Miracle-dz/UniFAR-FTUs huggingface dataset:
CLASSIFYING AND RECOMMENDING KNOWLEDGE IN REFERENCE DOCUMENTATION TO IMPROVE API USABILITY

Reference documentation is an important source of information on API usage. Programmers, however, can easily overlook reference information because of its tedious nature, and because the information they seek can be buried among irrelevant or boiler-plate text. We propose to detect and recommend fragments of API documentation relevant and important to a task. We categorize pieces of information in API documentation based on the type of knowledge they contain. From the pieces that contain knowledge worthy of recommendation, we extract the composition and the pattern of words, and use the patterns to automatically find new pieces that contain similar knowledge. In an evaluation study, with a training set of manually-classified reference documentation of about 1 000 API elements, we could issue recommendations with about, on average, 90% precision and 69% recall.
A Robust Protocol to Increase NimbleGen SeqCap EZ Multiplexing Capacity to 96 Samples

Contemporary genetic studies frequently involve sequencing of a targeted gene panel, for instance consisting of a set of genes associated with a specific disease. The NimbleGen SeqCap EZ Choice kit is commonly used for the targeted enrichment of sequencing libraries comprising a target size up to 7 Mb. A major drawback of this commercially available method is the exclusive use of single-indexing, meaning that at most 24 samples can be multiplexed in a single reaction. In case of relatively small target sizes, this will lead to excessive amounts of data per sample. We present an extended version of the NimbleGen SeqCap EZ protocol which allows to robustly multiplex up to 96 samples. We achieved this by incorporating Illumina dual-indexing based custom adapters into the original protocol. To further extend the optimization of cost-efficient sequencing of custom target panels, we studied the effect of higher pre-enrichment pooling factors and show that pre-enrichment pooling of up to 12 samples does not affect the quality of the data. To facilitate evaluation of capture efficiency in custom design panels, we also provide a detailed reporting tool.
Heart-Rate Variability Threshold as an Alternative for Spiro-Ergometry Testing: A Validation Study

Abstract Mankowski, RT, Michael, S, Rozenberg, R, Stokla, S, Stam, HJ, and Praet, SFE. Heart-rate variability threshold as an alternative for spiro-ergometry testing: a validation study. J Strength Cond Res 31(2): 474–479, 2017—Although spiro-ergometry is the established “gold standard” for determination of the second ventilatory threshold (VT2), it is a costly and rather time-consuming method. Previous studies suggest that assessing the second anaerobic threshold (AT2) on the basis of heart rate variability (HRV) during exercise may be a more cost-effective and noninvasive manner. However, appropriate validation studies, are still lacking. Eleven healthy, moderately trained subjects underwent 3 incremental exercise tests. Ventilation, oxygen uptake (V[Combining Dot Above]O2), CO2 production (V[Combining Dot Above]CO2), and HRV were measured continuously. Exercise testing was performed in 3 oxygen (FiO2) conditions of inspired air (14, 21, and 35% of oxygen). Participants and assessors were blinded to the FiO2 conditions. Two research teams assessed VT2s and HRVT2s independently from each other. Mean workloads corresponding to VT2 and HRVT2 in hypoxia were, respectively, 19 ± 17% (p = 0.01) and 15 ± 15% (p = 0.1) lower in comparison with hyperoxic conditions. Bland-Altman analysis showed low estimation bias (2.2%) and acceptably precise 95% limits of agreement for workload −15.7% to 20.1% for all FiO2 conditions. Bias was the lowest under normoxic conditions (1.1%) in comparison with hypoxia (3.7%) and hyperoxia (4.7%). Heart rate variability–based AT2 assessment had a most acceptable agreement with VT2 under normoxic conditions. This simple HRVT2 assessment may have potential applications for exercise monitoring in commercial fitness settings.
Systematic Nonlinear Planning

