Miracle-dz/UniFAR-FTUs huggingface dataset:
IFN-γ Production to Leishmania Antigen Supplements the Leishmania Skin Test in Identifying Exposure to L. braziliensis Infection

Background Cutaneous leishmaniasis due to L. braziliensis (CL) is characterized by a positive delayed type hypersensitivity test (DTH) leishmania skin test (LST) and high IFN-γ production to soluble leishmania antigen (SLA). The LST is used for diagnosis of CL and for identification of individuals exposed to leishmania infection but without disease. The main aim of the present study was to identify markers of exposure to L. braziliensis infection. Methodolgy/Principal Findings This cohort study enrolled 308 household contacts (HC) of 76 CL index cases. HC had no active or past history of leishmaniasis. For the present cross-sectional study cytokines and chemokines were determined in supernatants of whole blood culture stimulated with SLA. Of the 308 HC, 36 (11.7%) had a positive LST but in these IFN-γ was only detected in 22 (61.1%). Moreover of the 40 HC with evidence of IFN-γ production only 22 (55%) had a positive LST. A total of 54 (17.5%) of 308 HC had specific immune response to SLA. Only a moderate agreement (Kappa = 0.52; 95% CI: 0.36–0.66) was found between LST and IFN-γ production. Moreover while enhancement of CXCL10 in cultures stimulated with SLA was observed in HC with DTH+ and IFN-γ+ and in patients with IFN-γ+ and DTH−, no enhancement of this chemokine was observed in supernatants of cells of HC with DTH+ and IFN-γ−. Conclusions/Significance This study shows that in addition of LST, the evaluation of antigen specific IFN-γ production should be performed to determine evidence of exposure to leishmania infection. Moreover it suggests that in some HC production of IFN-γ and CXCL10 are performed by cells not involved with DTH reaction.
The successes and failures of a language as a language extension

This paper is an experience report on implementing the Chameleon role model as a language extension to Java. First, we introduce our role model on a conceptual level, then an overview of the shortcomings of Java. The shortcomings are interesting in that they shed light on the degree of control needed in order to reuse the language to be extended. In the contemplation parts of the paper, we advocate research that tries to abstract concepts to the extend possible, as seen with the pattern concept in Beta. And we advocate language design that permits recursive use of its concept, such as in our role model, where roles can be roles for objects as well as roles. Finally we identify, that language implementations are about two things. 1) The ability to elegantly express the semantics of the language—be it as a set of transformations of an existing language or a set of assembly instructions. And 2) to provide access to a large collection of common functionality, exemplified in this paper by the Java API, in order for the language to be used in real-life scenarios.
A Hardware-in-the-Loop test platform for the performance assessment of a PMU-based Real-Time State Estimator for Active Distribution Networks

The paper describes the development of a Hardware-in-the-Loop (HIL) test platform for the performance assessment of a PMU-based sub-second linear Real-Time State Estimator (RTSE) for Active Distribution Networks (ADNs). The estimator relies on the availability of data coming from Phasor Measurement Units (PMUs) and can be applied to both balanced and unbalanced ADNs. The paper first illustrates the architecture of the experimental HIL setup that has been fully designed by the Authors. It consists of a Real-Time Simulator (RTS) that models the electrical network model as well as the measurement infrastructure composed by virtual PMUs. These virtual devices stream their data to a real Phasor Data Concentrator (PDC) suitably coupled with a Discrete Kalman Filter State Estimator (DKF-SE). By using this experimental setup, the paper discusses the performance assessment of the whole process in terms of estimation accuracy and time latencies. In the RTS, a real ADN located in the Netherlands has been modeled together with the associated PMUs.
eKTR : an Efficient Key Management Scheme in Wireless Data Broadcast Services

Wireless broadcast is an effective approach to disseminate data to a number of users. To provide secure access to the broadcast data, key-based encryption is used to ensure that only users who own the valid keys can decrypt the data. Regarding various subscriptions, an efficient key management to distribute and change keys is in great demand in the broadcast system. In this paper, we propose an efficient key management scheme, eKTR, to address this issue. eKTR lets multiple programs share a single key tree so that the users subscribing these programs can hold less keys. In eKTR, we also propose an approach to further reduce rekey cost by identifying the minimum set of keys that must be changed to ensure broadcast security. Our simulations show that eKTR can save about 45% of communication overhead in the broadcast channel and about 50% of decryption cost for each user, compared with the traditional logical key hierarchy based approach.
HMS: History-Based Multi-Keywords Search in Unstructured Peer-to-Peer Systems

