Miracle-dz/UniFAR-FTUs huggingface dataset:
A Systematic Review for Cardiovascular Disease Detection using Machine Learning Methods

The most important part of providing health care is diagnosing diseases. If a disease is diagnosed earlier than usual or anticipated, it may save a person's life. Methods based on machine learning can assist the medical field by providing accurate and immediate disease diagnoses. The difficulty of diagnosing heart disease makes it one of the most hazardous diseases in the world today. In healthcare contexts, ML is a powerful technology that can swiftly and correctly predict outcomes. After a brief explanation of machine learning, we present synopses of the very common methods for HD diagnosis. This study provides a comprehensive overview of heart disease, the risk factors associated with it, and a brief discussion of the numerous techniques employed to automatically detect heart disease. The detailed information on certain machine learning-based methodologies and investigates the methods for heart disease diagnosis that have been mentioned in the literature throughout the previous five years (2018-2023). There is also mention of a comparison chart. However, among the possibilities mentioned, the classification of cardiac disease has recently drawn increasing attention as a useful and significant alternative.
Applications of calixarenes in cancer chemotherapy: facts and perspectives

Research on the therapeutic applications of calixarene derivatives is an emerging area of interest. The anticancer activity of various functionalized calixarenes has been reported by several research groups. Due to their superior geometric shape, calixarenes can accommodate drug molecules by forming inclusion complexes. Controlled release of anticancer drugs by calixarenes might help in targeted chemotherapy. This review summarizes the anticancer potential of the calixarenes and their drug loading properties. The potential use of calixarenes in chemoradiotherapy is also highlighted in brief.
Object state testing for object-oriented programs

Since class objects are the major components in object oriented (OO) programs during run time, testing the behavior of these objects become an important task in testing of object oriented programs to complement other types of testing, such as, structure testing and functional testing. To check the behavior of objects in OO programs, it is essential to check each state and each transition for every object. The paper proposes a new test model, called object state diagram, to capture and represent the dynamic behavior of objects in an OO program. The model is an extension of the existing state models, it supports basic OO features, such as class objects, inheritance, aggregation and overloading. Unlike other models, it is a concurrent, communicating state machine which has the capability of representing the object state hierarchy for a complex class object. Based on this model we address the issues and solutions to object state test strategy, test criteria and test generation.
BIM in Kenyan Construction Industry: Benefits, Challenges, and Adoption Processes in Sustainable Construction Projects

The construction industry converts a wide range of resources into economic, social, and environmental infrastructure. Kenya's construction industry is emerging as a primary engine of economic expansion, accounting for 7% of the country's gross domestic product. Building Information Modeling (BIM) has become a nascent technology and method in the construction sector of Kenya. Globally, the construction sector is transitioning from conventional CAD to BIM. BIM adoption is accelerating globally, fueled by large private and public sector owners seeking to institutionalize its benefits. Consequently, it is important to know the challenges to BIM adoption and the processes of delivering BIM in the construction industry of Kenya. This study aims to examine the benefits of using BIM, determine its barriers, and formulate the processes for enhancing BIM adoption in the delivery of projects in the Nairobi construction industry. The methodology of this study used quantitative methods and the targeted are contractors' firms in Nairobi. Using the collection of 66 valid questionnaires from 125 C1 contractors, several statistical analyses were performed. The study demonstrated the substantial benefits of utilizing BIM in the Nairobi construction industry. However, there was consensus about the challenges of BIM adoption in the Nairobi construction industry faced by contractors. Furthermore, most of the respondents concurred with the suggested processes for enhancing the adoption of BIM in the delivery of sustainable construction projects in Nairobi city. Therefore, the research identified the significant benefits of BIM usage, challenges, and adoption processes in Kenya's sustainable construction practices.
Aflibercept (VEGF Trap) in Inoperable Stage III or Stage IV Melanoma of Cutaneous or Uveal Origin

