Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing the human health risk of Baltic Sea sea trout (Salmo trutta L.) consumption

Abstract The current study assessed health risks posed by exposure to metals from the consumption of Baltic Sea trout (Salmo trutta L.). Concentrations of essential minerals in sea trout muscles were determined and compared with the physiological requirements of these minerals in Polish nutrition standards, recommended dietary allowances (RDA), and estimated average requirements (EAR). Chemical analyses indicated that sea trout was rich in phosphorus, calcium, magnesium, sodium, and potassium. The pattern significance gradation of the element concentrations was as follows: P>Ca>Mg>Na>K>Fe>Zn>Cu>Se>Mn>Co. Sea trout consumption can provide a considerable portion of the RDA of copper, magnesium, phosphorus, calcium, iron, and zinc. The ranking order of the mean toxic element concentrations in sea trout muscle tissues was As>Pb>Cd>Hg. Potential risk estimated with the hazard quotient (HQ) indicated that most metals posed no health risk because they did not exceed reference doses at HQ < 1. For carcinogenic and non-carcinogenic effects, the maximum allowable rates of sea trout consumption were sufficiently high to ensure human health. According to these data, the consumption of farmed sea trout from the Baltic Sea in the northern region of Pomerania, Poland did not pose a risk to human health.
Sampling-Based AQP in Modern Analytical Engines

As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often considered a second-class citizen. Modern analytical engines optimized for high-bandwidth media and multi-core architectures only exacerbate existing inefficiencies, resulting in prohibitive query-time online sampling and longer preprocessing times in offline AQP systems. We demonstrate that the sampling operators can be practical in modern scale-up analytical systems. First, we evaluate three common sampling methods, identify algorithmic bottlenecks, and propose hardware-conscious optimizations. Second, we reduce the performance penalties of the added processing and sample materialization through system-aware operator design and compare the sample creation time to the matching relational operators of an in-memory JIT-compiled engine. The cost of data reduction with materialization is up to 2.5x of the equivalent group-by in the case of stratified sampling and virtually free (∼ 1x) for reasonable sample sizes of other strategies. As query processing starts to dominate the execution time, the gap between online and offline AQP methods diminishes.
Dwell Regions: Generalized Stay Regions for Streaming and Archival Trajectory Data

A region ℛ is a dwell region for a moving object O if, given a threshold distance rq and duration τq, every point of ℛ remains within distance rq from O for at least time τq. Points within ℛ are likely to be of interest to O, so identification of dwell regions has applications such as monitoring and surveillance. We first present a logarithmic-time online algorithm to find dwell regions in an incoming stream of object positions. Our method maintains the upper and lower bounds for the radius of the smallest circle enclosing the object positions, thereby greatly reducing the number of trajectory points needed to evaluate the query. It approximates the radius of the smallest circle enclosing a given subtrajectory within an arbitrarily small user-defined factor and is also able to efficiently answer decision queries asking whether or not a dwell region exists. For the offline version of the dwell region problem, we first extend our online approach to develop the ρ-Index, which indexes subtrajectories using query radius ranges. We then refine this approach to obtain the τ-Index, which indexes subtrajectories using both query radius ranges and dwell durations. Our experiments using both real-world and synthetic datasets show that the online approach can scale up to hundreds of thousands of moving objects. For archived trajectories, our indexing approaches speed up queries by many orders of magnitude.
On Dynamically Pricing Crowdsourcing Tasks

Crowdsourcing techniques have been extensively explored in the past decade, including task allocation, quality assessment, and so on. Most of professional crowdsourcing platforms adopt the fixed pricing scheme to offer a fixed price for crowd tasks. It is neither incentive for crowd workers to produce good performance, nor profitable for the requester to gain high utility with low budget. In this article, we study the problem of pricing crowdsourcing tasks with optional bonuses. We propose a dynamic pricing mechanism, named CrowdPricer for incentively delivering bonuses to the crowd workers of completing tasks, in addition to offering a base payment for completing a task. We leverage a deep time sequence model to learn the effect of bonuses on workers’ quality for crowd tasks. CrowdPricer makes decisions on whether to provide bonuses on workers, so as to maximize the requester’s utility in expectation. We present an efficient bonus delivery algorithm under the help of beam search technique, in order to efficiently solve the decision making problem. Extensive experiments using both a real crowdsourcing platform and simulations demonstrate that CrowdPricer yields the higher utility for the requester. It also obtains more correct crowd answers than the state-of-the-art pricing methods.
HPCache: Memory-Efficient OLAP Through Proportional Caching

