Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing robust Java programs with exceptions

Exception handling mechanisms are intended to help developers build robust systems. Although an exception handling mechanism provides a basis for structuring source code dealing with unusual situations, little information is available to help guide a developer in the appropriate application of the mechanism. In our experience, this lack of guidance leads to complex exception structures. In this paper, we reflect upon our experiences using the Java exception handling mechanism. Based on these experiences, we discuss two issues we believe underlie the difficulties encountered: exceptions are a global design problem, and exception sources are often difficult to predict in advance. We then describe a design approach, based on work by Litke for Ada programs, which we have used to simplify exception structure in existing Java programs.
Avoiding hypoglycemia: a key to success for glucose-lowering therapy in type 2 diabetes

Type 2 diabetes carries a risk for hypoglycemia, particularly in patients on an intensive glucose control plan as a glucose-lowering strategy, where hypoglycemia may be a limitation for the therapy and also a factor underlying clinical inertia. Glucose-lowering medications that increase circulating insulin in a glucose-independent manner, such as insulin and sulfonylurea therapy, are the most common cause of hypoglycemia. However, other factors such as a delayed or missed meal, physical exercise, or drug or alcohol consumption may also contribute. Specific risk factors for development of hypoglycemia are old age, long duration of diabetes, some concomitant medication, renal dysfunction, hypoglycemia unawareness, and cognitive dysfunction. Hypoglycemia is associated with acute short-term symptoms related to either counterregulation, such as tachycardia and sweating, or to neuroglycopenia, such as irritability, confusion, and in severe cases stupor, coma, and even death. However, there are also long-term consequences of hypoglycemia such as reduced working capacity, weight gain, loss of self-confidence with reduced quality of life, and increased risk for cardiovascular diseases. For both the patients, the health care system, and the society at large, hypoglycemia carries a high cost. Strategies to mitigate the risk of hypoglycemia include awareness of the condition; education of patients, relatives, and health care providers; and selecting appropriate glucose-lowering medication that also judges the risk for hypoglycemia to prevent this complication. This article summarizes the current knowledge of hypoglycemia and its consequences with a special emphasis on its consequences for the choice of glucose-lowering therapy.
Grapheme-to-Phoneme Conversion using Multiple Unbounded Overlapping Chunks

We present in this paper an original extension of two data-driven algorithms for the transcription of a sequence of graphemes into the corresponding sequence of phonemes. In particular, our approach generalizes the algorithm originally proposed by Dedina and Nusbaum (D&N) (1991), which had originally been promoted as a model of the human ability to pronounce unknown words by analogy to familiar lexical items. We will show that DN's algorithm performs comparatively poorly when evaluated on a realistic test set, and that our extension allows us to improve substantially the performance of the analogy-based model. We will also suggest that both algorithms can be reformulated in a much more general framework, which allows us to anticipate other useful extensions. However, considering the inability to define in these models important notions like lexical neighborhood, we conclude that both approaches fail to offer a proper model of the analogical processes involved in reading aloud.
People Portraits and Cartoon Algorithm Study

This paper is to use the positive face to automatically generate a photo realist style, or has the effect of exaggerated cartoons. It includes two aspects: First, face the portrait photos automatically into production; Second, face deformed to generate cartoon effect. AAM model is a statistical model, can be well applied to the facial characteristics of location. In this paper, by improving the traditional AAM ways to overcome its lack of color information processing, design a more effective figure portraits Generation System. Then, take the initiative to shape a model feature extraction and characteristics of the method of combining the human face of the main features of automatic deformation, the cartoon characters generated portrait.
A directional noise suppressor with a specified beamwidth

this paper proposes a directional noise suppressor with a specified constant beamwidth. A directional gain is calculated based on interchannel phase difference and combined with a spectral gain commonly used in single-channelnoise suppressors (NSs). The beamwidth can be specified as passband edges of the directional gain. In order to implement frequency-independent constant beamwidth, frequency-proportionate band-edge phase differences are determined for the passband. Evaluation with signals recorded by a commercial PC demonstrates good agreement between the theoretical and the measured directivity. The signal-to-noise ratio improvement and the PESQ score for the enhanced signal are improved by 24.4 dB and 0.3 over a conventional NS.
Robust treatment of collisions, contact and friction for cloth animation

