Miracle-dz/UniFAR-FTUs huggingface dataset:
Overcoming Obstacles to Integrated Water Management in Local Government: Experience in a High-growth Regional Shire

The principles of integrated urban water management (IUWM) represent a paradigm shift in the provision of water-related urban infrastructure, most of which is controlled at a local government level. With technological impediments fast disappearing, success in meeting the underlying environmental objectives of IUWM is now primarily obstructed by organisational issues in local government. Maroochy Shire Council, located on Queensland's Sunshine Coast, has recently reviewed its institutional arrangements and procedures in relation to integrated water management. This paper discusses some of the obstacles faced and lessons learned through this review process. Fragmentation, inconsistency and vagueness are identified as three key issues to be addressed in modifications to planning policy. In addition to addressing these problems, Maroochy Shire Council developed a unifying corporate strategy for lUWM to coordinate and focus water management activities across the organisation. Assertive management of procedural change across a range of council departments, disciplines and organisational levels is required for successful implementation of lUWM. This change process relies heavily on a leader with initiative and influence to perform as an organisational champion for lUWM. The experience in Maroochy Shire indicates that substantial advances in meeting IUWM objectives can be made with a moderate investment of time and resources.
G protein activation occurs via a largely universal mechanism

Understanding how signaling proteins like G proteins are allosterically activated is a long-standing challenge with significant biological and medical implications. Because it is difficult to directly observe such dynamic processes, much of our understanding is based on inferences from a limited number of static snapshots of relevant protein structures, mutagenesis data, and patterns of sequence conservation. Here, we use computer simulations to directly interrogate allosteric coupling in six G protein α-subunit isoforms covering all four G protein families. To analyze this data, we introduce automated methods for inferring allosteric networks from simulation data and assessing how allostery is conserved or diverged among related protein isoforms. We find that the allosteric networks in these six G protein α-subunits are largely conserved and consist of two pathways, which we call pathway-I and pathway-II. This analysis predicts that pathway-I is generally dominant over the second pathway, which we experimentally confirmed by showing that mutations to pathway-I perturb nucleotide exchange more than mutations to pathway-II. In the future, insights into unique elements of each G protein family could inform the design of isoform-specific drugs. More broadly, our tools should also be useful for studying allostery in other proteins and assessing the extent to which this allostery is conserved in related proteins.
Universal inverse modelling of point spread functions for SMLM localization and microscope characterization

The point spread function (PSF) of a microscope describes the image of a point emitter. Knowing the accurate PSF model is essential for various imaging tasks, including single molecule localization, aberration correction and deconvolution. Here we present uiPSF (universal inverse modelling of Point Spread Functions), a toolbox to infer accurate PSF models from microscopy data, using either image stacks of fluorescent beads or directly images of blinking fluorophores, the raw data in single molecule localization microscopy (SMLM). The resulting PSF model enables accurate 3D super-resolution imaging using SMLM. Additionally, uiPSF can be used to characterize and optimize a microscope system by quantifying the aberrations, including field-dependent aberrations, and resolutions. Our modular framework is applicable to a variety of microscope modalities and the PSF model incorporates system or sample specific characteristics, e.g., the bead size, depth dependent aberrations and transformations among channels. We demonstrate its application in single or multiple channels or large field-of-view SMLM systems, 4Pi-SMLM, and lattice light-sheet microscopes using either bead data or single molecule blinking data.
Modularity of PRC1 Composition and Chromatin Interaction define Condensate Properties

Polycomb repressive complexes (PRC) play a key role in gene repression and are indispensable for proper development. Canonical PRC1 forms condensates in vitro and in cells and the ability of PRC1 to form condensates has been proposed to contribute to maintenance of repression. However, how chromatin and the various subunits of PRC1 contribute to condensation is largely unexplored. Using single-molecule imaging, we demonstrate that nucleosomal arrays and PRC1 act synergistically, reducing the critical concentration required for condensation by more than 20-fold. By reconstituting and imaging PRC1 with various subunit compositions, we find that the exact combination of PHC and CBX subunits determine the initiation, morphology, stability, and dynamics of condensates. In particular, the polymerization activity of PHC2 strongly influences condensate dynamics to promote formation of structures with distinct domains that adhere to each other but do not coalesce. Using live cell imaging, we confirmed that CBX properties are critical for condensate initiation and that PHC polymerization is important to maintain stable condensates. Together, we propose that PRC1 can fine-tune the degree and type of condensation by altering its composition which might offer important flexibility of regulatory function during different stages of development.
Fine-Tuning and Remodelling of Pectins Play a Key Role in the Maintenance of Cell Adhesion

