Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Concrete and Realistic Data in Evaluating Initial Visualization Designs

We explore means of designing and evaluating initial visualization ideas, with concrete and realistic data in cases where data is not readily available. Our approach is useful in exploring new domains and avenues for visualization, and contrasts other visualization work, which typically operate under the assumption that data has already been collected, and is ready to be visualized. We argue that it is sensible to understand data requirements and evaluate the potential value of visualization before devising means of automatic data collection. We base our exploration on three cases selected to span a range of factors, such as the role of the person doing the data collection and the type of instrumentation used. The three cases relate to visualizing sports, construction, and cooking domain data, and use primarily time-domain data and visualizations. For each case, we briefly describe the design case and problem, the manner in which we collected data, and the findings obtained from evaluations. Afterwards, we describe four factors of our data collection approach, and discuss potential outcomes from it.
Unsupervised segmentation of continuous genomic data

UNLABELLED The advent of high-density, high-volume genomic data has created the need for tools to summarize large datasets at multiple scales. HMMSeg is a command-line utility for the scale-specific segmentation of continuous genomic data using hidden Markov models (HMMs). Scale specificity is achieved by an optional wavelet-based smoothing operation. HMMSeg is capable of handling multiple datasets simultaneously, rendering it ideal for integrative analysis of expression, phylogenetic and functional genomic data. AVAILABILITY http://noble.gs. washington.edu/proj/hmmseg
DEFECT PREDICTION : HEURISTICS FOR WEIGHTED NAÏVE BAYES

Defect prediction is an important topic in software quality research. Statistical models for defect prediction can be built on project repositories. Project repositories store software metrics and defect information. This information is then matched with software modules. Naïve Bayes is a well known, simple statistical technique that assumes the ‘independence’ and ‘equal importance’ of features, which are not true in many problems. However, Naïve Bayes achieves high performances on a wide spectrum of prediction problems. This paper addresses the ‘equal importance’ of features assumption of Naïve Bayes. We propose that by means of heuristics we can assign weights to features according to their importance and improve defect prediction performance. We compare the weighted Naïve Bayes and the standard Naïve Bayes predictors’ performances on publicly available datasets. Our experimental results indicate that assigning weights to software metrics increases the prediction performance significantly.
Hick's law in a stochastic race model with speed-accuracy tradeoffs

We present an analytic solution for a race model of n stochastic accumulators for multiple choice reaction time. We show that to maintain a constant level of accuracy, the response criterion needs to be increased approximately logarithmically with n, to compensate for the increase with n in the likelihood that an incorrect alternative will be most active after any fixed amount of time accumulating information. Assuming that participants monitor and maintain a constant level of performance can then explain the logarithmic dependency of the response latency on n as specified by Hick's law. Moreover, we show that for short time intervals, the Shannon information that observers extract from a stimulus, is predicted to increase linearly with processing time.
Acana Supplementary Materials Gotoh Algorithm

Gotoh Algorithm essentially extends the Needleman-Wunsch algorithm and the Smith-Waterman algorithm to enable them working efficiently with the affine gap cost model. In the affine gap cost model, the penalty for a gap segment is calculated by a linear function of the gap segment length. Supposing a BLOSUM scoring matrix is used for aligning a pair of sequences A and B of length m and n, respectively. The Go-toh improved Needleman-Wunsch algorithm for a optimally global alignment can be summarized by the following recursion relations: the gap extension penalty; and score(A i , B j) is the score from a substitution scoring matrix where base A i is matched with B j. The Gotoh improved Smith-Waterman algorithm uses a very similar recursion relations for finding the optimal local alignment: To track the path of a local alignment, ACANA combines information in both S and I matrices. Suppose that a local alignment ends at the position (c, d) in the alignment matrix, and (i, j) is the current position in the course of tracing back. Variables gLen1 and gLen2 are defined as the number of gaps inserted at the current position in the first and second sequence, respectively. ACANA traces the local alignment via the following steps.
Interactive Model Based on an Extended CPN

often is a great challenge due to the large amount of parallel real-time operating components. In this paper the problems of verification of such systems are discussed. ECPN, an Extended Colored Petri Net is defined to formally describe state transitions of components and interactions among components. The relationship between sequence diagrams and Free Choice Petri Nets is investigated. Free Choice Petri Net theory helps verifying the liveness of sequence diagrams. By converting sequence diagrams to ECPNs and then comparing behaviors of sequence diagram ECPNs and statecharts, the consistency among models is analyzed. Finally, a verification process for an example model is demonstrated.
Morphogenetic pattern formation during ascidian notochord formation is regulative and highly robust