This paper presents a simple, sound, complete, and systematic algorithm for domain independent STRIPS planning. Simplicity is achieved by starting with a ground procedure and then applying a general, and independently verifiable, lifting transformation. Previous planners have been designed directly as lifted procedures. Our ground procedure is a ground version of Tate's NONLIN procedure. In Tate's procedure one is not required to determine whether a prerequisite of a step in an unfinished plan is guaranteed to hold in all linearizations. This allows Tate's procedure to avoid the use of Chapman's modal truth criterion. Systematicity is the property that the same plan, or partial plan, is never examined more than once. Systematicity is achieved through a simple modification of Tate's procedure.
Tantalum and Tantalum Compounds

The article contains sections titled: 1. Introduction 2. Properties 2.1. Physical Properties 2.2. Chemical Properties 3. Occurrence 4. Extraction 4.1. Extraction and Processing of Ore Concentrates 4.2. Obtaining Ta - Nb Concentrates from Tin Slags 4.3. Processing Tantalum Scrap 5. Metallic Tantalum 5.1. Production 5.2. Semifinished Products 5.3. Tantalum Powder for Capacitors 5.4. Other Uses 6. Tantalum Alloys 7. Tantalum Compounds 8. Analysis 9. Economic Aspects 10. Toxicology
A Preliminary Evaluation of Limb Salvage Surgery for Osteosarcoma around Knee Joint

Objective To evaluate the effectiveness and drawbacks of diversified procedures of limb salvage surgery (LSS), providing a reference of rational surgical criterion of LSS. Methods Fifty eight patients with stage IIB extremity osteosarcoma around knee joint area between 1992 and 2002 were studied retrospectively. Among them, 43 patients were treated by LSS followed by reconstruction. Reconstruction approaches included re-implantation of irradiation-devitalized tumor bone (n = 12), autoclaving-devitalized tumor bone (n = 8), prosthetic replacement (n = 11), allograft transplantation (n = 8) and vascularized fibula autograft implantation (n = 4). Amputations were performed in 15 patients. Patients were followed up for 6–16 years. Results There were no significant difference between LSS and amputation groups regarding disease free survival and local recurrence rates. The actuarial 5-year continuous disease free survival and local recurrence rate were 30.0% and 25.0% in patients of devitalized LSS group, whereas those were 56.5% and 8.7% in patients of non-devitalized reconstruction group. The complication rate was significantly higher in LSS group compared to amputation group (P = 0.003). Conclusion LSS with non-devitalized procedures is the optimal treatment for osteosarcoma around knee joint area. Prosthesis implantation is the preferred option for bone reconstruction following LSS. Prevention and treatment of post-operative complications should be paid more attention to get good long-term outcomes of surgery.
Multistrategy learner using Complimentary Algorithms

We present a hybrid learning algorithm called Learning Algorithm using SEarch Rings (LASER). LASER combines Naive Bayes and 1-Nearest neighbor learners in a multistrategic way. The Naive Bayes and the Nearest Neighbor algorithms seem to compliment each other in their search technique and their bias and present a interesting category of learning algorithms called complimentary learners. LASER uses kernel density estimates for evaluating locality information and determining which component algorithm to use. Empirical analysis shows that LASER was superior to the component algorithms. The main contribution of LASER was its robustness in handling class imbalance and feature irrelevance.
Body size and physical activity in relation to incidence of chronic obstructive pulmonary disease

