Miracle-dz/UniFAR-FTUs huggingface dataset:
A ality Type-aware Annotated Corpus and Lexicon for Harassment Research

A quality annotated corpus is essential to research. Despite the recent focus of the Web science community on cyberbullying research, the community lacks standard benchmarks. This paper provides both a quality annotated corpus and an offensive words lexicon capturing different types of harassment content: (i) sexual, (ii) racial, (iii) appearance-related, (iv) intellectual, and (v) political1. We first crawled data from Twitter using this content-tailored offensive lexicon. As mere presence of an offensive word is not a reliable indicator of harassment, human judges annotated tweets for the presence of harassment. Our corpus consists of 25,000 annotated tweets for the five types of harassment content and is available on the Git repository2.
Fast integration of DPG matrices based on tensorization (Part II—Prismatic elements)

Higher order finite element (FE) methods provide significant advantages in a number of applications such as wave propagation, where high order shape functions help to mitigate pollution (dispersion) error. However, classical assembly of higher order systems is computationally burdensome, requiring the evaluation of many point quadrature schemes. When the Discontinuous Petrov-Galerkin (DPG) FE methodology is employed, the use of an enriched test space further increases the computational burden of system assembly, increasing the relevance of improved assembly techniques. Sum factorization—a technique that exploits the tensor-product structure of shape functions to accelerate numerical integration—was proposed in [6] for the assembly of DPG matrices on hexahedral elements that reduced the computational complexity from order O(p) to O(p) (where p denotes polynomial order). In this work we extend the concept of sum factorization to the construction of DPG matrices on prismatic elements by expressing prism shape functions as tensor products of 2D simplex and 1D interval shape functions. Unexpectedly, the resulting sum factorization routines on partially-tensorized prism shape functions achieve the same O(p) complexity as sum factorization on fully-tensorized hexahedra shape functions (as products of 1D interval shape functions) presented in [6]. Throughout this work we adhere to the theory of exact sequence energy spaces, proposing sum factorization routines for each of the 3D FE exact sequence energy spaces—H, H(curl), H(div), and L. Computational results for construction of the DPG Gram matrix on a prismatic element in each exact sequence energy space are presented, corroborating the expected O(p) complexity. Additionally, construction of the DPG system for an ultraweak Maxwell problem on a prismatic element is considered and a partially-tensorized sum factorization for hexahedral elements is proposed to improve implementational compatibility between hexahedral and prismatic elements.
Detection of Antibiotic Resistance Genes in Source and Drinking Water Samples from a 1 First Nation Community in Canada 2

Detection of Antibiotic Resistance Genes in Source and Drinking Water Samples from a 1 First Nation Community in Canada 2 Dinesh M. Fernando, Hein Min Tun, Jenna Poole, Rakesh Patidar, Ru Li, Ruidong Mi, 3 Geethani E. A. Amarawansha, W. G. Dilantha Fernando, Ehsan Khafipour, Annemieke 4 Farenhorst, Ayush Kumar 5 Departments of Microbiology, Animal Science, Soil Science, Plant Science, and Medical 6 Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada. 7 Running Head: Antibiotic resistance genes in drinking water 8 9 Address correspondence to: Ayush.Kumar@umanitoba.ca 10
SPATIAL VARIABILITY OF SATURATED HYDRAULIC CONDUCTIVITY AND THRESHOLDS FOR SLOPE FAILURE

