested that the model of Tatsumi et al. (1986) may account for much of the geochemical data; this involves relatively shallow release, via fluids, of LIL elements into overlying peridotite beneath the fore-arc region. Induced convection in the mantle wedge moves the metasomatized mantle into the zones of magma generation.The development of the inferred, variably depleted mantle wedge source is here related to active back-arc spreading which is slightly older and more rapid behind the northern region of the arc. The lherzolite restite from this spreading process is interpreted to undergo further partial melting in the metasomatized mantle wedge overlying the subduction zone, involving induced convection.The back-arc island of Niua fo'ou is geochemically quite distinct from the arc magmas, being similar to N-MORB in its trace elements, but to OIB in its isotope ratios.
Crystalline organization of the fibrous prismatic calcitic layer of the Mediterranean mussel Mytilus galloprovincialis

The outer layer of the shell of members of the genus Mytilus is made of long, slender fibres of calcite (some 1–2 mm wide and hundreds of mm long), which reach the internal surface of the shell at an angle. This microstructure has been called anvil-type fibrous calcitic and its organization, crystallography and relationships to the organic phase are poorly known. We have studied the outer calcitic layer of the Mediterranean mussel M. galloprovincialis by means of optical and scanning and transmission electron microscopy (SEM and TEM), X-ray diffraction (XRD) and atomic-force microscopy (AFM). SEM data from other species have also been gathered. All data together imply that the material is extremely well ordered both from the morphological and crystallographic viewpoints. The XRD pole figures show that there are discrete 001 and 104 maxima; therefore, the material has a well-defined sheet texture. In living animals there is an organic membrane (surface membrane) that coats the inner surface of the shell. TEM sections of the decalcified material show that this mainly proteinaceous surface layer is internally laminated and fills all the spaces left between the growing fibres. Every fibre is a monocrystal with three well developed {104} rhombohedral faces at its growth end. One of these faces is directly in contact with, and strictly parallel, to the sublayers of the surface membrane and thus to the inner shell surface. AFM experiments consisting on growing calcite onto shell pieces in which the surface membranes are preserved, show that the calcitic fibres of the shell easily regrow across the membrane, demonstrating that it is permeable to ions. In this way, prisms are able to grow despite the existence of the intermediate membrane in the living animal. Additional experiments of calcite growth onto the inner side of the surface membrane show that crystals grow onto their {104} surfaces. The surface membrane is responsible for the high degree of ordering of the fibrous calcitic layer, because it stabilizes the orientation of a rhombohedral surface, once this is parallel to the protein sublayers. This is one of the very few cases in which the influence of the organic matter on the organization of microstructures can be demonstrated.
Zero-shot NLG evaluation through Pairware Comparisons with LLMs

Evaluating Natural Language Generation (NLG) outputs is crucial but laborious and expensive. While various automatic NLG assessment methods have been proposed, they often are quite task-speciﬁc and have to be engineered with a particular domain and attribute in mind. In this work, we propose a robust zero-shot approach to NLG evaluation using pairwise comparative judgment with open-source Large Language Models (LLMs). The motivation for this approach is that even as humans, it is easier to determine which of two options are better, than it is to independently objectively score each option. We use this insight and leverage the emergent abilities of LLMs, where we probe FlanT5 to determine which of two candidate responses is better, rather than assigning absolute scores. Our results demonstrate that comparative assessment is a more effective approach than absolute scoring, enabling smaller open-source LLMs to achieve comparable performance to larger public access APIs. We evaluate systems on both summary evaluation and dialogue response generation, and show that opensource LLMs can lead to good correlations with human scores for a range of different attributes.
Variations in moisture content for a soil cover over a 10 year period

The Equity Silver mine is located in north-central British Columbia and is the site of a large, well-instrumented soil cover. The soil-cover site was designed to prevent the generation of acid rock drainage from the acid-generating waste rock disposed of at this site. The cover was designed to act as an oxygen barrier by maintaining a layer of saturated soil above the waste rock. The cover consists of a compacted till placed over the waste rock and covered with a non-compacted layer of the same material. Neutron probes and thermal conductivity sensors were used to monitor the moisture content of the cover soil over a 10 year period. Weather data at the site were also collected. A review of the data collected has shown that saturation was maintained in the lower, 0.5 m thick compacted layer of the cover, as per the original cover design. The upper cover layer (0.3 m of noncompacted till) was subject to seasonal variations in moisture content, with drying in the summer months and wetting in the fall and spr.
Predicting incipient motion, including the effect of turbulent pressure fluctuations in the bed