We present an algorithm to efficiently and robustly process collisions, contact and friction in cloth simulation. It works with any technique for simulating the internal dynamics of the cloth, and allows true modeling of cloth thickness. We also show how our simulation data can be post-processed with a collision-aware subdivision scheme to produce smooth and interference free data for rendering.
Visualizing 3D scenes using non-linear projections and data mining of previous camera movements

We describe techniques for exploring 3D scenes by combining non-linear projections with the interactive data mining of camera navigations from previous explorations. Our approach is motivated by two key observations: First, that there is a wealth of information in prior explorations of a scene that can assist in future presentations of the same scene. Second, current linear perspective camera models produce images that are too limited to adequately capture the complexity of many 3D scenes. The contributions of this paper are two-fold. First, we show how spatial and temporal subdivision schemes can be used to store camera navigation information that is data mined and clustered to be interactively applicable to a number of existing techniques. Second, we show how the movement of a traditional linear perspective camera is closely tied to non-linear projections that combine space and time. As a result, we present a coherent system where the navigation of a conventional camera is data mined to provide both the understandability of linear perspective and the flexibility of non-linear projection of a 3D scene in real-time. Our system's generality is illustrated by three visualization techniques built with a single data mining and projection infrastructure.
Evolutionary Approach for Structural and Paramentric Adaptation of BP-like Multilayer Neural Networks

Paper describes experience with selected methods of structural and parametric adaptation of BP like multilayer neural networks for real time learning and application in Reinforcement strategy. Non-linear function aproximation is tested and evaluated with these approaches with the aim of perspective application in Computer games and building an intelligence for Bots in the virtual reality. TWEANN and NEAT methods are tested and experimental and theoretical study was accomplished on these methods. They are based on evolutionary computation and optimization of neural networks structure and synaptic weights. Application potential for supporting the intelligence of NAO humanoid robots is mentioned in the conclusion of the paper.
Nuclear delivery of NFκB-assisted DNA/polymer complexes: plasmid DNA quantitation by confocal laser scanning microscopy and evidence of nuclear polyplexes by FRET imaging

Quantification of a plasmid DNA (pDNA) and investigation of its polymer-associated state in the nucleus are crucial to evaluate the effectiveness of a gene-delivery system. This study was conducted with p3NF-luc-3NF, a pDNA-bearing optimized κB motif to favour NFκB-driven nuclear import. Here, a quantification of pDNA copies in the nucleus was performed by real-time confocal laser scanning microscopy in HeLa and C2C12 cells transfected with linear polyethylenimine or histidylated polylysine. Förster Resonance Energy Transfer (FRET) from the fluorescein-p3NF-luc-3NF donor to the co-localized rhodamine-polymer acceptor was carried out to investigate whether the pDNA was still condensed with the polymer in the nucleus. Upon 5 h of transfection, the nuclear amount of p3NF-luc3NF was ∼1500 copies in both cell lines whereas that of pTAL-luc, a 3NF-free counterpart pDNA, was less than 250. This quantity of p3NF-luc-3NF dropped dramatically to that of pTAL-luc in the presence of the BAY 11-7085, an inhibitor of NFκB activation. These data strongly support a nuclear import of p3NF-luc3NF mediated by NFκB. Moreover, FRET experiments clearly revealed that most of nuclear pDNA were still condensed with the polymer raising the question of their passage through the nuclear pore complex and their impact on the gene-expression efficiency.
POEM-based facial expression recognition, a new approach