Understanding how global patterns of tissue movement and deformation emerge from the combined activities of many individual cells remains a central unsolved problem in developmental biology. We consider this problem in the context of ascidian notochord formation, in which simultaneous invagination and convergent extension transforms a monolayer plate of 40 cells into a cylindrical rod (Munro and Odell, 2002). Active crawling of basolateral notochord cell edges across the faces of their adjacent neighbors accompanies this transformation and probably drives it. Basolateral crawling is biased both within the plane of the notochord plate and along the apical-basal axis in a way that could account for both invagination and convergent extension. But the source of this bias is unknown. Experimental and theoretical studies have identified many possible sources of patterned cellular behavior within tissues and these fall into two classes. First, pre-existing cytoplasmic asymmetries and/or spatial pre-patterns in the expression of “morphoregulatory” genes could determine spatial patterns of intrinsic motile and adhesive behavior before any morphogenetic movements occur. For example, pre-existing gradients of adhesivity along a specific embryonic axis might be resolved by active cell movements into oriented tissue extension (Gergen et al., 1986; Irvine and Wieschaus, 1994; Mittenthal and Mazo, 1983; Nardi and Kafatos, 1976a; Nardi and Kafatos, 1976b; Wieschaus et al., 1991). Second, interactions with surrounding tissues during morphogenesis could trigger or otherwise influence patterned cell behavior. For example, recent studies in Xenopusand Fundulusembryos suggest signals emanating from localized specific cell populations or tissue boundaries could propagate through cell populations and thereby polarize motile and adhesive behaviors within them (Domingo and Keller, 1995; Shih and Keller, 1992; Trinkaus, 1998; Trinkaus et al., 1992). Alternatively, local interactions occurring at tissue boundaries could bias the directionality of cell extension or movement, for example through contact-dependent inhibition or stabilization of protrusive behavior at planar tissue boundaries (Jacobson and Moury, 1995; Jacobson et al., 1986; Keller et al., 1989; Keller et al., 1992), or interactions with an oriented extracellular matrix at vertical tissue boundaries (Keller et al., 1991; Nakatsuji et al., 1982; Nakatsuji and Johnson, 1983; Shih and Keller, 1992). Here, we exploit the relatively simple organization and development of the ascidian embryo to assess the relative 1 Development 129, 1-12 (2002) Printed in Great Britain © The Company of Biologists Limited 2002 DEV5936
A different methodology to control and predict ground vibrations from mine blasting

Ground vibration prediction and control from mine blasting is a complex task involving disciplines such as geotechnical engineering, explosives engineering, and geology. Despite the importance of controlling ground vibrations, the mining industry commonly uses empirical methodologies based on concepts related to the nuclear tests era (charge weight scaling relationships). Over the past decade, attempts have been made to popularize more elaborate methodologies. These methods range from basic waveform superposition to analytical and numerical methods. Such methodologies are difficult to utilize daily because of their complexity, sometimes low accuracy (despite their sophistication), requirement for difficult to obtain parameters, and time needed to reach solutions using complex algorithms. In this paper, a different methodology to control and predict ground vibrations from blasting is presented. This methodology uses a semi-empirical approach, where the generation and propagation of ground vibration waves and the ground vibration characteristics at a point of interest are considered through the collection of a signature waveform. The methodology allows assessment of the optimum delay between charges to minimize and control ground vibration levels. A case study is included to demonstrate the benefits and the methodology in detail.
High-Speed Hardware Architectures and Fair FPGA Benchmarking