Purpose: Aflibercept is a soluble decoy VEGF receptor and angiogenesis inhibitor with potent preclinical antitumor activity in melanoma. We conducted a multicenter phase II study in patients with inoperable stage III or IV melanoma and no prior chemotherapy. Experimental Design: A two-stage design was adopted to evaluate 4-month progression-free survival rate (PFSR) and response rate. Aflibercept was given at 4 mg/kg intravenously every 2 weeks. Response was assessed every 8 weeks. First-stage accrual of 21 patients was specified and with an adequate 4-month PFSR accrual continued to a total of 41. Results: Forty-one patients of ages 23 to 84 (median = 57) were enrolled. Thirty-nine had American Joint Committee on Cancer stage IV (5 M1a, 7 M1b, and 27 M1c) and 2 had inoperable stage IIIC (N3). Eastern Cooperative Oncology Group (ECOG) performance status was 0 (27 patients) or 1 (14 patients). Ten patients had primary uveal melanoma, 28 cutaneous, and 3 had unknown primaries. A median of 7 cycles were initiated (range: 1–56). Grade 3 and 4 toxicities included hypertension in 9 patients (22%) and proteinuria in 6 (15%). Among 40 patients evaluable for efficacy (those who initiated aflibercept), 3 (7.5%) had a confirmed partial response and 20 had progression-free survival of 4 months or above. The predicted 1-year survival rate derived from the Korn meta-analysis model is 36% (N = 39), whereas we observed a corresponding 56.4% survival rate at 1 year (95% CI, 43–74, P < 0.005). Median overall survival in this trial is 16.3 months (95% CI, 9.2 to not reached). We observed a significant association between severity of hypertension following aflibercept and survival improvement. Conclusions: Aflibercept showed promising activity in patients with metastatic melanoma of cutaneous or uveal origin. Further evaluation of aflibercept as a single agent and in combination is warranted. Clin Cancer Res; 17(20); 6574–81. ©2011 AACR.
Learning to Rank Using an Ensemble of Lambda-Gradient Models

Abstract We describe the system that won Track 1 of the Yahoo! Learning to Rank Challenge.Keywords: Learning to Rank, Gradient Boosted Trees, Lambda Gradients, Web Search 1. Introduction and Summary The Yahoo! Learning to Rank Challenge, Track 1, was a public competition on a Ma-chine Learning for Information Retrieval task: given a set of queries, and given a set ofretrieved documents for each query, train a system to maximize the Expected ReciprocalRank (Chapelle et al.,2009) on a blind test set, where the training data takes the formof a feature vector x 2R d with label y2Y; Yf0;1;2;3;4g(a more positive numberdenoting higher relevance) for each query/document pair (the original, textual data wasnot made available). The Challenge setup, background information, and results have beenextensively covered elsewhere and we refer toChapelle and Chang(2011) for details. Inthis paper we summarize the work that resulted in the winning system. 1 We limit the workdescribed in this paper to the work done speci cally for the Challenge; the work was doneover a four week period prior to the end of the Challenge.Our approach used a linear combination of twelve ranking models, eight of which werebagged LambdaMART boosted tree models, two of which were LambdaRank neural nets,and two of which were MART models using a logistic regression cost. LambdaRank isa method for learning arbitrary information retrieval measures; it can be applied to anyalgorithm that learns through gradient descent (Burges et al.,2006). LambdaRank is alistwise method, in that the cost depends on the sorted order of the documents. We brieysummarize the ideas here, where the x
On a Particular Foliation Associated with a Polynomial Family of Noninvertible Maps of the Plane

The present work describes a family of polynomial noninvertible maps of the plane shared within two open regions: (i) (denoted by Z0) each point having no real preimage, and (ii) (denoted by Z2) each point having two real preimages. The regions Z0, Z2 are separated by the critical curve LC, locus of points having two coincident preimages. Z2 is made up of two sheets (giving rise to a plane foliation) joining on LC, each being associated with a well-defined inverse of the map. The considered maps family is structurally unstable. For a wide choice of the parameter space it generates a singular foliation in the sense that the region Z2 is separated into two zones, Z'2 and , inside which the two preimages do not have the same qualitative behavior. Moreover, the boundary between Z'2 and is made up of points having only one real preimage at finite distance, the second one being at infinity. This situation gives rise to a nonclassical homoclinic bifurcation. The maps of the family have another important feature: their inverses present a denominator which vanish along a line of the plane. This has a great consequence on a chaotic attractor structure, when it exists. The imbedding of the map into a wider structurally stable family, generating regions Zk (k=1,3 being the number of real preimages), permits to understand the foliation nature when the imbedding parameter cancels leading to the structurally unstable map.
Fuzzy Rough Sets: The Forgotten Step