Plant cell adhesion is essential for development and stress response, mediated by pectin-rich middle lamella deposition between cell walls. However, the precise control mechanism of cell adhesion remains unclear. The qua2-1 and esmd1-1 mutants provide a better understanding of this process and suggest a signaling pathway triggering the loss and restoration of adhesion via cell wall modifications. This study attempts to characterize the potential regulatory role of endogenous oligogalacturonides (OGs) and pectin modifications in the control of cell adhesion in Arabidopsis. From dark-grown hypocotyls, our extraction revealed seven distinct endogenous OGs with varying polymerization and modifications. Abundance variations of OGs were observed among wild type, qua2-1, esmd1-1, and qua2-1/esmd1-1 mutants. The structure of homogalacturonans was analyzed by enzymatic fingerprint, in order to identify changes in esterification patterns. Expression analysis of pectin-modifying enzymes showed significant variations in PME, PMEI, and PAE genes. Gene expressions correlate with homogalacturonans modifications and cell adhesion phenotypes. This study enhances our understanding of a feedback loop between the endogenous OGs, homogalacturonans esterification fine tuning, and pectin remodeling enzymes expression in controlling cell adhesion.
Is developmental plasticity triggered by DNA methylation changes in the invasive cane toad (Rhinella marina)?

Many organisms can adjust their development according to environmental conditions, including the presence of conspecifics. Although this developmental plasticity is common in amphibians, its underlying molecular mechanisms remain largely unknown. Exposure during development to either ‘cannibal cues’ from older conspecifics, or ‘alarm cues’ from injured conspecifics, causes reduced growth and survival in cane toad (Rhinella marina) tadpoles. Epigenetic modifications, such as changes in DNA methylation patterns, are a plausible mechanism underlying these developmental plastic responses. Here we tested this hypothesis, and asked whether cannibal cues and alarm cues trigger the same DNA methylation changes in developing cane toads. We found that exposure to both cannibal cues and alarm cues induced local changes in DNA methylation patterns. These DNA methylation changes affected genes putatively involved in developmental processes, but in different genomic regions for different conspecific-derived cues. Genetic background explained most of the epigenetic variation among individuals. Overall, the molecular mechanisms triggered by exposure to cannibal cues seem to differ from those triggered by alarm cues. Studies linking epigenetic modifications to transcriptional activity are needed to clarify the proximate mechanisms that regulate developmental plasticity in cane toads.
On the Detection of Image-Scaling Attacks in Machine Learning

Image scaling is an integral part of machine learning and computer vision systems. Unfortunately, this preprocessing step is vulnerable to so-called image-scaling attacks where an attacker makes unnoticeable changes to an image so that it becomes a new image after scaling. This opens up new ways for attackers to control the prediction or to improve poisoning and backdoor attacks. While effective techniques exist to prevent scaling attacks, their detection has not been rigorously studied yet. Consequently, it is currently not possible to reliably spot these attacks in practice. This paper presents the first in-depth systematization and analysis of detection methods for image-scaling attacks. We identify two general detection paradigms and derive novel methods from them that are simple in design yet significantly outperform previous work. We demonstrate the efficacy of these methods in a comprehensive evaluation with all major learning platforms and scaling algorithms. First, we show that image-scaling attacks modifying the entire scaled image can be reliably detected even under an adaptive adversary. Second, we find that our methods provide strong detection performance even if only minor parts of the image are manipulated. As a result, we can introduce a novel protection layer against image-scaling attacks.
Estimation of earthquake hazard parameters from incomplete data files. Part II. Incorporation of magnitude heterogeneity

Abstract The maximum likelihood estimation of earthquake hazard parameters (maximum regional magnitude m max , activity rate λ, and the Gutenberg - Richter parameter b ) from incomplete data files is extended to the case of uncertain magnitude values. Two models of uncertainty are considered. In the first one, earthquake magnitude is specified by two values, the lower and the upper magnitude limit. It is assumed that such an interval contains the real, unknown magnitude. In the second model, uncertainty of earthquake magnitude is defined in the same way as it was proposed by Tinti and Mulargia (1985): the departure of the observed (apparent) magnitude from the true, unknown value is distributed normally. The proposed approach allows the combination of catalog parts of different quality, e.g., those where the assessment of magnitude is questionable and those with magnitudes determined very precisely. As an illustration, the proposed procedures are applied for the estimation of seismicity parameters in western Norway with adjacent sea areas.
“Las Funciones de Los Padres Y Probabilidades de Éxito”: Studying the Role Parents Play in the College Success of Socioeconomically and Educationally Disadvantaged First-Year Latin@s

ABSTRACT Using semi-structured interviews with nine socioeconomically and educationally disadvantaged Latin@s at a predominantly White institution, this phenomenological study examined the role that parents played in their success in college. Three distinct themes were identified related to academic advice, motivation, needs; encouraging their resilience; and, unexpectedly, challenging their college success. Implications for future policy and practice are highlighted, as well as recommendations for extending this important line of inquiry on Latin@s in higher education.
Fluid-induced Seismicity: Pressure Diffusion and Hydraulic Fracturing