Incipient motion of particles on a river bed can, in principle, be understood and predicted from a balance of the forces acting on the particles. On a natural river bed the exposure of particles to the flow is variable. The effect of exposure on the initiation of motion, including the case of deep embedding, is studied in this paper. So far, the turbulence‐induced lifting force has been derived exclusively from examinations of the surface flow. The understanding of destabilization processes of the riverbed is improved when turbulence‐induced vertical pressure gradients in the upper sediment layer are included. This is particularly important for particles that lie in the lee of larger ones. An analytical solution for the critical Shields parameter of spherical particles is found, including the effects of pressure fluctuations in the bed, macroscale flow structures, average bed slope, and shallow flow. Existing laboratory data designed to test the effect of exposure and roughness conditions are in excellent agreement with the new model.
Modified Soil Water Retention Functions for All Matric Suctions

The Brooks-Corey and van Genuchten functions were modified to adequately represent retention at all matric suctions. The modification consisted of replacing the residual water content with an adsorption equation (Campbell and Shiozawa, 1992). The modified functions retain the form of the original functions in the wet range and the form of an adsorption equation in the dry range. The modified functions provided excellent fits to data from six soils with textures ranging from sand to silty clay. The modified van Genuchten function can use previously determined parameters to obtain a reasonable representation of the high matric suction range, thus allowing for the use of existing parameter sets. The modified functions, as well as the function proposed by Rossi and Nimmo (1994), were combined with the Mualem conductivity model to generate closed-form analytical expressions for the calculation of hydraulic conductivity.
Fast and reliable online learning to rank for information retrieval

The amount of digital data we produce every day far surpasses our ability to process this data, and finding useful information in this constant flow of data has become one of the major challenges of the 21st century. Search engines are one way of accessing large data collections. Their algorithms have evolved far beyond simply matching search queries to sets of documents. Today’s most sophisticated search engines combine hundreds of relevance signals to provide the best possible results for each searcher. Current approaches for tuning the parameters of search engines can be highly effective. However, they typically require considerable expertise and manual effort. They rely on supervised learning to rank, meaning that they learn from manually annotated examples of relevant documents for given queries. Obtaining large quantities of sufficiently accurate manual annotations is becoming increasingly difficult, especially for personalized search, access to sensitive data, or search in settings that change over time. In this thesis, I develop new online learning to rank techniques, based on insights from reinforcement learning. In contrast to supervised approaches, these methods allow search engines to learn directly from users’ interactions. User interactions can typically be observed easily and cheaply, and reflect the preferences of real users. Interpreting user interactions and learning from them is challenging, because they can be biased and noisy. The contributions of this thesis include a novel interleaved comparison method, called probabilistic interleave, that allows unbiased comparisons of search engine result rankings, and methods for learning quickly and effectively from the resulting relative feedback. The obtained analytical and experimental results show how search engines can effectively learn from user interactions. In the future, these and similar techniques can open up new ways for gaining useful information from ever larger amounts of data.
Empirical Response Spectral Attenuation Relations for Shallow Crustal Earthquakes

Using a database of 655 recordings from 58 earthquakes, empirical response spectral attenuation relations are derived for the average horizontal and vertical component for shallow earthquakes in active tectonic regions. A new feature in this model is the inclusion of a factor to distinguish between ground motions on the hanging wall and footwall of dipping faults. The site response is explicitly allowed to be non-linear with a dependence on the rock peak acceleration level.
The thickness of the magnetopause current layer: ISEE 1 and 2 observations

The analysis of the dual magnetic field profile obtained by the ISEE mission provides a unique opportunity to study the earth's magnetospheric boundaries. A survey of the magnetopause thickness over the dayside magnetosphere is carried out by using the magnetic field measurements from the twin ISEE 1 and ISEE 2 magnetometers. Since reliable measurements are possible only for small separations (<1000 km) between ISEE 1 and 2 our data set is restricted to only thirty magnetopause crossings in the range of local time from 0800 to 1700 and at GSM latitude from 2° to 35°. We find that the magnetopause is in constant rapid and irregular motion with velocities ranging, in 80% of the cases, from 10 km/s to 80 km/s and with the current sheet thickness ranging from 400 to 1000 km. The thickness seems much better ordered by dipole mangetic latitudes than by GSM latitude. Near the magnetic equator the magnetopause current sheet is thinnest, about 500 km on average. This observation suggests that reconnection is initiated in the equatorial regions rather than in the polar cusps.
Growing three aromatic grasses in different alkali soils in semi‐arid regions of northern India

Alkali lands in India occupy about 3 million ha. Due to poor physical properties, excessive exchangeable sodium and high pH, most of these lands support a very poor vegetation cover. Many of the medicinal and aromatic plants are in great demand for both internal requirements and export. But since these crops are non‐conventional in nature, it is not always possible for them to be produced on fertile lands, which can be used for arable crops. The marginal lands, specifically the lands affected by salinity or sodicity problems where profitable returns are not possible from agricultural crops, could be successfully utilized for the cultivation of these high‐value crops with marginal inputs. Results reported in this paper clearly indicated that out of three aromatic grasses, palmarosa (Cymbopogon martinii (Roxb.) Wats. ) and lemon grass (C. flexuosus (Steud.) Wats. ) could successfully be grown on moderatly alkali soils of pH up to 9·2 while vetiver (Vetiveria zizanioides (L.) Nash), which withstands both high pH and stagnation of water, could successfully be grown without significant yield reduction on highly alkali soils. These grasses not only produce essential oils used for industrial purposes but also ameliorate the soil. Copyright © 2004 John Wiley & Sons, Ltd.
A reevaluation of submarine groundwater discharge along the southeastern coast of North America

