Miracle-dz/UniFAR-FTUs huggingface dataset:
Temperature, stress and spontaneous mutation in Caenorhabditis briggsae and Caenorhabditis elegans

Mutation rate often increases with environmental temperature, but establishing causality is complicated. Asymmetry between physiological stress and deviation from the optimal temperature means that temperature and stress are often confounded. We allowed mutations to accumulate in two species of Caenorhabditis for approximately 100 generations at 18°C and for approximately 165 generations at 26°C; 26°C is stressful for Caenorhabditis elegans but not for Caenorhabditis briggsae. We report mutation rates at a set of microsatellite loci and estimates of the per-generation decay of fitness (ΔMw), the genomic mutation rate for fitness (U) and the average effect of a new mutation (E[a]), assayed at both temperatures. In C. elegans, the microsatellite mutation rate is significantly greater at 26°C than at 18°C whereas in C. briggsae there is only a slight, non-significant increase in mutation rate at 26°C, consistent with stress-dependent mutation in C. elegans. The fitness data from both species qualitatively reinforce the microsatellite results. The fitness results of C. elegans are potentially complicated by selection but also suggest temperature-dependent mutation; the difference between the two species suggests that physiological stress plays a significant role in the mutational process.
Lazy Abstraction on Software Model Checking

This paper is a survey of the BLAST, which is a software model checker for C programs developed at Berkeley. Based on the popular abstract-check-refine paradigm, the concept of lazy abstraction is introduced in the BLAST project. Lazy abstraction is a new idea for the optimization of the abstract-check-refine loop. We present the lazy abstraction concept and the implementation framework of BLAST. In the end, an example of using the BLAST is also given.
Comet: batched stream processing for data intensive distributed computing

Batched stream processing is a new distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired by our empirical study on a trace from a large-scale production data-processing cluster; it allows a set of effective query optimizations that are not possible in a traditional batch processing model. We have developed a query processing system called Comet that embraces batched stream processing and integrates with DryadLINQ. We used two complementary methods to evaluate the effectiveness of optimizations that Comet enables. First, a prototype system deployed on a 40-node cluster shows an I/O reduction of over 40% using our benchmark. Second, when applied to a real production trace covering over 19 million machine-hours, our simulator shows an estimated I/O saving of over 50%.
Secure and robust high quality DWT domain audio watermarking algorithm with binary image

To enhance security and robustness of digital audio watermarking algorithms, this paper presents an algorithm based on mean-quantization in Discrete Wavelet Transform (DWT) domain. A binary image is used as a watermark, and is encrypted with chaotic encryption with secret key. This approach is based on the embedding of an encrypted watermark in the low frequency components using a two wavelet functions with adaptation to the frame size. The reason for embedding the watermark in the low frequency components is that these components' energy is high enough to embed the watermark in such a way that the watermark is inaudible; therefore, it should not alter the audible content and should not be easy to remove. The algorithm has a good security because only the authorized can detect the copyright information embedded to the host audio signal. The watermark can be blindly extracted without knowledge of the original signal. To evaluate the performance of the presented audio watermarking method, objective quality tests including bit error rate (BER), normalized cross correlation(NCC), peak-signal to noise ratio (PSNR) are conducted for the watermark and Signal-to-Noise Ratio(SNR) for audio signals. The tests' results show that the approach maintains high audio quality, and yields a high recovery rate after attacks by commonly used audio data manipulations such as noise addition, amplitude modification, low-pass filtering, re-quantization, re-sampling, cropping, cutting, and compression. Simulation results show that our approach not only makes sure robustness against common attacks, but it also further improves systemic security and robustness against malicious attack.
Navigating the confluence of streams in the development of disciplinary identity, 2004--2009

This poster presents preliminary research on the relationship between the iSchools movement and the development of disciplinary identity between 2004 and 2009, the period during which the iSchools organization was officially founded. The goal is to explore whether it is possible to identify trends that emerge from articles written by iSchool faculty and graduate students (i-authors) that appeared in five journals with high impact factor rankings in the areas of Information Science and Library Science (LIS) and Computer Science and Information Systems (CIS) as indexed in the 2009 Journal Citation Reports. These two areas were selected because they represent the disciplinary homes of the majority of the iSchools membership. Descriptive statistics including frequency tables were used to identify trends in the development of disciplinary identity in the study of information. The results suggest that iSchool authors may be selecting publication venues based on the geographic proximity of the journal rather than journal impact rankings, subject matter, or style of work affinities. The researchers plan to conduct author cocitation analysis to further examine the influence of these factors. Graphs and charts are used to present the findings in the poster itself, and additional references will be provided.
Partial Elements and Recursion via Dominances in Univalent Type Theory