Analytical engines rely on in-memory caching to avoid disk accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- & time-based caching decisions, however, are a proxy of the expected query execution speedup only when disk accesses are significantly slower than in-memory query processing. On the other hand, fast storage offers loading times that approach or even outperform fully in-memory query execution response times, rendering purely frequency-based statistics incapable of capturing impact of a caching decision on query execution. For example, caching the input of a frequent query that spends most of its time processing joins is less beneficial than caching a page for a slightly less frequent but scan-heavy query. As a result, existing caching policies waste valuable memory space to cache input data that offer little-to-no acceleration for analytics. This paper proposes HPCache, a buffer management policy that enables fast analytics on high-bandwidth storage by efficiently using the available in-memory space. HPCache caches data based on their speedup potential instead of relying on frequency-based statistics. We show that, with fast storage, the benefit of in-memory caching varies significantly across queries; therefore, we quantify the efficiency of caching decisions and formulate an optimization problem. We implement HPCache in Proteus and show that i) estimating speedup potential improves memory space utilization, and ii) simple runtime statistics suffice to infer speedup expectations. We show that HPCache achieves up to 12% faster query execution over state-of-the-art caching policies, or 75% less in-memory cache footprint without deteriorating query performance. Overall, HPCache enables efficient use of the in-memory space for input caching in the presence of fast storage, without any requirement for workload predictions.
Improving In-Memory Database Operations with Acceleration DIMM (AxDIMM)

The significant overhead needed to transfer the data between CPUs and memory devices is one of the hottest issues in many areas of computing, such as database management systems. Disaggregated computing on the memory devices is being highlighted as one promising approach. In this work, we introduce a new near-memory acceleration scheme for in-memory database operations, called Acceleration DIMM (AxDIMM). It behaves like a normal DIMM through the standard DIMM-compatible interface, but has embedded computing units for data-intensive operations. With the minimized data transfer overhead, it reduces CPU resource consumption, relieves the memory bandwidth bottleneck, and boosts energy efficiency. We implement scan operations, one of the most data-intensive database operations, within AxDIMM and compare its performance with SIMD (Single Instruction Multiple Data) implementation on CPU. Our investigation shows that the acceleration achieves 6.8x more throughput than the SIMD implementation.
Formal Verification of Transcendental Fixed- and Floating-point Algorithms using an Automatic Theorem Prover

We present a method for formal verification of transcendental hardware and software algorithms that scales to higher precision without suffering an exponential growth in runtimes. A class of implementations using piecewise polynomial approximation to compute the result is verified using MetiTarski, an automated theorem prover, which verifies a range of inputs for each call. The method was applied to commercial implementations from Cadence Design Systems with significant runtime gains over exhaustive testing methods and was successful in proving that the expected accuracy of one implementation was overly optimistic. Reproducing the verification of a sine implementation in software, previously done using an alternative theorem-proving technique, demonstrates that the MetiTarski approach is a viable competitor. Verification of a 52-bit implementation of the square root function highlights the method’s high-precision capabilities.
Estimation of the Size of Union of Delphic Sets: Achieving Independence from Stream Size

Given a family of sets (S1, S2,. SM) over a universe Ω, estimating the size of their union in the data streaming model is a fundamental computational problem with a wide variety of applications. The holy grail in the field of streaming is to seek design of algorithms that achieve (ε, δ)-approximation with poly(log |Ω|, ε-1, log δ-1) space and update time complexity. Earlier investigations achieve algorithms with desired space and update time complexity for restricted cases such as singletons (Distinct Elements problem), one-dimensional ranges, arithmetic progressions, and sub-cubes. However, techniques used in these works fail for many other simple structured sets. A prominent example is that of Klee's Measure Problem (KMP), wherein every set Si is represented by an axis-parallel rectangle in d-dimensional spaces. Despite extensive prior work, the best-known streaming algorithms for many of these cases depend on the size of the stream, and therefore the problem of whether there exists a streaming algorithm for estimations of size of the union of sets with poly(log |Ω|, ε-1, log δ-1) space and update time complexity has remained open. In this work, we focus on certain general families of sets called Delphic families (which allows efficient membership, sampling, and cardinality queries). Such families of sets capture several well-known problems, including KMP, test coverage, and hypervolume estimation. The primary contribution of our work is to resolve the above-mentioned open problem for streams over Delphic families. In particular, we design the first streaming algorithm for estimating |⋃i=1M Si| with poly(log |Ω|, ε-1, log δ-1) space and update time complexity (independent of M, the length of the stream) when each Si is a member from a Delphic family of sets. We further generalize our results to larger families of sets, called approximate-Delphic families, for which the size of a set can be known approximately but not exactly. Our results resolve two of the open problems listed in Meel, Vinodchandran, Chakraborty (PODS-21).
Fibonacci spirals may not need the Golden Angle