The development of a fully automatic facial expression recognition system is an open problem. Its implications are very important, with applications ranging from machine intelligence and interaction to psychology research. In order to obtain a viable system, it is necessary to get valid parameters to characterize the facial expression in an image or a video sequence. Several different techniques have been implemented, using global-based, local-based and hybrid methods. In our work we developed a new algorithm based on POEM algorithms. We tested the performance using the Cohn-Kanade database and we compared the results with algorithms using geometric features and regular LBP patterns. Additionally, since the parameters have high linear and non-linear dependence they don't have an homogeneous statistic importance as descriptors, so we performed data mining processing. Our results show that POEM-based algorithms have high performance and low cost, even with low resolution images, outperforming most of traditional state of the art works. Preliminary tests also show the viability of using meta classifiers in order to further improve the performance.
Distinct Kinetic Changes in Neurotransmitter Release After SNARE Protein Cleavage

Neurotransmitter release is triggered by calcium ions and depends critically on the correct function of three types of SNARE [soluble N-ethylmaleimide–sensitive factor attachment protein (SNAP) receptor] proteins. With use of the large calyx of Held presynaptic terminal from rats, we found that cleavage of different SNARE proteins by clostridial neurotoxins caused distinct kinetic changes in neurotransmitter release. When elevating calcium ion concentration directly at the presynaptic terminal with the use of caged calcium, cleavage of SNAP-25 by botulinum toxin A (BoNT/A) produced a strong reduction in the calcium sensitivity for release, whereas cleavage of syntaxin using BoNT/C1 and synaptobrevin using tetanus toxin (TeNT) produced an all-or-nothing block without changing the kinetics of remaining vesicles. When stimulating release by calcium influx through channels, a difference between BoNT/C1 and TeNT emerged, which suggests that cleavage of synaptobrevin modifies the coupling between channels and release-competent vesicles.
Beliefs that influence cost-related medication non-adherence among the “haves” and “have nots” with chronic diseases

Background and objective Some patients continue taking their medication as prescribed despite serious financial pressures, while others with the ability to pay forego treatment due to cost concerns. The primary goal of this study was to explore how patients’ beliefs about the necessity of treatment and treatment side effects, influence cost-related non-adherence (CRN). Methods 27,302 participants in the Harris Interactive Chronic Illness Panel completed an internet survey. The current study focused on two subsamples representing: (a) the most economically-vulnerable survey respondents (ie, individuals with household incomes of US$25,000 per year or less and monthly out-of-pocket medication costs of at least US$60, n = 1321); and (b) respondents who were the most likely to have the financial resources to pay for medications (ie, those with incomes of US$125,000 or more and monthly medication costs of less than US$60.00, n = 1195). Multivariate models were constructed for each group to determine the independent impact on CRN of perceived need for medications and side-effect concerns. Increased risk for CRN associated with depression and asthma diagnoses also was examined. Results Twenty-one percent of economically vulnerable respondents reported continuing to take their medication as prescribed despite serious cost pressures, while 14% of high-income respondents reported CRN despite apparently manageable out-of-pocket costs. Both low perceived need for medications and concerns about side-effects affected CRN risk in low-income and high-income groups. Within groups of both low-income and high-income respondents, depression and asthma significantly increased patients’ odds of reporting CRN. Conclusion Beyond objective financial measures, CRN is influenced by patient beliefs, which can influence the perceived value of prescription drugs. Addressing these beliefs, as well as the unique adherence concerns of patients with depression and asthma, could decrease CRN rates even if cost pressures themselves cannot be reduced.
AN ONTOLOGY BASED APPROACH FOR DISASTER PREDICTION