Peer-to-peer approaches bring one perfect alternative for the Web content search. However, how to search and retrieve the data based on the content query is still an open problem for peer-to-peer systems. In this paper we propose Historybased Multi-keywords Search(HMS) in unstructured peer-to-peer systems, which only requires each peer to maintain partial query information of its neighbors, and exploit these information to autonomously find, for each query, how many neighbors and which neighbors are likely to answer. The simulations prove that HMS can limit the traffic of query messages while keeping the high quality of query results.
Chapter 11 High Assurance BPEL Process Models

An increasing number of software applications and business processes are relying upon the use of web services to achieve their requirements. This is due in part to the use of standardized composition languages like the Business Process Execution Language (BPEL). BPEL allows the process designer to compose a procedural workflow from an arbitrary number of available web services and sup- plemental "programming-like" activities (e.g., assigning values to variables). Such composition languages naturally bring concerns of reliability, consistency, and du- rability, let alone safety and security. Thus, there is a need for formal specification and analysis of BPEL compositions for high assurance satisfaction. We propose the use of Unified Modeling Language (UML) sequence diagrams as a means for analysis of BPEL process consistency and demonstrate our technique with two ex- amples.
Hypothalamic Obesity after Craniopharyngioma: Mechanisms, Diagnosis, and Treatment

Obesity is a common complication after craniopharyngioma therapy, occurring in up to 75% of survivors. Its weight gain is unlike that of normal obesity, in that it occurs even with caloric restriction, and attempts at lifestyle modification are useless to prevent or treat the obesity. The pathogenesis of this condition involves the inability to transduce afferent hormonal signals of adiposity, in effect mimicking a state of CNS starvation. Efferent sympathetic activity drops, resulting in malaise and reduced energy expenditure, and vagal activity increases, resulting in increased insulin secretion and adipogenesis. Lifestyle intervention is essentially useless in this syndrome, termed “hypothalamic obesity. ” Pharmacologic treatment is also difficult, consisting of adrenergics to mimic sympathetic activity, or suppression of insulin secretion with octreotide, or both. Recently, bariatric surgery (Roux-en-Y gastric bypass, laparoscopic gastric banding, truncal vagotomy) have also been attempted with variable results. Early and intensive management is required to mitigate the obesity and its negative consequences.
DPClass: An Effective but Concise Discriminative Patterns-Based Classification Framework

Pattern-based classification was originally proposed to improve the accuracy using selected frequent patterns, where many efforts were paid to prune a huge number of non-discriminative frequent patterns. On the other hand, tree-based models have shown strong abilities on many classification tasks since they can easily build high-order interactions between different features and also handle both numerical and categorical features as well as high dimensional features. By taking the advantage of both modeling methodologies, we propose a natural and effective way to resolve pattern-based classification by adopting discriminative patterns which are the prefix paths from root to nodes in tree-based models (e.g., random forest). Moreover, we further compress the number of discriminative patterns by selecting the most effective pattern combinations that fit into a generalized linear model. As a result, our discriminative pattern-based classification framework (DPClass) could perform as good as previous state-of-the-art algorithms, provide great interpretability by utilizing only very limited number of discriminative patterns, and predict new data extremely fast. More specifically, in our experiments, DPClass could gain even better accuracy by only using top-20 discriminative patterns. The framework so generated is very concise and highly explanatory to human experts.
Representing Functional Logic Computations ?

The execution of declarative programs is largely independent of concrete execution strategies. For instance, functional logic languages support various strategies to execute programs, e.g., sequential, parallel, concurrent, fair, depth-first etc. This freedom causes difficulties for tools intended to visualize, trace, or debug functional logic computations. To improve this situation, we describe structures for representing a functional logic computation independently of its concrete execution strategy. Our representation serves as an interface to connect different implementations of functional logic languages, such as PAKCS, KiCS, MCC, FLVM, or TOY, to current and future tools, such as tracers or debuggers, for visualizing and understanding computations.
Who is Responsible for the Child’s Moral Character Education?

This paper tried to answer the question: ‘Who gives the child's moral character education, is it a family responsibility, a collective responsibility or the sole responsibility of a certain institution? After the review of some theories of moral character development and or education, an effort was executed to investigate the various institutions that interact with the child as regards his moral character education. A conclusion was drawn that the moral character education of the child is not the sole responsibility of just a certain institution; rather, different social institutions must cooperate and interact effectively in order to provide the child a meaningful moral character education. Several suggestions were made on how these institutions should interact in order to provide the child moral character education.
Fault Diagnosis of Dynamic Systems Reusing Cases

This paper discuss about fault diagnosis (FD) techniques for dynamic systems. Case Based Reasoning (knowledge-based technique) has been applied in the Electrical Systems domain in order to diagnose the origin of voltage faults. In other hand, residual generation (analytical model-based technique) was accomplished using Dynamic Time Warping and a laboratory plant has been used to test this approach.
POCS-Based Annotation Method Using Kernel PCA for Semantic Image Retrieval