Author(s): Alessio, Paul | Advisor(s): Keller, Ed A | Abstract: Shallow landslides are commonly triggered by positive pore-fluid pressures linked to heavy rainfall. Positive pore-fluid pressures are generated at low-conductivity layers that occur within the soil profile or at the soil-bedrock interface. In this study, in situ measurements of saturated hydraulic conductivity (Ksat) were performed at three historic debris flow sites to determine its variability and implications for triggering debris flows at Sedgwick Reserve, California. Falling head tests were performed in the soil column within each horizon and at the soil-bedrock interface to estimate Ksat. It was found that the failure plane exhibited Ksat values ranging from 4 to 33 mm/hr, whereas overlying soils of the A and B/Bt horizons exhibited higher infiltration rates, ranging from 37-138 mm/hr and 24-127 mm/hr, respectively. Below the failure plane, Ksat ranged from 4 to 120 mm/hr, signifying a pattern of fast-slow-fast infiltration. Measurements of grain size distributions and bulk density do not provide insight into the cause of low-conductivity at the soil-bedrock interface. Rather, field observations suggest that the infilling of fractures with fine-grained particles at the soil-bedrock interface may be the cause of the low-conductivity layer. Statistical analyses also show that Ksat has a strong dependence on soil horizon. Hillslope parameters and measurements of soil mechanical properties were used in a finite slope-stability model to predict thresholds for failure. Results of the stability analysis predict failure at 35-50% saturation of the soil column above the failure plane. This study suggests that the vertical patterns and spatial variability in hydraulic conductivities of landslide-prone soils are important factors in predicting slope stability.
Material descriptors for morphotropic phase boundary curvature in lead-free piezoelectrics

An important aspect of searching for alternatives to the current piezoelectric workhorse PZT (PbZrxTi1−xO3) is to establish a vertical morphotropic phase boundary (MPB) in the composition-temperature phase diagram. However, the MPBs in most lead-free piezoelectrics, especially the BaTiO3-based piezoelectrics, are not as vertical as that of PZT, resulting in serious temperature dependence of piezoelectric and dielectric properties. We investigate the dependence of the verticality of the MPB on polarization and strain related design descriptors in BaTiO3-based and Pb-based systems. We find that the slope of the MPB decreases monotonically with the unit cell volume ratio of the tetragonal (T) and rhombohedral (R) ends; however, it increases with the ionic displacement ratio of the two ends. As the above two descriptors are not straight forward to access as a priori information, two parameters that relate to the atomic size and effective nuclear charge are introduced to enable an effective search for a desire.
APPRENTICE: USING KNOWLEDGE DISTILLATION TECHNIQUES TO IMPROVE LOW-PRECISION NET-

Deep learning networks have achieved state-of-the-art accuracies on computer vision workloads like image classification and object detection. The performant systems, however, typically involve big models with numerous parameters. Once trained, a challenging aspect for such top performing models is deployment on resource constrained inference systems — the models (often deep networks or wide networks or both) are compute and memory intensive. Low-precision numerics and model compression using knowledge distillation are popular techniques to lower both the compute requirements and memory footprint of these deployed models. In this paper, we study the combination of these two techniques and show that the performance of low-precision networks can be significantly improved by using knowledge distillation techniques. Our approach, Apprentice, achieves state-of-the-art accuracies using ternary precision and 4-bit precision for variants of ResNet architecture on ImageNet dataset. We present three schemes using which one can apply knowledge distillation techniques to various stages of the train-and-deploy pipeline.
Dynamical Systems Theory and Explanatory Indispensability

I examine explanations’ realist commitments in relation to dynamical systems theory. First I rebut an ‘explanatory indispensability argument’ for mathematical realism from the explanatory power of phase spaces. Then I critically consider a possible way of strengthening the indispensability argument by reference to attractors in dynamical systems theory. The take-home message is that understanding of the modal character of explanations (in dynamical systems theory) can undermine Platonist arguments from explanatory indispensability.
Aggregated Learning: A Vector Quantization Approach to Learning with Neural Networks

We establish an equivalence between information bottleneck (IB) learning and an unconventional quantization problem, `IB quantization'. Under this equivalence, standard neural network models correspond to scalar IB quantizers. We prove a coding theorem for IB quantization, which implies that scalar IB quantizers are in general inferior to vector IB quantizers. This inspires us to develop a learning framework for neural networks, AgrLearn, that corresponds to vector IB quantizers. We experimentally verify that AgrLearn applied to some deep network models of current art improves upon them, while requiring less training data. With a heuristic smoothing, AgrLearn further improves its performance, resulting in new state of the art in image classification on Cifar10.
A Unit Selection Methodology for Music Generation Using Deep Neural Networks