It has been already recognized that the passive seismic monitoring has a significant potential to characterize physical processes related to fluid dynamics in hydrocarbon reservoirs. One of its conventional applications is mapping of hydraulic fracturing. However, this is not the only application. Understanding of the spatio-temporal dynamics of microseismic clouds can significantly contribute to estimating important physical characteristics of fracturing processes and of reservoir properties. For instance, r-t-analysis turns out to be very useful. E.g., plots of distances from the injection source to event hypocenters versus event occurrence times show signatures of the hydraulic fracture opening, fracturing fluid loss and its infiltration into reservoir rocks as well as the diffusion of fluid pressure into surrounding formations. The back front of the induced seismicity is especially useful for characterization of fractured domains after terminating the injection.
Which veterans in the Supportive Services for Veteran Families program receive temporary financial assistance and why: a mixed methods study

ABSTRACT The VA Supportive Services for Veteran Families (SSVF) program is one of the largest housing assistance programs in the US. One of the key components of this program is temporary financial assistance (TFA) which can be used for rent, security deposits, utilities, and other housing-related expenses. The objective of this paper was to identify characteristics of SSVF enrollees that are associated with receiving any TFA and the amount of TFA received. We conducted a mixed methods study which included a retrospective cohort study of Veterans who entered the SSVF program between 10/2015 and 9/2018 and interviews with 20 SSVF grantee employees. Important characteristics that were positively associated with TFA included African American race, female sex, having a spouse or partner, number of children, education, employment, monthly income, and receiving VA healthcare services. Factors negatively associated with receiving any TFA or the amount of TFA included older age, Medicaid insurance, previous homelessness, and a mental illness diagnosis. Interviews with grantee employees revealed that income-related factors were by far the most influential determinant of whether to give TFA and the amount of TFA to give Veterans enrolling in SSVF.
The Role of Government on Diffusion and Discontinuance of the Same ICT: Contrasting Cases of UAE and Taiwan

ABSTRACT Although the significance of governmental involvement in fostering business development has been widely researched, there appears an inadequate understanding of how different types of governmental roles lead to contrasting innovation process for small businesses. Based on an interpretive case study, our research seeks to bridge such a knowledge gap by examining RFID projects implemented in two socially and culturally distinctive contexts. The project in the UAE leads to widespread routinization in its livestock industry while the ones in Taiwan result in abrupt discontinuance. Empirical findings show that despite various issues involved the contrasting types of governmental roles might be the most decisive factor leading to such opposite results. The role played by the UAE government is categorized as strategic enforcer while the one by Taiwan’s government as innovation initiator. The former is a directive and interventional role that seeks to transform the industry while the latter is a facilitative and provisional role with no regulative involvement. Insights gained from our comparative analysis suggest that to successfully diffuse ICT projects for local industries the role played by the government and subsequent supports entailed will need to be in line with their strategic objectives. Implications for future practice and research are provided.
Demystifying and Mitigating Cross-Layer Deficiencies of Soft Error Protection in Instruction Duplication

Soft errors are prevalent in modern High-Performance Computing (HPC) systems, resulting in silent data corruptions (SDCs), compromising system reliability. Instruction duplication is a widely used software-based protection technique against SDCs. Existing instruction duplication techniques are mostly implemented at LLVM level and may suffer from low SDC coverage at assembly level. In this paper, we evaluate instruction duplication at both LLVM and assembly levels. Our study shows that existing instruction duplication techniques have protection deficiency at assembly level and are usually over-optimistic in the protection. We investigate the root-causes of the protection deficiency and propose a mitigation technique, Flowery, to solve the problem. Our evaluation shows that Flowery can effectively protect programs from SDCs evaluated at assembly level.
cuSZp: An Ultra-fast GPU Error-bounded Lossy Compression Framework with Optimized End-to-End Performance

Modern scientific applications and supercomputing systems are generating large amounts of data in various fields, leading to critical challenges in data storage footprints and communication times. To address this issue, error-bounded GPU lossy compression has been widely adopted, since it can reduce the volume of data within a customized threshold on data distortion. In this work, we propose an ultra-fast error-bounded GPU lossy compressor cuSZp. Specifically, cuSZp computes the linear recurrences with hierarchical parallelism to fuse the massive computation into one kernel, drastically improving the end-to-end throughput. In addition, cuSZp adopts a block-wise design along with a lightweight fixed-length encoding and bit-shuffle inside each block such that it achieves high compression ratios and data quality. Our experiments on NVIDIA A100 GPU with 6 representative scientific datasets demonstrate that cuSZp can achieve an ultra-fast end-to-end throughput (95.53x compared with cuSZ) along with a high compression ratio and high reconstructed data quality.
Causal Inference Using LLM-Guided Discovery