We begin by revisiting partial functions in type theory, working in a constructive univalent type theory. We look at the notion of partiality via the notion of dominance , originally introduced to study synthetic computability and domain theory in topos logic, with models in realizability toposes. We then perform ﬁrst steps in computability theory within such a constructive type theory without assuming countable choice or Markov’s principle. Our guiding question is what, if any, notion of partial function allows the proposition “all partial functions from N to N are Turing computable” to be consistent in constructive univalent type theory.
An approach based on design practices to specify requirements in agile projects

The agile manifesto highlights a frequent communication with the customer to detail his/her needs and to validate the software requirements through frequent software deliveries. So, the agile methods treat the Software Requirements Specification (SRS) differently from the traditional development methods. User stories are one of the most widely used approaches to specify requirements in agile projects. However, empirical studies in the industry point out that user stories are targeted to customers, only cover simple functional requirements visible to the users, and do not address system and non-functional requirements that are also required for coding, testing, and maintaining. We propose an approach to specify requirements based on design practices targeted to the developer. We conducted an industrial case study during eight months to evaluate the proposed approach. The initial findings indicate that the SRS is closer to what will be implemented, and it meets the developers' expectations.
Assessing Lead Time of Selected Ovarian Cancer Biomarkers: A Nested Case–Control Study

Background CA125, human epididymis protein 4 (HE4), mesothelin, B7-H4, decoy receptor 3 (DcR3), and spondin-2 have been identified as potential ovarian cancer biomarkers. Except for CA125, their behavior in the prediagnostic period has not been evaluated. Methods Immunoassays were used to determine concentrations of CA125, HE4, mesothelin, B7-H4, DcR3, and spondin-2 proteins in prediagnostic serum specimens (1–11 samples per participant) that were contributed 0–18 years before ovarian cancer diagnosis from 34 patients with ovarian cancer (15 with advanced-stage serous carcinoma) and during a comparable time interval before the reference date from 70 matched control subjects who were participating in the Carotene and Retinol Efficacy Trial. Lowess curves were fit to biomarker levels in cancer patients and control subjects separately to summarize mean levels over time. Receiver operating characteristic curves were plotted, and area-under-the curve (AUC) statistics were computed to summarize the discrimination ability of these biomarkers by time before diagnosis. Results Smoothed mean concentrations of CA125, HE4, and mesothelin (but not of B7-H4, DcR3, and spondin-2) began to increase (visually) in cancer patients relative to control subjects approximately 3 years before diagnosis but reached detectable elevations only within the final year before diagnosis. In descriptive receiver operating characteristic analyses, the discriminatory power of these biomarkers was limited (AUC statistics range = 0.56–0.75) but showed increasing accuracy with time approaching diagnosis (eg, AUC statistics for CA125 were 0.57, 0.68, and 0.74 for ≥4, 2–4, and <2 years before diagnosis, respectively). Conclusion Serum concentrations of CA125, HE4, and mesothelin may provide evidence of ovarian cancer 3 years before clinical diagnosis, but the likely lead time associated with these markers appears to be less than 1 year.
A Simple Word Embedding Model for Lexical Substitution

The lexical substitution task requires identifying meaning-preserving substitutes for a target word instance in a given sentential context. Since its introduction in SemEval-2007, various models addressed this challenge, mostly in an unsupervised setting. In this work we propose a simple model for lexical substitution, which is based on the popular skip-gram word embedding model. The novelty of our approach is in leveraging explicitly the context embeddings generated within the skip-gram model, which were so far considered only as an internal component of the learning process. Our model is efficient, very simple to implement, and at the same time achieves state-ofthe-art results on lexical substitution tasks in an unsupervised setting.
Visualization Tools for Musical Timing Applied to Afro-Cuban Percussion

Timing is perhaps the most fundamental aspect of music, and visualization tools can help in formulating hypotheses and exploring questions regarding musical timing. We present a series of novel graphical representations of musical timing, generated by computer from signal analysis of audio recordings and from listeners’ annotations collected in real time. We have tested our methods on recordings of Afro-Cuban percussion with particular emphasis on the “clave” rhythmic patterns used for temporal organization. The proposed visualizations are based on the idea of Bar Wrapping, which is the breaking and stacking of a linear time axis at a fixed metric location.
Comparative Study of Linear and Nonlinear Ultrasonic Techniques for Evaluation Thermal Damage of Tube-Like Structures