Background: Limited evidence suggests that adiposity and lack of physical activity may increase the risk of chronic obstructive pulmonary disease (COPD). We investigated the relation of body size and physical activity with incidence of COPD. Methods: We obtained data on anthropometric measurements and physical activity from 113 279 participants in the National Institutes of Health–AARP Diet and Health Study who reported no diagnosis of COPD at baseline (1995–1996). We estimated associations between these measurements and subsequent diagnosis of COPD between 1996 and 2006, with extensive adjustment for smoking and other potentially confounding variables. Results: Participants reported 3648 new COPD diagnoses during follow-up. The incidence of COPD was higher in both severely obese (body mass index [BMI]D≥ 35) and underweight (BMID< 18.5) participants, but after adjustment for waist circumference, only underweight remained positively associated with COPD (relative risk [RR]D1.56, 95% confidence interval [CI]D1.15–2.11). Larger waist circumference (highest v. normal categories, adjusted RRD1.72, 95% CID1.37–2.16) and higher waist–hip ratio (highest v. normal categories, adjusted RRD1.46, 95% CID1.23–1.73) were also positively associated with COPD. In contrast, hip circumference (highest v. normal categories, adjusted RR 0.78, 95% CI 0.62–0.98) and physical activity (≥ 5 v. 0 times/wk, adjusted RRD0.71, 95% CID0.63–0.79) were inversely associated with COPD. Interpretation: Obesity, in particular abdominal adiposity, was associated with an increased risk of COPD, and increased hip circumference and physical activity were associated with a decreased risk of COPD. These findings suggest that following guidelines for a healthy body weight, body shape and physical activity decrease the risk of COPD.
Optimal Cover of Points by Disks in a Simple Polygon

Let P be a simple polygon, and let Q be a set of points in P. We present an almost-linear time algorithm for computing a minimum cover of Q by disks that are contained in P. We generalize the algorithm above, so that it can compute a minimum cover of Q by homothets of any fixed compact convex set O of constant description complexity that are contained in P. This improves previous results of Katz and Morgenstern [20]. We also consider the disk-cover problem when Q is contained in a (not too wide) annulus, and present a nearly linear algorithm for this case too.
Genetic relationship of two highly studied Synechococcus strains designated Anacystis nidulans

The cyanobacteria Synechococcus sp. strain PCC 7942 and Synechococcus sp. strain PCC 6301 are very closely related and both have been designated by the binomial Anacystis nidulans. The only established difference between the two strains is the superior transformation properties of strain PCC 7942. Significant homology between the rRNA genes of these strains was demonstrated by the ability of an rRNA operon from strain PCC 6301, interrupted by a spectinomycin and streptomycin resistance marker, to transform strain PCC 7942 by recombining with and replacing an endogenous rRNA operon. Restriction fragment length polymorphism data indicated that the chromosomes of the two strains were conserved around the three psbA loci, the two rRNA operons, and the psbDI locus. However, multiple polymorphisms were detected downstream of the psbDII locus, identifying a DNA rearrangement such as an inversion, insertion, or deletion within the chromosome. Analysis of genome structure by pulsed-field gel electrophoresis of large NotI restriction fragments showed only two bands that were visibly shifted between the chromosomes of the two strains. These data support their very close genetic relationship and the feasibility of studying genes derived from strain PCC 6301 in the highly transformable PCC 7942 strain.
Non-iterative data-driven controller tuning using the correlation approach

Data-driven controller tuning for the model-reference control problem is investigated. A new controller-tuning scheme for linear time-invariant single-input single-output systems is proposed. The method, which is based on the correlation approach, uses a single set of input/output data taken in open-loop or closed-loop operation. A specific choice of instrumental variables makes the correlation criterion an approximation of the model-reference control criterion. The correlation criterion and the controller parameters are asymptotically not affected by noise. Although for finite data length the criterion is biased, a bias analysis shows that it generally improves the controller robustness. The effectiveness of the proposed method is illustrated via a simulation example.
Task Structure and Postcompletion Error in the Execution of a Routine Procedure