New data of fluxes of radium isotopes and concentrations of radium in coastal groundwater enable an estimation of fluxes of submarine groundwater discharge (SGD) to a large section of the South Atlantic Bight (SAB). The new fluxes are considerably greater than SGD fluxes to this region estimated earlier. The annual average total SGD fluxes, which represent a range of salinity, are 3 times greater than the river fluxes. The highest fluxes of radium and SGD occur in the summer off the coast of Georgia. When scaled per kilometer of shoreline, the SGD flux is the same for the coastlines of Onslow Bay, NC (140 km), a section of the South Atlantic Bight from Onslow Bay, NC, to Cresent Beach, Florida, United States (600 km), and the entire Atlantic Ocean (75,000 km). The fact that each independent estimate is based on different methods and assumptions gives confidence to the results. These SGD fluxes are not restricted to the shoreline but occur throughout the continental shelf. They are important for supplying not only radium but also nutrients, carbon, metals, and freshwater to these coastal waters.
Black-Box Variational Inference Converges

We provide the first convergence guarantee for full black-box variational inference (BBVI), also known as Monte Carlo variational inference. While preliminary investigations worked on simplified versions of BBVI ( e.g. , bounded domain, bounded support, only optimizing for the scale, and such), our setup does not need any such algorithmic modifications. Our results hold for log-smooth posterior densities with and without strong log-concavity and the location-scale variational family. Also, our analysis reveals that certain algorithm design choices commonly employed in practice, particularly, nonlinear parameterizations of the scale of the variational approximation, can result in suboptimal convergence rates. Fortunately, running BBVI with proximal stochastic gradient descent fixes these limitations, and thus achieves the strongest known convergence rate guarantees. We evaluate this theoretical insight by comparing proximal SGD against other standard implementations of BBVI on large-scale Bayesian inference problems.
Sand Erosion by Mobile Predaceous Stream Insects: Implications for Ecology and Hydrology

Despite increasing knowledge of the ability of keystone animal species (“ecosystem engineers”) to change their physical environment, there is little and inconsistent evidence that benthic invertebrates affect the erosion of bottom material in streams. Therefore we designed field stream experiments and observations to investigate the effect of mobile predaceous stonefly (Dinocras cephalotes) larvae on sand erosion. When short of prey, the stoneflies erode sand from stream riffles thereby deepening the interstices between cobbles. On the basis of reasonable assumptions, we speculate that Dinocras has an erosion potential of about 200–400 kg sand m−2 yr−1 at natural population densities under favorable flow conditions. We consider the possible implications of the bioturbation potential of stream invertebrates for ecology (habitat quality and disturbance) and hydrology (sand transport and stability of coarse stream bottoms), which call for joint research on this novel role invertebrates play in the functioning of stream ecosystems.
Stabilisation of neutral systems with saturating control inputs

This article focuses on the stabilisation problem of neutral systems in the presence of time-varying delays and control saturation. Based on a descriptor approach and the use of a modified sector relation, global and local stabilisation conditions are derived using Lyapunov–Krasovskii functionals. These conditions, formulated directly as linear matrix inequalities (LMIs), allow one to relate the control law to be computed to a set of admissible initial conditions, for which the asymptotic and exponential stabilities of the closed-loop system are ensured. An extension of these conditions to the particular case of retarded systems is also provided. From the theoretical conditions, optimisation problems with LMI constraints are therefore proposed to compute stabilising state feedback gains with the aim of ensuring stability for a given set of admissible initial conditions or the global stability of the closed-loop system. A numerical example illustrates the application of the proposed results.
QOMA: quasi-optimal multiple alignment of protein sequences

MOTIVATION We consider the problem of multiple alignment of protein sequences with the goal of achieving a large SP (Sum-of-Pairs) score. RESULTS We introduce a new graph-based method. We name our method QOMA (Quasi-Optimal Multiple Alignment). QOMA starts with an initial alignment. It represents this alignment using a K-partite graph. It then improves the SP score of the initial alignment through local optimizations within a window that moves greedily on the alignment. QOMA uses two parameters to permit flexibility in time/accuracy trade off: (1) The size of the window for local optimization. (2) The sparsity of the K-partite graph. Unlike traditional progressive methods, QOMA is independent of the order of sequences. The experimental results on BAliBASE benchmarks show that QOMA produces higher SP score than the existing tools including ClustalW, Probcons, Muscle, T-Coffee and DCA. The difference is more significant for distant proteins. AVAILABILITY The software is available from the authors upon request.