A projection onto convex sets (POCS)-based annotation method for semantic image retrieval is presented in this paper. Utilizing database images previously annotated by keywords, the proposed method estimates unknown semantic features of a query image from its known visual features based on a POCS algorithm, which includes two novel approaches. First, the proposed method semantically assigns database images to some clusters and introduces a nonlinear eigenspace of visual and semantic features in each cluster into the constraint of the POCS algorithm. This approach accurately provides semantic features for each cluster by using its visual features in the least squares sense. Furthermore, the proposed method monitors the error converged by the POCS algorithm in order to select the optimal cluster including the query image. By introducing the above two approaches into the POCS algorithm, the unknown semantic features of the query image are successfully estimated from its known visual features. Consequently, similar images can be easily retrieved from the database based on the obtained semantic features. Experimental results verify the effectiveness of the proposed method for semantic image retrieval.
Structural models for software reliability prediction

Many previous software reliability prediction models by this author and others have concentrated on the bulk (macro) aspects of the program. This paper describes a newly developed micro model which is based on program structure. It is assumed that the program has been written in structured or modular form so that decomposition in to its constituent parts is simple. Further, we assume that via analysis of the program the decomposition can be related to several paths or other functional structures within the program. The model is constructed based upon the frequencies with which each of the j paths are run, (fj), the running time of each path, (tj), and the probability of error along each path, (qj). Several methods of calculating or measuring the fj, tj, and qj parameters are suggested. In fact it is possible to use one technique (historical data) to produce crude estimates at the start of the design, and refine the estimates with more accurate values as the design progresses. The paper concludes with the application of the model to a particular example: calculation of the roots of a quadratic equation, and a discussion of proposed experiments for validating the model.
Evidence for paralytic shellfish poisons in the freshwater cyanobacterium Lyngbya wollei (Farlow ex Gomont) comb. nov

Lyngbya wollei (Farlow ex Gomont) comb. nov., a perennial mat-forming filamentous cyanobacterium prevalent in lakes and reservoirs of the southeastern United States, was found to produce a potent, acutely lethal neurotoxin when tested in the mouse bioassay. Signs of poisoning were similar to those of paralytic shellfish poisoning. As part of the Tennessee Valley Authority master plan for Guntersville Reservoir, the mat-forming filamentous cyanobacterium L. wollei, a species that had recently invaded from other areas of the southern United States, was studied to determine if it could produce any of the known cyanotoxins. Of the 91 field samples collected at 10 locations at Guntersville Reservoir, Ala. , on the Tennessee River, over a 3-year period, 72.5% were toxic. The minimum 100% lethal doses of the toxic samples ranged from 150 to 1,500 mg kg of lyophilized L. wollei cells-1, with the majority of samples being toxic at 500 mg kg-1. Samples bioassayed for paralytic shellfish toxins by the Association of Official Analytical Chemists method exhibited saxitoxin equivalents ranging from 0 to 58 micrograms g (dry weight)-1. Characteristics of the neurotoxic compound(s), such as the lack of adsorption by C18 solid-phase extraction columns, the short retention times on C18 high-performance liquid chromatography (HPLC) columns, the interaction of the neurotoxins with saxiphilin (a soluble saxitoxin-binding protein), and external blockage of voltage-sensitive sodium channels, led to our discovery that this neurotoxin(s) is related to the saxitoxins, the compounds responsible for paralytic shellfish poisonings. The major saxitoxin compounds thus far identified by comparison of HPLC fluorescence retention times are decarbamoyl gonyautoxins 2 and 3. There was no evidence of paralytic shellfish poison C toxins being produced by L. wollei. Fifty field samples were placed in unialgal culture and grown under defined culture conditions. Toxicity and signs of poisoning for these laboratory-grown strains of L. wollei were similar to those of the field collection samples.
Intermittent White-Collar Offenders: Who They Are and How to Stop Them

2 Acknowledgements . 3 Introduction . 5 Defining White-Collar Crime . 6 Examining the Offender . 9 Personality and Gender Characteristics . 13 Crime Theories . 16 WCC: Post Offense . 20 Business Applications . 22 Education . 22 Pre-Employment Personality Tests . 25 Limiting WCC Opportunities . 27 Regulation & Punishment . 31 Conclusion . 35 Bibliography . 36
Lighting Analysis and Texture Modification of 3D Human Face Scans