Abstract Abstract Phyllotaxis, the regular arrangement of plant lateral organs, is an important aspect of quantitative plant biology. Some models relying on the geometric relationship of the shoot apex and organ primordia focus mainly on spiral phyllotaxis, a common phyllotaxis mode. While these models often predict the dependency of Fibonacci spirals on the Golden Angle, other models do not emphasise such a relation. Phyllotactic patterning in Asteraceae is one such example. Recently, it was revealed that auxin dynamics and the expansion and contraction of the active ring of the capitulum (head) are the key processes to guide Fibonacci spirals in gerbera (Gerbera hybrida). In this Insights paper, we discuss the importance of auxin dynamics, distinct phases of phyllotactic patterning, and the transition of phyllotaxis modes. These findings signify the local interaction among primordia in phyllotactic patterning and the notion that Fibonacci spirals may not need the Golden Angle.
Posttranslational regulation of transporters important for 3 symbiotic interactions 4 5

5 Tami R. McDonald 1 , Madeeha F. Rizvi 2 , Bretton L. Ruiter 2 , Rahul Roy 1 , Anke Reinders 3 , John 6 M. Ward 2* 7 8 9 10 11 1 Biology Department, St. Catherine University, St. Paul, MN, USA 12 2 Department of Plant and Microbial Biology, University of Minnesota, USA 13 3 College of Continuing and Professional Studies, University of Minnesota, USA 14 15 *Corresponding author: jward@umn.edu 16 17 18 The author responsible for distribution of materials integral to the findings presented in this 19 article in accordance with the policy described in the Instructions for Authors 20 (https://academic.oup.com/plphys/pages/General-Instructions) is John M. Ward 21 (jward@umn.edu) 22 23 One-sentence summary: Regulation of transport proteins involved in mycorrhizal and rhizobial 24 symbioses is best understood by incorporating what is known about regulation of related 25 transporter proteins in the same family. 26 27 Author contributions: Concept: JMW and TRM; writing: MFR, BLR, RR, AR, TRM, and JMW; 28 development of figures: RR. 29 30 31 32 33 34 35 36 37
Teaching Machine Learning in 2020

Faced by the abundant use of machine learning in industry and academia, the effective and efﬁ-cient teaching of core concepts in this ﬁeld becomes of high importance. For this, we organized a workshop on teaching methods in the ﬁeld of machine learning. In this document, we summarize the current standing of the community as by our workshop and their methods. We touch on existing working concepts in machine learning di-dactics, what methods present initiatives use and cover open teaching resources available to date. With this, we hope to provide a starting point for future collaborations on this central topic given the expanding use of machine learning in science, industry and our daily lives.
On the Asymmetry of the Tropical Pacific Thermocline Fluctuation Associated With ENSO Recharge and Discharge

The El Niño/Southern Oscillation (ENSO) plays a crucial role in a successful climate prediction at seasonal‐interannual time scales. One of the challenges of forecasting the ENSO is from the non‐cyclical feature, which is linked to the ocean heat discharge and recharge processes of the equatorial Pacific. We note that there are appreciable differences in both the intensities and spatial patterns associated with preceding thermocline fluctuation in the tropical Pacific between the recharge and discharge phases of ENSO. Preceding thermocline anomalies in the western and central deep tropical Pacific contribute to the recharge phase of ENSO, while preceding thermocline anomalies in the western (eastern) tropical Pacific have a positive (negative) contribution to the discharge phase of ENSO. The contrastive connections with the preceding thermocline fluctuation are mainly due to the asymmetric wind stress anomalies associated with El Niño and La Niña.
Simulated Experince Evaluation in Developing Multi-agent Coordination Graphs

Cognitive science has proposed that a way people learn is through self-critiquing by generating 'what-if' strategies for events (simulation). It is theorized that people use this method to learn something new as well as to learn more quickly. This research adds this concept to a graph-based genetic program. Memories are recorded during fitness assessment and retained in a global memory bank based on the magnitude of change in the agent’s energy and age of the memory. Between generations, candidate agents perform in simulations of the stored memories. Candidates that perform similarly to good memories and differently from bad memories are more likely to be included in the next generation. The simulationinformed genetic program is evaluated in two domains: sequence matching and Robocode. Results indicate the algorithm does not perform equally in all environments. In sequence matching, experiential evaluation fails to perform better than the control. However, in Robocode, the experiential evaluation method initially outperforms the control then stagnates and often regresses. This is likely an indication that the algorithm is over-learning a single solution rather than adapting to the environment and that learning through simulation includes a satisficing component.
Role in the Development of Cell Polarity and Interactions with the Ras Pathway in Saccharomyces cerevisiae

DNAX Research Institute of Molecular and Cellular Biology, Palo Alto, California 943041; Department of Biology, The University of Michigan, Ann Arbor, Michigan 481092; Department of Biology, University of Tokyo, Tokyo 113, Japan3; Department of Biochemistry, UMDNJ-Robert Wood Johnson Medical School, Piscataway, New Jersey 088544; and Department of Biochemistry, Kobe University School of Medicine, Kobe 650, Japan5
Telematic integration of health data: the INTESA project