At the core of causal inference lies the challenge of determining reliable causal graphs solely based on observational data. Since the well-known backdoor criterion depends on the graph, any errors in the graph can propagate downstream to effect inference. In this work, we initially show that complete graph information is not necessary for causal effect inference; the topological order over graph variables (causal order) alone suffices. Further, given a node pair, causal order is easier to elicit from domain experts compared to graph edges since determining the existence of an edge can depend extensively on other variables. Interestingly, we find that the same principle holds for Large Language Models (LLMs) such as GPT-3.5-turbo and GPT-4, motivating an automated method to obtain causal order (and hence causal effect) with LLMs acting as virtual domain experts. To this end, we employ different prompting strategies and contextual cues to propose a robust technique of obtaining causal order from LLMs. Acknowledging LLMs' limitations, we also study possible techniques to integrate LLMs with established causal discovery algorithms, including constraint-based and score-based methods, to enhance their performance. Extensive experiments demonstrate that our approach significantly improves causal ordering accuracy as compared to discovery algorithms, highlighting the potential of LLMs to enhance causal inference across diverse fields.
Interference-aware Multiplexing for Deep Learning in GPU Clusters: A Middleware Approach

A common strategy for improving efficiency in training deep learning entails multiplexing tasks on a single GPU. To mitigate the interference caused by multiplexing, existing approaches primarily employ kernel-level solutions to regulate GPU kernel execution, or harness hardware-level techniques to explicitly restrict GPU streaming multiprocessors and memory. Nevertheless, none of them perform satisfactorily in optimizing the completion time of tasks. In this paper, we present IADeep, a middleware solution designed to significantly improve multiplexing efficiency. The core concept is the co-optimization of task assignments within a cluster and interference mitigation on each device. IADeep coordinates the configuration of all co-located tasks in a less fine-grained fashion, effectively reducing interference and enhancing task training performance. Across the entire cluster, IADeep intelligently selects applications suitable for multiplexing to further amplify the advantages of optimizing task configurations. Evaluations on a 20 RTX 3090-GPU cluster demonstrate that IADeep can significantly outperform state-of-the-art multiplexing solutions.
Online Information Filtering: The Role of Contextual Cues in Electronic Networks of Practice

Online forums sponsored by Electronic Networks of Practice are commonly used to exchange information related to problem solving, but the quality of solutions posted on forums can vary widely. To assist knowledge seekers, most forums offer contextual cues that signal solution quality, such as endorsements by the question poster, experts, or other community members. However, the influence of these cues on information-filtering decisions, particularly when presented simultaneously, remains poorly understood. This study draws on signaling theory to develop hypotheses about how four cue dimensions-source, valence, format, and volume-shape information filtering on an online forum. Results from three choice-based conjoint studies show that some sources are more influential than others and that positive cues weigh more heavily on filtering decisions than negative cues. Results also show that cues tend to be more influential when they employ a more granular format and reflect the input of a larger number of individuals.
Baltic Sea: Radionuclides

The most significant source of anthropogenic radioactivity in the Baltic Sea is fallout from the accident at the Chernobyl nuclear power plant in 1986. The second most important source is global fallout from atmospheric nuclear weapons tests carried out during the late 1950s and early 1960s. Radioactivity inputs into the Baltic Sea from nuclear reprocessing plants in Western Europe have become of minor importance due to significant reduction of discharges in recent years. In terms of input of 137Cs into the Baltic Sea, Chernobyl fallout has contributed about 82% and nuclear weapons test fallout about 14%. For 90Sr in the Baltic Sea, input from atmospheric fallout from nuclear weapons tests has contributed about 81%, while the contribution from Chernobyl fallout was about 13%. Cesium-137 is the main indicator of Baltic seawater with respect to anthropogenic radioactivity. The highest concentrations in seawater during 1999–2006 were found in the Baltic Proper and the Bothnian Sea. The general trend is steadily decreasing. Concentrations of anthropogenic radioactivity in fish generally show decreasing trends in agreement with concentrations in seawater. Among freshwater fish, pike showed large 137Cs values due to their higher concentration factors (CFs). The larger 137Cs values of pike were observed at the coast of the Bothnian Sea. The Baltic Sea is the regional sea in the world with the highest concentrations of 137Cs. The Baltic Sea ranks third in the world with respect to 90Sr in seawater; only the Irish Sea and the Black Sea show higher levels. In 1990, average concentrations of 137Cs in fish from the Baltic Sea were similar to those in the Irish Sea, about 4 times higher than in the Black Sea and about 30 times higher than in the Mediterranean Sea. Keywords: Baltic Sea; anthropogenic radionuclides; natural radionuclides; seawater; sediment; biota; inventories