Performance in hardware has typically played a significant role in differentiating among leading candidates in cryptographic standardization efforts. Winners of two past NIST cryptographic contests (Rijndael in case of AES and Keccak in case of SHA-3) were ranked consistently among the two fastest candidates when implemented using FPGAs and ASICs. Hardware implementations of cryptographic operations may quite easily outperform software implementations for at least a subset of major performance metrics, such as latency, number of operations per second, power consumption, and energy usage, as well as in terms of security against physical attacks, including side-channel analysis. Using hardware also permits much higher flexibility in trading one subset of these properties for another. This paper presents high-speed hardware architectures for four lattice-based CCA-secure Key Encapsulation Mechanisms (KEMs), representing three NIST PQC finalists: CRYSTALS-Kyber, NTRU (with two distinct variants, NTRU-HPS and NTRU-HRSS), and Saber. We rank these candidates among each other and compare them with all other Round 3 KEMs based on the data from the previously reported work.
A ﬁrst-principles global multiphase equation of state for hydrogen

We present and discuss a wide-range hydrogen equation of state model based on a consistent set of ab initio simulations including quantum protons and electrons. Both the process of constructing this model and its predictions are discussed in detail. The cornerstones of this work are the speciﬁcation of simple physically motivated free energy models, a general multiparameter/multiderivative ﬁtting method
Smith ScholarWorks Smith ScholarWorks

The unipotent subgroup of a ﬁnite group of Lie type over a prime ﬁeld F p comes equipped with a natural set of generators; the properties of the Cayley graph associated to this set of generators have been much studied. In the present paper, we show that the diameter of this Cayley graph is bounded above and below by constant multiples of np + n 2 log p , where n is the rank of the associated Lie group. This generalizes the result of [E], which treated the case of SL n ( F p ). (
Effective privacy preserving in cloud computing using position aware Merkle tree model

In this research manuscript, a new protocol is proposed for predicting the available space in the cloud and verifying the security of stored data. The protocol is utilized for learning the available data, and based on this learning, the available storage space is identified, after which the cloud service providers allow for data storage. The Integrity verification separates the private and the public data, which avoids privacy issues. The integration of the private data is done with the help of cloud service providers with respect to the third-party auditing (TPA). Earlier, public key cryptography and bilinear map technologies have been combined by the researchers, but the computation time and costs were high. To secure the integrity of the data storage, the client should execute several computations. Therefore, this research suggests a reliable and effective method called position-aware Merkle tree (PMT), which is implemented for ensuring data integrity. The proposed system uses a PMT that enables the TPA to perform multiple auditing tasks with high efficiency, less computational cost and computation time. Simulation results clearly shows that the developed PMT method consumed 0.00459 milliseconds of computation time, which is limited when compared to the existing models.
Improving Deforestation Detection Accuracy in Noisy Satellite Images with Contrastive Learning-based Approach

Deforestation, the large-scale destruction of trees, has far-reaching biological and environmental consequences that pose a significant threat to the environment. Accurate deforestation detection is crucial for successful conservation initiatives and effective land management. Over the last decade, numerous deforestation detection methods utilizing spaceborne photography have been proposed. However, these methods tend to be sensitive to unique image noise in the satellite domain by virtue of the diverse aerial characteristics and air qualities in different regions. To solve this problem, we propose a novel noise-robust deforestation detection framework with a contrastive-learning based approach. The proposed framework consists of two phases: contrastive learning, which aims to extract similar feature embeddings for the same category, proceeded with transfer learning in order to develop the deforestation classifier. Remarkably, the proposed contrastive learning approach successfully handles noisy input satellite images during the feature extraction process. Upon conducting validation, we have found that the proposed method outperforms existing deforestation detection methods by a significant performance gap, highlighting the effectiveness of the proposed contrastive learning approach.
Frontiers in data analytics for adaptation research: Topic modeling