In this work we describe and evaluate methods to learn musical embeddings. Each embedding is a vector that represents four contiguous beats of music and is derived from a symbolic representation. We consider autoencoding-based methods including denoising autoencoders, and context reconstruction, and evaluate the resulting embeddings on a forward prediction and a classification task.
HyperSLICE: HyperBand optimised Spiral for Low-latency Interactive Cardiac Examination

BACKGROUND: Interactive cardiac magnetic resonance imaging is used for fast scan planning and MR guided interventions. However, the requirement for real-time acquisition and near real-time visualization constrains the achievable spatio-temporal resolution. PURPOSE: To improve interactive imaging resolution through optimization of undersampled spiral sampling and leveraging of deep learning for low-latency reconstruction (deep artifact suppression).
Kegiatan Keagamaan Doa Bersama untuk Pembentukan Karakter Religius

Penelitian ini merupakan penelitian kualitatif dengan menggunakan metode deskriptif yang bertujuan untuk mendeskripsikan dan menjelaskan kontribusi kegiatan keagamaan doa bersama untuk pembentukan karakter religius pada kelas XI SMA Negeri 10 Samarinda tahun ajaran 2022/2023. Karakter religius merupakan karakter yang berkaitan dengan Tuhan Yang Maha Esa dimana dalam bersikap dan berperilaku sesuai dengan ajaran agama yang dianutnya. Program pembiasaan merupakan suatu kegiatan yang dilakukan secara berulang-ulang, berkelanjutan, serta continue sehingga menimbulkan seseorang terbiasa untuk bertindak dan berperilaku sesuai aturan sehingga tujuan yang direncanakan dapat tercapai. Berdasarkan hasil penelitian yang telah dilakukan bahwa penerapan program pembiasaan doa bersama pada siswa kelas XI yaitu dimulai dari pukul 07.15 WIB, yang dimulai dari masuk kelas, membaca al-quran, doa, lalu diakhiri menyanyikan lagu nasional. Dalam penerapannya juga didampingi oleh guru mata pelajaran jam pertama dan guru yang berada di ruang radio untuk memastikan agar siswa melaksanakan program pembiasaan doa bersama secara maksimal. Program pembiasaan doa bersama juga berpengaruh terhadap pembentukan karakter religius siswa di SMA Negeri 10 Samarinda.
Multi-Processor Approximate Message Passing with Lossy Compression

—We consider large-scale linear inverse problems in Bayesian settings. Our general approach follows a recent line of work that applies the approximate message passing (AMP) framework in multi-processor (MP) computational systems by storing and processing a subset of rows of the measurement matrix along with corresponding measurements at each MP node. In each MP-AMP iteration, nodes of the MP system and its fusion center exchange messages pertaining to their estimates of the input. Unfortunately, communicating these messages is often costly in applications such as sensor networks. To reduce the communication costs, we apply lossy compression to the messages. To improve compression, we realize that the rate distortion trade-off differs among MP-AMP iterations, and use dynamic programming (DP) to optimize per-iteration coding rates. Numerical results conﬁrm that the proposed coding rates offer signiﬁcant and often dramatic reductions in communication costs. That said, computational costs involve two matrix vector products per MP-AMP iteration, which may be signiﬁcant for large matrices. Therefore, we further improve the trade-off between computational and communication costs with a modiﬁed DP scheme. Case studies involving sensor networks and large-scale computing systems highlight the potential of our approach.
Stability of calibration procedures: fractals in the Black-Scholes model

Usually, in the Black-Scholes pricing theory the volatility is a positive real parameter. Here we explore what happens if it is allowed to be a complex number. The function for pricing a European option with a complex volatility has essential singularities at zero and infinity. The singularity at zero reflects the put-call parity. Solving for the implied volatility that reproduces a given market price yields not only a real root, but also infinitely many complex roots in a neighbourhood of the origin. The Newton-Raphson calculation of the complex implied volatility has a chaotic nature described by fractals.
The Theory is Predictive, but is it Complete?: An Application to Human Perception of Randomness