Traditional rough set theory uses equivalence relations to compute lower and upper approximations of sets. The corresponding equivalence classes either coincide or are disjoint. This behaviour is lost when moving on to a fuzzy T-equivalence relation. However, none of the existing studies on fuzzy rough set theory tries to exploit the fact that an element can belong to some degree to several "soft similarity classes" at the same time. In this paper we show that taking this truly fuzzy characteristic into account may lead to new and interesting definitions of lower and upper approximations. We explore two of them in detail and we investigate under which conditions they differ from the commonly used definitions. Finally we show the possible practical relevance of the newly introduced approximations for query refinement
Multi-context Argumentative Agents

We propose a new approach to designing agents based upon multi context systems and argumentation This approach allows the development of agent architectures which have a formal model in logic and a direct link between that model and its implementation To exemplify our approach we describe a case study of this relationship for a particular class of agent model namely the strong realist Belief Desire Intention model
Development during Adolescence of the Neural Processing of Social Emotion

Abstract In this fMRI study, we investigated the development between adolescence and adulthood of the neural processing of social emotions. Unlike basic emotions (such as disgust and fear), social emotions (such as guilt and embarrassment) require the representation of another's mental states. Nineteen adolescents (10–18 years) and 10 adults (22–32 years) were scanned while thinking about scenarios featuring either social or basic emotions. In both age groups, the anterior rostral medial prefrontal cortex (MPFC) was activated during social versus basic emotion. However, adolescents activated a lateral part of the MPFC for social versus basic emotions, whereas adults did not. Relative to adolescents, adults showed higher activity in the left temporal pole for social versus basic emotions. These results show that, although the MPFC is activated during social emotion in both adults and adolescents, adolescents recruit anterior (MPFC) regions more than do adults, and adults recruit posterior (temporal) regions more than do adolescents.
Neural Reranking Improves Subjective Quality of Machine Translation: NAIST at WAT2015

This year, the Nara Institute of Science and Technology (NAIST)'s submission to the 2015 Workshop on Asian Translation was based on syntax-based statistical machine translation, with the addition of a reranking component using neural attentional machine translation models. Experiments re-confirmed results from previous work stating that neural MT reranking provides a large gain in objective evaluation measures such as BLEU, and also confirmed for the first time that these results also carry over to manual evaluation. We further perform a detailed analysis of reasons for this increase, finding that the main contributions of the neural models lie in improvement of the grammatical correctness of the output, as opposed to improvements in lexical choice of content words.
Time-Series Pattern Based Effective Noise Generation for Privacy Protection on Cloud

Cloud computing is proposed as an open and promising computing paradigm where customers can deploy and utilize IT services in a pay-as-you-go fashion while saving huge capital investment in their own IT infrastructure. Due to the openness and virtualization, various malicious service providers may exist in these cloud environments, and some of them may record service data from a customer and then collectively deduce the customer's private information without permission. Therefore, from the perspective of cloud customers, it is essential to take certain technical actions to protect their privacy at client side. Noise obfuscation is an effective approach in this regard by utilizing noise data. For instance, noise service requests can be generated and injected into real customer service requests so that malicious service providers would not be able to distinguish which requests are real ones if these requests' occurrence probabilities are about the same, and consequently related customer privacy can be protected. Currently, existing representative noise generation strategies have not considered possible fluctuations of occurrence probabilities. In this case, the probability fluctuation could not be concealed by existing noise generation strategies, and it is a serious risk for the customer's privacy. To address this probability fluctuation privacy risk, we systematically develop a novel time-series pattern based noise generation strategy for privacy protection on cloud. First, we analyze this privacy risk and present a novel cluster based algorithm to generate time intervals dynamically. Then, based on these time intervals, we investigate corresponding probability fluctuations and propose a novel time-series pattern based forecasting algorithm. Lastly, based on the forecasting algorithm, our novel noise generation strategy can be presented to withstand the probability fluctuation privacy risk. The simulation evaluation demonstrates that our strategy can significantly improve the effectiveness of such cloud privacy protection to withstand the probability fluctuation privacy risk.
Clinical characteristics of nephropathia epidemica in Sweden: prospective study of 74 cases.