Rapid growth over the past two decades in digitized textual information represents untapped potential for methodological innovations in the adaptation governance literature that draw on machine learning approaches already being applied in other areas of computational social sciences. This Focus Article explores the potential for text mining techniques, specifically topic modeling, to leverage this data for large‐scale analysis of the content of adaptation policy documents. We provide an overview of the assumptions and procedures that underlie the use of topic modeling, and discuss key areas in the adaptation governance literature where topic modeling could provide valuable insights. We demonstrate the diversity of potential applications for topic modeling with two examples that examine: (a) how adaptation is being talked about by political leaders in United Nations Framework Convention on Climate Change; and (b) how adaptation is being discussed by decision‐makers and public administrators in Canadian municipalities using documents collected from 25 city council archives.
Production of the economically important polyunsaturated fatty acids using Rhizopus spp. isolated from the uncultivated land of Yemen

Zygomycetes especially oleaginous fungi have a great ability to produce huge quantities of lipids high in economically important poly-unsaturated fatty acids. About 32 isolates were isolated from oleaginous zygotes. Six of the 32 were identified as Rhizopus spp. identified. Tested for production of high levels of lipids. 6 out of 32 have the ability to produce huge quantities of lipids. The Rhizopus sp. UC 13 strain was selected for further optimization as it produced 1.05 gl -1 lipid with a lipid content of 39.21%. The production of lipids was increased using the Taguchi method which selected a number of factors at varying levels for the optimization process. Glucose, ammonium sulfate, temperature, pH and time directly affect lipogenesis. Saturated fatty acids (SFAs) were more prevalent than unsaturated fatty acids (USFAs) based on the GC-Mass profile, which also revealed that Caproic, Undecanoic, Tridecanoic, Palmitoleic, Heptadecanoic, Heneicosanoic, and Behenic were the most prevalent SFAs. Moreover, USFAs as Linolenic, Cis-11, 14, 17-Eicosatrienoic, Gamma-Linolenic, Cis-8, 11, 16-Docosadienoic and 14-Eicosatrienoic and Cis-13n were present in a small quantities. As a result, Rhizopus sp. UC 13 is regarded as a potential oleaginous filamentous fungus that can be applied in factories for the production of PUFAs
Three methods for determining respiratory waves from ECG (Part I)

In the diagnosis of many disease entities directly or indirectly related to disorders of respiratory parameters and heart disease, an important support would be to estimate the temporal changes in these parameters (most often respiratory wave (RW) and respiratory rate (RR)) on the basis the results of measurements of other physiological parameters of the patient. Such a possibility exists during ECG examination. The paper presents three methods for estimating RWand RR using ECG signal processing. The three procedures developed are shown: using Savitzky–Golay filtering (S-G), the ECG-Derived Respiration method (EDR) and the Respiratory Sinus Arrhythmia Analysis method (RSA). It must be clearly stated that the proposed methods are not designed to fully diagnose the patient’s respiratory function, but they can be applied to detect some conditions that are difficult to diagnose when performing an ECG, such as sleep-disordered breathing. The obtained results of the analysis were compared with those obtained from a dedicated measurement system developed by the authors. The second part of the paper will show the results of preliminary clinical verification of the developed analysis methods, taking into account the physiological parameters of the patient.
Biogeochemical climatology for the Southern Benguela Upwelling System, constructed from in situ monitoring data

Abstract. An annual and a seasonal biogeochemical climatology had been constructed for the Southern Benguela Upwelling System, from in situ data collected along a 12 station monitoring line, sampled at monthly intervals from 2001 to 2012. The monitoring line reaches a maximum offshore distance of almost 190 km, with monitoring station depths ranging from 27 to 1465 m. In addition to temperature, salinity and oxygen CTD profile data, archived monitoring data for the macro-nutrients (phosphate, nitrate + nitrite, silicate) and chlorophyll-a was evaluated. The climatologies exhibit clear spatial and seasonal variability patterns for all parameters, that yield important insight into the SBUS upwelling cycle. These data sets comprise valuable additions to our knowledge base, and will aid both future modelling efforts and studies of biogeochemical processes in upwelling systems. Data for the constructed climatologies have been made available via the PANGAEA Data Archiving and Publication database at http://doi.pangaea. de/10.1594/PANGAEA.882218 .
Multi-omics profiling reveal responses of three major Dendrobium species from different growth years to medicinal components