When we test a theory using data, it is common to focus on correctness: do the predictions of the theory match what we see in the data? But we also care about completeness: how much of the predictable variation in the data is captured by the theory? This question is difficult to answer, because in general we do not know how much "predictable variation" there is in the problem. In this paper, we consider approaches motivated by machine learning algorithms as a means of constructing a benchmark for the best attainable level of prediction. We illustrate our methods on the task of prediction of human-generated random sequences. Relative to an atheoretical machine learning algorithm benchmark, we find that existing behavioral models explain roughly 10 to 12 percent of the predictable variation in this problem. This fraction is robust across several variations on the problem. We also consider a version of this approach for analyzing field data from domains in which human perception and generation of randomness has been used as a conceptual framework; these include sequential decision-making and repeated zero-sum games. In these domains, our framework for testing the completeness of theories suggest that existing theoretical models may be more complete in their predictions for some domains than for others, suggesting that our methods can offer a comparative perspective across settings. Overall, our results indicate that (i) there is a significant amount of structure in this problem that existing models have yet to capture and (ii) there are rich domains in which machine learning may provide a viable approach to testing completeness.
Distinct Subtypes of Hepatorenal Syndrome and Associated Outcomes as Identified by Machine Learning Consensus Clustering

Background: The utilization of multi-dimensional patient data to subtype hepatorenal syndrome (HRS) can individualize patient care. Machine learning (ML) consensus clustering may identify HRS subgroups with unique clinical profiles. In this study, we aim to identify clinically meaningful clusters of hospitalized patients for HRS using an unsupervised ML clustering approach. Methods: Consensus clustering analysis was performed based on patient characteristics in 5564 patients primarily admitted for HRS in the National Inpatient Sample from 2003–2014 to identify clinically distinct HRS subgroups. We applied standardized mean difference to evaluate key subgroup features, and compared in-hospital mortality between assigned clusters. Results: The algorithm revealed four best distinct HRS subgroups based on patient characteristics. Cluster 1 patients (n = 1617) were older, and more likely to have non-alcoholic fatty liver disease, cardiovascular comorbidities, hypertension, and diabetes. Cluster 2 patients (n = 1577) were younger and more likely to have hepatitis C, and less likely to have acute liver failure. Cluster 3 patients (n = 642) were younger, and more likely to have non-elective admission, acetaminophen overdose, acute liver failure, to develop in-hospital medical complications and organ system failure, and to require supporting therapies, including renal replacement therapy, and mechanical ventilation. Cluster 4 patients (n = 1728) were younger, and more likely to have alcoholic cirrhosis and to smoke. Thirty-three percent of patients died in hospital. In-hospital mortality was higher in cluster 1 (OR 1.53; 95% CI 1.31–1.79) and cluster 3 (OR 7.03; 95% CI 5.73–8.62), compared to cluster 2, while cluster 4 had comparable in-hospital mortality (OR 1.13; 95% CI 0.97–1.32). Conclusions: Consensus clustering analysis provides the pattern of clinical characteristics and clinically distinct HRS phenotypes with different outcomes.
Animal Cytogenetics and Comparative Mapping

a Department of Zoology, The University of Melbourne, Melbourne; b Comparative Genomics Research Group and the ARC Centre for Kangaroo Genomics, Research School of Biological Sciences, Australian National University, Canberra; c Department of Genetics, LaTrobe University, Bundoora; d Department of Molecular Biosciences and Centre for Evolutionary Biology and Biodiversity, The University of Adelaide, Adelaide (Australia); e Genomics Division, Lawrence Berkeley National Laboratory, Berkeley (USA); f Victorian Bioinformatics Consortium, Monash University, Clayton; g Bone and Joint Research Laboratory, Institute of Medical and Veterinary Science, Adelaide (Australia)
Animal Cytogenetics and Comparative Mapping