Natural disasters are those anomalies created by th e nature in the process of the Earth. The harms the y have caused to human society tend to be horrifying. Almo st every country will be more or less affected by natural disasters annually. In consequence, giving a fairly accurate forecast of the disaster that may happen turns into a vital part of disaster prevention. Tra ditional research on disasters is mainly based on c lassi al statistical methods or expertise judgment, which is lack of semantic-driven and intelligent reasoning. I this paper, an ontology based approach for disaster pred iction was put forward. As the explicit specificati on of a conceptualization, ontologies can achieve a certain degree of knowledge sharing and reuse, and improve the system ability of communications, interoperability and reliability. On the basis of analyzing the infl uencing factors and historical evolution of disasters, a do main ontology model of natural disaster in OWL onto logy language was created. The hidden influencing factor s or disaster chain information can be excavated by the reasoner with domain-specific rules. As a result, w e built an ontology-driven disaster prediction and information system. By performing the task of typho on prediction based on our ontology-based system, o ur approach can improve the intelligence level of the disaster in its management and forecast.
A fuzzy logic controller for a rigid disk drive

A fuzzy logic algorithm is applied to a bang-bang controller for a rigid disk drive. The algorithm has the two functions of 'trial seek' and 'correction for uneven force'. The desired time of switching for bang-bang control is estimated using fuzzy logic: a method for correcting for actuator coil resistance due to temperature change is implemented. Experimental results illustrate the effectiveness of the approach. <<ETX>>
Discrete-Event Coordination Design for Distributed Agents

This paper presents new results on the formal design of distributed coordinating agents in a discrete-event framework. In this framework, agents are modeled to be individually equipped with a coordination module, through which they interact and communicate. In terms of existing control-theoretic concepts, we first define the concept of a coordinable language and show that it is the necessary and sufficient existence condition of coordination modules for distributed agents to achieve conformance to a prespecified interagent constraint language. Following, we present a synthesis algorithm to compute near-optimal coordination modules. An example is provided to illustrate the design synthesis using the proposed algorithm. Finally, a discussion with related work distinguishes our coordination design problem from related problems in the literature.
Circulating DNA: a potential marker of sickle cell crisis

Free circulating DNA is present in the plasma of healthy subjects, and is elevated in conditions characterized by increased cell death, such as cancer and physical trauma. Analysis of circulating DNA in plasma could provide a useful biomarker in sickle cell disease (SCD) in view of the increased cell turnover through chronic ongoing haemolysis, recurrent vaso‐occlusion and inflammation. Plasma DNA was determined by real‐time quantitative polymerase chain reaction (PCR) amplification of the β‐globin gene (HBB) in 154 patients with SCD [105 haemoglobin (Hb)SS, 46 HbSC and three HbS/β0 thalassaemia] and 53 ethnically matched controls. Blood samples were obtained from all patients in steady state; 21 of the 154 patients were also sampled during admission to hospital for acute pain. Median concentration of circulating plasma DNA in acute pain was more than 10‐fold that in steady state and in controls – 10070 vs. 841 and 10070 vs. 933 genome equivalents/ml respectively (P < 0·0001, in both cases). During steady state, patients had plasma DNA levels similar to controls. Plasma DNA levels in SCD correlated with C‐reactive protein levels (P < 0·005) and total white cell counts (P < 0·05) in steady state. The study shows that plasma DNA concentration may have potential as a biomarker in sickle cell patients.
The Sustainability of Wealth among Nomads: An Agent-Based Approach

One of the core objectives of social science in general, and of archaeology in particular, is to explain the emergence and development of complex social systems—i.e., social systems with status inequality and government by non-kin-based authority. In this chapter, we implement an empirically calibrated, spatial agent-based model (ABM) as a tool for studying why and how wealth differentials and associated social inequalities are generated and sustained over multiple generations. We also describe the theoretical foundation, formal strategies, and examples of the mathematical and computational approaches needed to develop complex ABMs. Recent research on inequality and the sustainability of wealth among mobile pastoralists (nomads) has challenged older interpretations. Earlier ethnographic and historical research emphasized the egalitarian nature of pastoralism and the inability to sustain wealth due to environmental vulnerability and marginalization within developing nation-states. In the 1990s, basic interpretations of egalitarianism were reevaluated to
Phantom sensations in people with complete spinal cord lesions: A grounded theory perspective