: Following an approach based on the methods of basic research, the INTESA project has developed a complete architecture of health information system, capable to guarantee a smart and safe storing of the essential information, an effective and personalized retrieval of data, and some innovative models to compare the results of clinical and medical activities of all the “actors” of the health care process. Together with other metropolitan repositories based on HL7 messages and applications able to examine the data stored, the developed archive will contribute to keep a check on every citizen’s health history, clinical examinations and cure therapies, but, above all, it will allow to verify the efficacy and efficiency of the health care processes related to particular pathologies.
The vestigial(vg) gene of Drosophilaplays

The development and patterning of structures such as teeth, limbs, heart or liver are complex processes that rely on the spatial and temporal orchestration of cell interactions. These in turn rely on signalling systems but, in the last few years, it has become clear that a specific structure is not the outcome of specific signalling events. On the contrary, the available information suggests that there is a limited number of signalling systems which often work through a small number of effectors to elicit a great variety of responses. The specificity of the outcome resides on the effectors available to the signalling system through the history of the cell. For example, in vertebrates, Sonic Hedgehog (Shh) is involved in the development and patterning of the limb, the specification of the floor plate, the determination of neuronal cell fates and other processes (Riddle et al., 1993; Echelard et al., 1993). For each of these functions, Shh controls specific sets of genes. However, it always does it through the same signal transduction pathway and therefore something has to confer a particular interpretation of these signals in a specific manner: tooth, limb, heart or liver. As a group of cells develop into a particular structure, something has to keep the ‘group identity’ constant. The wing of Drosophila provides a useful system to unravel the molecular basis of this notion of identity. Developmental studies have shown that the vestigial (vg) gene encodes a nuclear protein that plays a central role in the development of e wings in Drosophila: loss of vg results in the failure of wings to develop (Lindsley and Zimm, 1992) and ectopic expression of vg leads to the development of ectopic wing tissue (Kim et al., 1996). These experiments suggest that vestigialcan be viewed as a ‘wing selector’ gene i.e. a gene that enforces wing developmental pathway on cells (Kim et al., 1996). This notion is supported by the observation that ectopic expression of vestigial can rescue the loss of wing caused by mutations in genes involved in the regulation of wing development such as apterous, Suppressor of Hairless or wingless(Klein and Martinez Arias, 1998a). The expression of vg during wing development is regulated through two enhancers called the second intron or boundary enhancer (vgBE), and the quadrant enhancer ( vgQE) (Williams et al., 1994; Kim et al., 1996; and Fig. 1). These names reflect the patterns of expression directed by these regulatory regions: the vestigial Boundary Enhancer ( vgBE), a thin stripe over the prospective wing margin, and vestigial quadrant enhancer (vgQE), a pattern in four quadrants that are complementary to the vgBE and which fill in the developing wing blade. Both, vgBE and vgQE, act as integrators of signalling systems that drive wing development and, in this manner, these regulatory regions determine the tempo and the mode of wing development (Williams et al., 1994; Kim et al., 1996). 913 Development 126, 913-925 (1999) Printed in Great Britain © The Company of Biologists Limited 1999 DEV1380
Characteristics of People Seeking Prescribed Cannabinoids for the Treatment of Chronic Pain: Evidence From Project Twenty 21

Background Prescribed cannabinoids are now legal in the UK and increasingly being used for a variety of conditions, with one of the most frequent conditions being chronic pain. This paper describes the characteristics of individuals seeking prescribed cannabinoids for the treatment of chronic pain in Project Twenty 21, a UK based real world data registry of prescribed cannabis patients. Method By 1st November 2021 data were available for 1,782 people who had sought treatment with medical cannabis as part of Project Twenty 21. The most common diagnosis among this cohort was chronic pain with 949 (53.5%) of the cohort reporting a primary condition related to chronic pain. Medical and self-report data on the characteristics of these patients, their health status and type/s of cannabinoid/s prescribed are summarized in this report. Results Of the 949 people reporting chronic pain as a primary condition 54.7% were male and their average age was 42.0 years (range = 18–84). Patients reported a low quality of life and high levels of comorbidity: people reported an average of 4.6 comorbid conditions with the most common comorbid conditions including anxiety, depression, insomnia and stress. A range of cannabinoid products were prescribed with the most common products being classified as high THC flower (48.5%). The majority of patients also reported using at least one other prescribed medication (68.7%). Conclusions Consistent with findings in other national and international databases, chronic pain was the most common primary condition in this real world study of prescribed cannabinoids. There was considerable variation in the types of chronic pain, comorbid pathology and in the characteristics of products being prescribed to treat these conditions. Together, this evidence supports the utility of real world evidence, as opposed to clinical trial approaches to studying the potential benefits of prescribed cannabinoids in treating chronic pain.