Objective: To replicate a successful laboratory slip-class error paradigm and, more importantly, to further understand the underlying causes of errors made in that paradigm. Background: Routine procedural errors are facts of everyday life but have received limited controlled empirical study, despite the sometimes severe consequences associated with such errors. This research concerns one such error, postcompletion error (M. D. Byrne & S. Bovair, 1997), which is a lapse that occurs after the main goal of a task has been satisfied. Method: In the two experiments conducted, participants were trained to criterion on a routine procedural task and were then brought back to the lab for a later session or sessions in which performance on task execution was measured. In the second experiment, a variety of motivational manipulations, retraining, and task redesign were compared. Results: Experiment 1 demonstrated a substantial reduction of error rate generated by a simple design change (alteration of when feedback about goal completion occurred). Furthermore, the reduction in error rate came with no penalty in terms of overall speed of performance. Experiment 2 showed that this more appropriate design is superior to motivationally oriented interventions, retraining, and even midtask redesign. As in Experiment 1, Experiment 2 revealed no speed-accuracy tradeoff. Conclusion: These experiments provide evidence that controlled laboratory studies of slip-class errors can be meaningful and highlight the centrality of cognitive factors (particularly goal structure) in such errors. Application: Potential applications include design of interfaces and their related procedures as well as error-mitigation techniques.
Modeling Cloud Architectures as Interactive Systems

The development and maintenance of cloud software is complicated by complex but crucial technological requirements that are tightly coupled with each other and with the softwares actual business functionality. Consequently, the complexity of design, implementation, deployment, and maintenance activities increases. We present an architecture description language that raises the level of technological abstraction by modeling cloud software as interactive systems. We show how its models correspond to an architecture style that particularly meets the requirements of cloud-based cyber-physical systems. The result provides a basis for an architecture-driven model-based methodology for engineering cloud software.
Speech restoration based on deep learning autoencoder with layer-wised pretraining

Neural network can be used to “remember” speech patterns by encoding speech statistical regularity in network parameters. Clean speech can be “recalled” when noisy speech is input to the network. Adding more hidden layers can increase network capacity. But when the hidden layer size increases (deep network), the network is easily to be trapped to a local solution when traditional training strategy is used. Therefore, the performance of using a deep network sometimes is even worse than using a shallow network. In this study, we explore the greedy layer-wised pretraining strategy to train a deep autoencoder (DAE) for speech restoration, and apply the restored speech for noisy robust speech recognition. The DAE is ﬁrst pretrained using quasi-Newton optimization algorithm layer by layer in which each layer is regarded as a shallow autoencoder. And the output of the preceding layer is served as the input to the next layer. The pretrained layers are stacked and “unrolled” to be a DAE. The pretrained parameters are served as initial parameters of the DAE which are used to reﬁne training. The trained DAE is used as a ﬁlter for speech restoration when noisy speech is given. Noisy robust speech recognition experiments were done to examine the performance of the trained deep network. Experimental results show that the DAE trained with pretraining process signiﬁcantly improved the performance of speech restoration from noisy input.
Applications of description logics to improve multimedia information retrieval for efficient educational tools

There is a growing discrepancy between the creation of digital content and its actual employment and usefulness in a learning society. Technologies for recording lectures have become readily available and the sheer number and size of such objects produced grows exponentially. However, in practice most recordings are monolithic entities that cannot be integrated into an active learning process offhand. To overcome this problem, recorded lectures have to be semantically annotated to become full-fledged e-learning objects facilitating automated reasoning over their content. We present a running web-based system - the e-Librarian Service CHESt - that is able to match a user's question given in natural language to a selection of semantically pertinent learning objects based on an adapted best cover algorithm. We show with empirical data that the precision of our e-Librarian Service is much more efficient than traditional keyword-based information retrieval; it yields a correct answer in most of the cases (93% of the queries), and mostly with a high precision, i.e., without supplementary hits. We also describe some ideas to improve the retrieval performance by user feedback.
Some New Mathematical Modelings of Junctions