Ultrasonic guided wave techniques have been widely used for long range nondestructive detection in tube-like structures. The present paper investigates the ultrasonic linear and nonlinear parameters for evaluating the thermal damage in aluminum pipe. Specimens were subjected to thermal loading. Flexible polyvinylidene fluoride (PVDF) comb transducers were used to generate and receive the ultrasonic waves. The second harmonic wave generation technique was used to check the material nonlinearity change after different heat loadings. The conventional linear ultrasonic approach based on attenuation was also used to evaluate the thermal damages in specimens. The results show that the proposed experimental setup is viable to assess the thermal damage in an aluminum pipe. The ultrasonic nonlinear parameter is a promising candidate for the prediction of micro-damages in a tube-like structure.
Irinotecan and radiosensitization in rectal cancer

Neoadjuvant radiation therapy with concurrent 5-fluorouracil-based chemotherapy is currently considered the standard of care for locally advanced rectal cancer. Pathologically complete response is a desirable outcome and has been associated with increased disease-free survival. There is a need to improve on this approach given that only approximately 10% achieve a pathologically complete response. Irinotecan has an established role in the treatment of metastatic rectal cancer. Both in-vitro and in-vivo data have shown promising radiosensitization properties. This study provides an overview of the published clinical trials evaluating the role of irinotecan as a radiosensitizer in the management of locally advanced rectal cancer. Although early-phase clinical trials initially showed promising results, this did not translate into improved outcome in a larger randomized phase II trial. Increased topoisomerase I expression has recently been identified as a possible predictive marker for improved response to irinotecan-based radiosensitization. This finding could help identify a subset of patients more likely to benefit from the addition of irinotecan in future trials.
Hotspot clustering for ad hoc network

The adaptive clustering algorithm proposed by Gerla is purely based on geographical location freedom degree and plus time freedom degree, so it's two dimensional. In this paper, three dimensional clustering based on data flow is proposed. Three freedom degrees, data flow, the diameter of clusters, and time, are considered in the course of cluster establishment to solve hotspot phenomena. Hotspots are highly congested regions in ad hoc networks that can result in packet loss, end to end delay and out of order packets delivery. Through constructing clusters around hotspots, data flow coming to hotspots can be distributed to other nodes in the cluster with alternative route to the destination. Then it can mitigate congestion of hotspots and improve performance of wireless ad hoc network. Results from simulations on the OMNET++ platform show that various QoS indicators of the network get improved by use of hotspot clustering algorithm. And resource distribution of the whole network emerges as equilibrium effects.
Efficacy of Mobile Apps to Support the Care of Patients With Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background Diabetes Mellitus (DM) is a chronic disease that is considered a global public health problem. Education and self-monitoring by diabetic patients help to optimize and make possible a satisfactory metabolic control enabling improved management and reduced morbidity and mortality. The global growth in the use of mobile phones makes them a powerful platform to help provide tailored health, delivered conveniently to patients through health apps. Objective The aim of our study was to evaluate the efficacy of mobile apps through a systematic review and meta-analysis to assist DM patients in treatment. Methods We conducted searches in the electronic databases MEDLINE (Pubmed), Cochrane Register of Controlled Trials (CENTRAL), and LILACS (Latin American and Caribbean Health Sciences Literature), including manual search in references of publications that included systematic reviews, specialized journals, and gray literature. We considered eligible randomized controlled trials (RCTs) conducted after 2008 with participants of all ages, patients with DM, and users of apps to help manage the disease. The meta-analysis of glycated hemoglobin (HbA1c) was performed in Review Manager software version 5.3. Results The literature search identified 1236 publications. Of these, 13 studies were included that evaluated 1263 patients. In 6 RCTs, there were a statistical significant reduction (P<.05) of HbA1c at the end of studies in the intervention group. The HbA1c data were evaluated by meta-analysis with the following results (mean difference, MD −0.44; CI: −0.59 to −0.29; P<.001; I²=32%). The evaluation favored the treatment in patients who used apps without significant heterogeneity. Conclusions The use of apps by diabetic patients could help improve the control of HbA1c. In addition, the apps seem to strengthen the perception of self-care by contributing better information and health education to patients. Patients also become more self-confident to deal with their diabetes, mainly by reducing their fear of not knowing how to deal with potential hypoglycemic episodes that may occur.
Analysis of polymer flow in embossing stage during thermal nanoimprint lithography

Viscous polymer flow in embossing stage during thermal nanoimprint lithography was investigated. Flow behavior of the thermoplastic polymer was analyzed numerically and experimentally. Fixed grid scheme along with the finite element method was used for numerical analysis. Effects of process parameters such as the temperature, the stamp speed, and the stamp geometry on the filling pattern for single cavity were studied. Also the patterns with several cavities were analyzed to understand the flow behavior between adjacent cavities. Experiments were performed using PMMA sheets to confirm the effects of parameters obtained from numerical analyses. Two different types of geometries were considered and the filled patterns were observed using a scanning electron microscopy. Numerical results exhibited a similar tendency as the experimental observation. POLYM. ENG. SCI., 2011. © 2010 Society of Plastics Engineers
A Direct Empirical Proof of the Existence of Dark Matter