ABC Fax + 41 61 306 12 34 E-mail karger@karger.ch www.karger. com © 2001 S. Karger AG, Basel 0301–0171/01/0942–0049$17.50/0 Accessible online at: www.karger. com/journals/ccg Abstract. A comparative map of human chromosome 12 (HSA 12) and pig chromosome 5 (SSC 5) was constructed using ten pig expressed sequence tags (ESTs). These ESTs were isolated from primary granulosa cell cultures by differential display (EST b10b), or from a granulosa cDNA library (VIIIE1, DRIM, N*9, RIIID2 and RVIC1) or from a small intestine cDNA library (ATPSB, ITGB7, MYH9, and STAT2). Also used were two Traced Orthologous Amplified Sequence Tags (TOASTs) (LALBA, TRA1), one microsatellite-associated gene (IGF1) and finally five human YACs selected for their cytogenetic position, with a view to increasing the number of informative markers for the comparison. Large-insert clones were obtained by screening a pig bacterial artificial chromosome (BAC) library with specific primers for each EST and TOAST and for IGF1. These BACs were used as probes for fluorescent in situ hybridisation (FISH) both on porcine and human metaphases. In addition, the human YACs were FISH mapped on pig chromosomes. This allowed us to refine and, in some cases, to correct the previous mapping obtained with a somatic cell hybrid panel. While these data confirm chromosome painting results showing that the distal part of SSC 5p arm is conserved on HSA 22, while the rest of the chromosome corresponds to HSA 12, they also demonstrate gene-order differences between human and pig. In addition, it was also possible to determine the position of the synteny breakpoint.
Animal Cytogenetics and Comparative Mapping

ABC Fax + 41 61 306 12 34 E-mail karger@karger.ch www.karger. com © 2001 S. Karger AG, Basel 0301–0171/01/0934–0297$17.50/0 Accessible online at: www.karger. com/journals/ccg Abstract. In order to expand the comparative map between human chromosome 3 (HSA3) and porcine chromosome 13 (SSC13), seven genes from HSA3 were mapped on SSC13 by fluorescence in situ hybridisation (FISH), viz. ACAA1, ACPP, B4GALT4, LTF, MYLK, PDHB and RARB. With a view to integrating this expanded comparative map with the existing SSC13 linkage map, we used the INRA-University of Minnesota porcine Radiation Hybrid panel (IMpRH) to localize more precisely and to order 15 genes on the SSC13 map, viz. ACPP, ADCY5, APOD, BCHE, CD86, DRD3, GAP43, PCCB, RAF1, RHO, SI, TF, TFRC, TOP2B and ZNF148. In this way, we were able to create an integrated map, containing 38 type I and 81 type II markers, by correlating the linkage, radiation hybrid (RH) and cytogenetic maps of SSC13. This integrated map will give us the opportunity to take maximal advantage of the comparative mapping strategy for positional candidate cloning of genes responsible for economically important traits.
Cooling Codes: Thermal-Management Coding for High-Performance Interconnects

High temperatures have dramatic negative effects on interconnect performance and, hence, numerous techniques have been proposed to reduce the power consumption of on-chip buses. However, existing methods fall short of fully addressing the thermal challenges posed by high-performance interconnects. In this paper, we introduce new efficient coding schemes that make it possible to directly control the <italic>peak temperature</italic> of a bus by effectively cooling its hottest wires. This is achieved by avoiding state transitions on the hottest wires for as long as necessary until their temperature drops off. We also reduce the <italic>average power consumption</italic> by making sure that the total number of state transitions on all the wires is below a prescribed threshold. We show how each of these two features can be coded for separately or, alternatively, how both can be achieved at the same time. In addition, <italic>error-correction</italic> for the transmitted information can be provided while controlling the peak temperature and/or the average power consumption. In general, our cooling codes use <inline-formula> <tex-math notation="LaTeX">$n > k$ </tex-math></inline-formula> wires to encode a given <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-bit bus. One of our goals herein is to determine the minimum possible number of wires <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> needed to encode <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> bits while satisfying any combination of the three desired properties. We provide full theoretical analysis in each case. In particular, we show that <inline-formula> <tex-math notation="LaTeX">$n = k+t+1$ </tex-math></inline-formula> suffices to cool the <inline-formula> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula> hottest wires, and this is the best possibility. Moreover, although the proposed coding schemes make use of sophisticated tools from combinatorics, discrete geometry, linear algebra, and coding theory, the resulting encoders and decoders are fully practical. They do not require significant computational overhead and can be implemented without sacrificing a large circuit area.