Most of the structures in Civil Engineering consists in assemblies of deformable bodies, thus it is of interest to dispose of efficient models of junctions between de- formable solids. The classical schemes of Continuum Mechanics lead to boundary value problems involving several parameters, one being essential: the (low) thick- ness of the layer filled by the adhesive. For usual behaviors of the adherents and the adhesive, it is not difficult to prove existence of solutions, but their numerical approximations may be difficult due to the rather low thickness of the adhesive im- plying a too fine mesh. We propose a simplified but accurate mathematical modeling by a rigorous study of the asymptotic behavior of the three-dimensional adhesive when its thickness goes to zero. Depending on the stiffness of the adhesive, the limit model will replace the thin adhesive layer by either a mechanical constraint along the surface the layer shrinks toward or a material surface; the structure of the constitu- tive equations of the constraint or of the material surface keeping the memory of the mechanical behavior of the adhesive. The mathematical techniques used in these studies, carried out for more than 25 years, involve variational convergences and the Trotter theory of convergence of semi-groups of operators. We will present classical results concerning standard elastic or dissipative behaviors of the adhesive and some new ones devoted to microscopic aspects, imperfectly bonded adhesive joints, loaded joints, etc. .
RNA Binding of T-cell Intracellular Antigen-1 (TIA-1) C-terminal RNA Recognition Motif Is Modified by pH Conditions*

Background: T-cell intracellular antigen-1 (TIA-1) is a key DNA/RNA-binding protein in RNA metabolism. Results: Binding of the TIA-1 RRM3 domain (isolated or fused to RRM2) to RNA is affected by pH changes. Conclusion: The pH dependence of the RRM3/RNA interaction may have a significant effect on the overall TIA-1 function. Significance: Unveiling the auxiliary role of RRM3 in RNA recognition sheds light on the TIA-1 function between cell compartments. T-cell intracellular antigen-1 (TIA-1) is a DNA/RNA-binding protein that regulates critical events in cell physiology by the regulation of pre-mRNA splicing and mRNA translation. TIA-1 is composed of three RNA recognition motifs (RRMs) and a glutamine-rich domain and binds to uridine-rich RNA sequences through its C-terminal RRM2 and RRM3 domains. Here, we show that RNA binding mediated by either isolated RRM3 or the RRM23 construct is controlled by slight environmental pH changes due to the protonation/deprotonation of TIA-1 RRM3 histidine residues. The auxiliary role of the C-terminal RRM3 domain in TIA-1 RNA recognition is poorly understood, and this work provides insight into its binding mechanisms.
Method for Estimating Three-Dimensional Knee Rotations Using Two Inertial Measurement Units: Validation with a Coordinate Measurement Machine

Three-dimensional rotations across the human knee serve as important markers of knee health and performance in multiple contexts including human mobility, worker safety and health, athletic performance, and warfighter performance. While knee rotations can be estimated using optical motion capture, that method is largely limited to the laboratory and small capture volumes. These limitations may be overcome by deploying wearable inertial measurement units (IMUs). The objective of this study is to present a new IMU-based method for estimating 3D knee rotations and to benchmark the accuracy of the results using an instrumented mechanical linkage. The method employs data from shank- and thigh-mounted IMUs and a vector constraint for the medial-lateral axis of the knee during periods when the knee joint functions predominantly as a hinge. The method is carefully validated using data from high precision optical encoders in a mechanism that replicates 3D knee rotations spanning (1) pure flexion/extension, (2) pure internal/external rotation, (3) pure abduction/adduction, and (4) combinations of all three rotations. Regardless of the movement type, the IMU-derived estimates of 3D knee rotations replicate the truth data with high confidence (RMS error < 4° and correlation coefficient r≥0.94).
The Evolution of the ICT Start-Up Eco-System in Japan: From Corporate Logic to Venture Logic?

This paper uses the notion of institutional logics to advance our understanding of institutional change in the ICT start-up eco-system in Japan. We chose to study ICT start-ups because the rates of entry, growth, and exit are faster in this sector than in others, making it easier to observe institutional change. Our study, based on data from interviews, closed master classes and document analysis, is presented in three steps. First, we describe the two logics that coexist in the ICT start-up eco-system, namely Corporate Logic and Venture Logic, and practices under each logic in three arenas, namely the capital market, the labor market, and social networks. Second, we identify several factors that enabled the emergence of Venture Logic during the period since the mid-1990s. Third, looking into the future, we discuss the reasons why we predict that the two logics are likely to co-exist in this field, resulting in organizational heterogeneity.