Dendrobium is a perennial herb found in Asia that is known for its medicinal and ornamental properties. Studies have shown that the stem is the primary medicinal component of Dendrobium spp. To investigate the effect of the species and age of Dendrobium (in years) on the content of its medicinal components, we collected the stems of 1-to-4-year-old D. officinale, D. moniliforme, and D. huoshanense, sequenced the transcriptome, metabolome, and microbiome, and analyzed the data in a comprehensive multi-omics study. We identified 10,426 differentially expressed genes (DEGs) with 644 differentially accumulated metabolites (DAMs) from 12 comparative groups and mapped the flavonoid pathway based on DEGs and DAMs. Transcriptomic and metabolomic data indicated a general trend of the accumulation of flavonoids exhibiting pharmacological effects in the three Dendrobium species. In addition, joint metabolome and microbiome analyses showed that actinobacteria was closely associated with flavonoid synthesis with increasing age. Our findings provide novel insights into the interactions of flavonoids of Dendrobium with the transcriptome and microbiome.
Unraveling Proto-Oncogene (ErbB2) Expression in Patients With Carcinoma Head of Pancreas and Chronic Pancreatitis Patients: A Case-Control Study

Background The pre-malignant tendency of the normal, non-affected portion of the pancreas is not as well explored as the multicentricity documented in pancreatic cancer cases. In order to ascertain the expression of inflammatory markers and Erythroblastic Oncogene B (ErbB2) in the non-affected pancreas in patients with pancreatic cancer, a case-control study was carried out. Materials and methods In patients who underwent pancreatoduodenectomy for pancreatic cancer (PC), pro-inflammatory genes and a tumor marker, erythroblastic oncogene 2 (ErbB2) in the epidermal growth factor receptor family were analyzed in the pancreatic tissue at the cut surface of the normal pancreas using qRT-PCR. Twenty patients diagnosed with Chronic pancreatitis (CP) after Frey's surgical procedure were selected, and their pancreatic tissues were analyzed as controls. The HPLC-purified primers were designed using National Center for Biotechnology Information (NCBI) software. The primer's specificity was verified for gene expression analysis using the Basic Local Alignment Search Tool (BLAST). The genes under study were normalized using β-actin as the housekeeping gene, and the 2-ddct method was used to compute the fold change compared to the control sample. Results Patients with margin-positive were not included. Pro-inflammatory genes (TNF-α, NF-kβ, and COX-2) had significantly lower foldchange in PC patients compared to the CP group. The CP control group had higher levels of IL-6 gene expression than the PC group. Patients with pancreatic cancer had a considerably higher expression of the ErbB2 gene than patients with CP. Conclusion The upregulated ErbB2 gene in the unaffected pancreatic tissue of pancreatic cancer patients, when compared to controls, indicates that the remaining pancreas may have the capacity to cause cancer. Proto-oncogene may play a role in the pathophysiologic process in patients with pancreatic cancer.
Major plant biome changes in the Primorye Region (Far East of Russia) during the Paleogene

Major plant biome changes in Primorye (Far East of Russia) during the Paleogene are studied using the Integrated Plant Record vegetation analysis for the first time, based on palaeobotanical records. Palaeobotanical data employed for the reconstruction comprises 54 palaeofloras covering the early Paleocene to late Oligocene, a time-span of ca. 42 myr. Our data indicate the presence of more forested conditions in Primorye during the Paleogene than at present and demonstrate the major plant biome changes from the subtropical MMF/BLEF ecotone in the late Paleocene to the warm-temperate BLDF/MMF ecotone in the late Oligocene. The obtained major plant biome changes coincide in general with the climate cooling trend. K e y w o r d s : vegetation types, climate, spatial gradients, time series