The 3D scanning of human faces is an important tool to acquire accurate shape and texture information of heads and faces for both animation and recognition purposes. One of the most popular scanning tools is Cyberware head and face 3D colour scanner. Currently, 3D face databases scanned using the Cyberware head and face 3D colour scanner databases are publicly available and have been used in many face recognition system as the training data, one of which is USF human ID 3-D database. The mechanism of facial texture capturing, however, remains unclear due to the special settings of the light sources during scanning. The direct application of the acquired texture intensity as the albedo of the face surfaces leads to suboptimal modelling results. This paper analyses the lighting configuration of the scanner and proposes an appropriate reflectance model to describe the reflecting mechanism when scanning. The texture modifications can be carried on in the existing scanning results without any further scans. Experiment results show that the proposed reflectance model can better approximate the reflecting situation of scanning so that the acquired textures can be directly used as diffuse reflectance coefficients and achieve better rendering results. Key words: 3D face model, 3D scanner, facial textures, lighting condition, reflection model.
The cross-layer cognitive routing with load balance in heterogeneous wireless mesh networks

The wireless mesh network (WMN) has recently emerged as a promising technology for distributed wireless networking. In multi-radio multi-channel heterogeneous WMNs, load balancing can avoid congestion thus to improve the overall performance. A cross-layer cognitive routing protocol with load balance which using RACIM, a new metric, to choose qualified routing paths is presented. RACIM can evaluate the link quality and load status by incorporating the cross-layer cognitive information, such as channel bandwidth, the rate of transmission bit error (BER) and the frequency of channel etc. In order to share cognitive information between layers, we add a new type of ICMP message. The simulation results show the effectiveness of the proposed protocol.
Large Scale Gigabit Emulated Testbed for Grid Transport Evaluation

Evaluating the performance of Grid applications running on high performance platforms interconnected by high speed and long distance net- works with new transport services and protocols is highly required. This paper presents the eWAN inte- grated environment enabling large scale grid emula- tion at gigabit speed. It discusses features provided to control key characteristics (topology, round trip time, packet size, drop rate, link capacity) of an evaluation scenario. A method to increase the accuracy of rate control under various delay configuration is proposed and some experimental results are detailled.
An investigation of broad coverage automatic pronoun resolution for information retrieval

Term weighting methods have been shown to give significant increases in information retrieval performance. The presence of pronomial references in documents reduces the term frequencies of associated words with a consequent effect on term weights and information retrieval behaviour. This investigation explores the impact on information retrieval performance of broad coverage automatic pronoun resolution. Results indicate that this approach has potential to improve both precision at fixed cutoff levels and average precision.
An Abrupt Centennial-Scale Drought Event and Mid-Holocene Climate Change Patterns in Monsoon Marginal Zones of East Asia

The mid-latitudes of East Asia are characterized by the interaction between the Asian summer monsoon and the westerly winds. Understanding long-term climate change in the marginal regions of the Asian monsoon is critical for understanding the millennial-scale interactions between the Asian monsoon and the westerly winds. Abrupt climate events are always associated with changes in large-scale circulation patterns; therefore, investigations into abrupt climate changes provide clues for responses of circulation patterns to extreme climate events. In this paper, we examined the time scale and mid-Holocene climatic background of an abrupt dry mid-Holocene event in the Shiyang River drainage basin in the northwest margin of the Asian monsoon. Mid-Holocene lacustrine records were collected from the middle reaches and the terminal lake of the basin. Using radiocarbon and OSL ages, a centennial-scale drought event, which is characterized by a sand layer in lacustrine sediments both from the middle and lower reaches of the basin, was absolutely dated between 8.0–7.0 cal kyr BP. Grain size data suggest an abrupt decline in lake level and a dry environment in the middle reaches of the basin during the dry interval. Previous studies have shown mid-Holocene drought events in other places of monsoon marginal zones; however, their chronologies are not strong enough to study the mechanism. According to the absolutely dated records, we proposed a new hypothesis that the mid-Holocene dry interval can be related to the weakening Asian summer monsoon and the relatively arid environment in arid Central Asia. Furthermore, abrupt dry climatic events are directly linked to the basin-wide effective moisture change in semi-arid and arid regions. Effective moisture is affected by basin-wide precipitation, evapotranspiration, lake surface evaporation and other geographical settings. As a result, the time scales of the dry interval could vary according to locations due to different geographical features.
Co-regularized deep representations for video summarization

Compact keyframe-based video summaries are a popular way of generating viewership on video sharing platforms. Yet, creating relevant and compelling summaries for arbitrarily long videos with a small number of keyframes is a challenging task. We propose a comprehensive keyframe-based summarization framework combining deep convolutional neural networks and restricted Boltzmann machines. An original co-regularization scheme is used to discover meaningful subject-scene associations. The resulting multimodal representations are then used to select highly-relevant keyframes. A comprehensive user study is conducted comparing our proposed method to a variety of schemes, including the summarization currently in use by one of the most popular video sharing websites. The results show that our method consistently outperforms the baseline schemes for any given amount of keyframes both in terms of attractiveness and in-formativeness. The lead is even more significant for smaller summaries.