Purpose. Phantom sensations are somatic phenomena arising from denervated parts of the body. There is very little research, and much diagnostic confusion, regarding such experiences in people with spinal cord injuries. In the case of ‘complete’ spinal cord lesions, phantom experiences may challenge, and indeed, contradict, the understanding that both clinicians and patients have of such injuries. This paper seeks to provide a better understanding of such ‘phantom’ sensations in spinal cord injury. Method. We used grounded theory methods to explore ‘phantom’ sensations as experienced by individuals with complete (ASIA A) spinal lesions. Eight people with complete lesions, who were selected through theoretical sampling, participated in a semi-structured interview. Results. Emergent themes included injury context, sensations experienced, the meaning of sensations, body connectivity, attitude and communication about sensations. Conclusions. Our results provide an enhanced understanding of the embodied experience of phantom sensations, and important insights regarding self-construction and rehabilitative processes in people with spinal cord injury who experience such anomalous sensations.
Experimental evaluation of multi-hop routing protocols for wireless sensor networks

Performance of a deployed Wireless Sensor Network (WSN) is greatly influenced by the interference it is subject to during operation. Degradation happens due to interference resulting in packet drops, retransmissions, link instability and inconsistent protocol behavior. These potential sources of interference must be accounted for during the design stage of a WSN in order to achieve acceptable network performance. Based on these observations, we have proposed a multi-hop routing protocol for ZigBee based WSN that takes into account interference caused by WiFi networks in operation in the vicinity and uses multiple channels at different frequencies to increase the network throughput. This paper details an empirical study that compare the network performance of our proposed multi-hop multi-channel routing protocol with other popular multi-hop routing protocols. This study shows that interference caused by WiFi and co-channel contention degrades the network performance of multi-hop routing protocols unless proactive measures are taken to mitigate the adverse effects of these interference.
Molecular docking, structure-activity relationship and biological evaluation of the anticancer drug monastrol as a pteridine reductase inhibitor in a clinical isolate of Leishmania donovani.

OBJECTIVES Using the pteridine reductase (PTR1) enzyme of Leishmania as the target, the objective of our study was to find a drug candidate that can enter the clinical development process after being evaluated for safety and efficacy in animals. METHODS Monastrol (R) and (S) enantiomers were docked using the QUANTUM program into the active site of a Leishmania donovani PTR1 (LdPTR1) homology model. A structure-activity relationship based on a homology model of a recombinant enzyme was substantiated by a recombinant enzyme inhibition assay. We adapted an L. donovani (transfected with green fluorescent protein) intramacrophage amastigote screening assay as a cellular model for leishmaniasis. Furthermore, since the clinicopathological features and immunopathological mechanisms of visceral leishmaniasis (VL) in a hamster model are remarkably similar to those of human disease, systemic infection of hamsters with L. donovani was utilized to collect in vivo data for monastrol. RESULTS Both monastrol (R) and (S) enantiomers fit well in the ligand-binding pocket of LdPTR1. Monastrol exhibits a K(i) value of 0.428 microM in the recombinant enzyme inhibition assay. We confirm monastrol as a potent inhibitor of PTR1 in Leishmania; it inhibits proliferation of amastigotes with an IC(50) (50% inhibitory concentration) of 10 microM in macrophage cultures infected with an L. donovani clinical isolate, with no host cytotoxicity. We also show that in experimental animals, oral administration of a 5 mg/kg dose of monastrol on two alternate days inhibits 50% of parasite growth, giving therapeutic backing to the use of monastrol as a potent antileishmanial in human VL cases. CONCLUSIONS To our knowledge, this is the first report presenting monastrol as a potent oral antileishmanial.