We present new weak-lensing observations of 1E 0657-558 (z = 0.296), a unique cluster merger, that enable a direct detection of dark matter, independent of assumptions regarding the nature of the gravitational force law. Due to the collision of two clusters, the dissipationless stellar component and the fluid-like X-ray-emitting plasma are spatially segregated. By using both wide-field ground-based images and HST/ACS images of the cluster cores, we create gravitational lensing maps showing that the gravitational potential does not trace the plasma distribution, the dominant baryonic mass component, but rather approximately traces the distribution of galaxies. An 8 σ significance spatial offset of the center of the total mass from the center of the baryonic mass peaks cannot be explained with an alteration of the gravitational force law and thus proves that the majority of the matter in the system is unseen.
A Mechanistic Explanation Linking Adaptive Mutation, Niche Change, and Fitness Advantage for the Wrinkly Spreader

Experimental evolution studies have investigated adaptive radiation in static liquid microcosms using the environmental bacterium Pseudomonas fluorescens SBW25. In evolving populations a novel adaptive mutant known as the Wrinkly Spreader arises within days having significant fitness advantage over the ancestral strain. A molecular investigation of the Wrinkly Spreader has provided a mechanistic explanation linking mutation with fitness improvement through the production of a cellulose-based biofilm at the air-liquid interface. Colonisation of this niche provides greater access to oxygen, allowing faster growth than that possible for non-biofilm—forming competitors located in the lower anoxic region of the microcosm. Cellulose is probably normally used for attachment to plant and soil aggregate surfaces and to provide protection in dehydrating conditions. However, the evolutionary innovation of the Wrinkly Spreader in static microcosms is the use of cellulose as the matrix of a robust biofilm, and is achieved through mutations that deregulate multiple diguanylate cyclases leading to the over-production of cyclic-di-GMP and the stimulation of cellulose expression. The mechanistic explanation of the Wrinkly Spreader success is an exemplar of the modern evolutionary synthesis, linking molecular biology with evolutionary ecology, and provides an insight into the phenomenal ability of bacteria to adapt to novel environments.
Atrial fibrillation following autologous stem cell transplantation in patients with multiple myeloma: incidence and risk factors

Objectives: Atrial fibrillation (AF) often develops in patients with multiple myeloma following autologous stem cell transplantation (ASCT), but the exact incidence of, and the risk factors for AF have not been described. In this study, we sought to determine the incidence of AF in patients with multiple myeloma undergoing ASCT. Methods: Patients who received ASCT for multiple myeloma between January 2000 and December 2009 were identified using the ICD-9 codes for multiple myeloma and ASCT, and formed the basis of this report. Results: The study included 278 patients (mean age, 63 ± 9.5 years). A total of 75 (27%) patients developed AF at a mean duration of 14.8 days following ASCT. On multiple regression analysis, baseline renal dysfunction (odds ratio 15.2 [confidence interval 5.08–45.6]), left ventricular systolic dysfunction (9.55 [2.78–32.79]), dilated left atrium on echocardiogram (4.97 [1.8–13.78]), and hypertension (3.6 [1.36–9.52]) were significantly associated with the development of AF after ASCT. The presence of light-chain secretion (0.21 [0.07–0.6]) was associated with a lower incidence of AF. Age, gender, and race were not significantly associated with the development of AF after ASCT. Conclusions: AF is very frequent in patients with multiple myeloma when they receive ASCT. The presence of abnormal renal function, left ventricular systolic dysfunction, dilated left atrium, or hypertension at baseline identifies patients at high risk of developing AF following ASCT.
A Gaussian Belief Propagation Solver for Large Scale Support Vector Machines

Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic programming problem, which is quadratic in the number of training samples. We introduce an efficient parallel implementation of an support vector regression solver, based on the Gaussian Belief Propagation algorithm (GaBP). In this paper, we demonstrate that methods from the complex system domain could be utilized for performing efficient distributed computation. We compare the proposed algorithm to previously proposed distributed and single-node SVM solvers. Our comparison shows that the proposed algorithm is just as accurate as these solvers, while being significantly faster, especially for large datasets. We demonstrate scalability of the proposed algorithm to up to 1,024 computing nodes and hundreds of thousands of data points using an IBM Blue Gene supercomputer. As far as we know, our work is the largest parallel implementation of belief propagation ever done, demonstrating the applicability of this algorithm for large scale distributed computing systems.