Clinical symptoms and laboratory measures of renal and liver function, coagulation, and inflammatory parameters were prospectively studied in 74 hospitalized patients (14-74 years of age) with serologic evidence of nephropathia epidemica. The most common clinical findings were acute onset of symptoms, fever (greater than or equal to 38 degrees C), thirst, headache, nausea, back pain, vomiting, myalgia, and abdominal pain. Twenty-seven patients (37%) had hemorrhagic manifestations, i.e., epistaxis, melena, hematemesis, petechial bleeding, macroscopic hematuria, or metrorrhagia. Disseminated intravascular coagulation developed in four patients. Fifty-one percent had thrombocytopenia. Proteinuria was recorded for all patients, while hematuria and glucosuria were noted for 85% and 58%, respectively. Serum creatinine levels were elevated in 71 (96%) of the patients. Levels of C-reactive protein or erythrocyte sedimentation rates were elevated in all cases, usually to levels found in serious bacterial diseases. Sixty-six (89%) of the patients were followed for up to 7 months, at which time all had recovered clinically. No patient died or required dialysis. We conclude that nephropathia epidemica in Sweden has a clinical picture similar to that of hemorrhagic fevers in other parts of the world, but with a milder course and a better prognosis.
Characterizing the Aedes aegypti Population in a Vietnamese Village in Preparation for a Wolbachia-Based Mosquito Control Strategy to Eliminate Dengue

Background A life-shortening strain of the obligate intracellular bacteria Wolbachia, called wMelPop, is seen as a promising new tool for the control of Aedes aegypti. However, developing a vector control strategy based on the release of mosquitoes transinfected with wMelPop requires detailed knowledge of the demographics of the target population. Methodology/Principal Findings In Tri Nguyen village (611 households) on Hon Mieu Island in central Vietnam, we conducted nine quantitative entomologic surveys over 14 months to determine if Ae. aegypti populations were spatially and temporally homogenous, and to estimate population size. There was no obvious relationship between mosquito (larval, pupal or adult) abundance and temperature and rainfall, and no area of the village supported consistently high numbers of mosquitoes. In almost all surveys, key premises produced high numbers of Ae. aegypti. However, these premises were not consistent between surveys. For an intervention based on a single release of wMelPop-infected Ae. aegypti, release ratios of infected to uninfected adult mosquitoes of all age classes are estimated to be 1.8–6.7∶1 for gravid females (and similarly aged males) or teneral adults, respectively. We calculated that adult female mosquito abundance in Tri Nguyen village could range from 1.1 to 43.3 individuals of all age classes per house. Thus, an intervention could require the release of 2–78 wMelPop-infected gravid females and similarly aged males per house, or 7–290 infected teneral female and male mosquitoes per house. Conclusions/Significance Given the variability we encountered, this study highlights the importance of multiple entomologic surveys when evaluating the spatial structure of a vector population or estimating population size. If a single release of wMelPop-infected Ae. aegypti were to occur when wild Ae. aegypti abundance was at its maximum, a preintervention control program would be necessary to ensure that there was no net increase in mosquito numbers. However, because of the short-term temporal heterogeneity, the inconsistent spatial structure and the impact of transient key premises that we observed, the feasibility of multiple releases of smaller numbers of mosquitoes also needs to be considered. In either case, fewer wMelPop-infected mosquitoes would then need to be released, which will likely be more acceptable to householders.
[AIDS and transmissible opportunistic diseases in the Brazilian border area].

INTRODUCTION Person-to-person transmission of HIV and other communicable diseases may be associated with human geographic mobility. This article evaluated the incidence of transmissible opportunistic diseases among AIDS cases that had been reported by municipalities in the Brazilian border area. METHODS Brazilian border area municipalities were grouped into three cultural regions; the source data was AIDS cases registered with the Ministry of Health from 1990 to 2003, which were classified according to CDC-adapted, Rio de Janeiro/Caracas and death criteria; detected communicable opportunistic diseases were categorized into groups according to transmission: 1) inhalation agent; 2) contaminated water and/or food ingestion, and 3) interpersonal contact. The descriptive evaluation considered cultural region, years of schooling, sex and age group. RESULTS Different AIDS incidence patterns were observed among groups of opportunistic diseases in each cultural region. The extreme southern region showed the greatest incidence of AIDS; the absolute incidence of female cases was greatest in the category of heterosexual transmission; the number of male cases was greatest among intravenous drug users; transmission was most frequent in the interpersonal contact group, particularly incidences of candidiasis; tuberculoses and pneumonias were most frequent in the inhalation agent transmission group; the contaminated water/food ingestion transmission group showed an unchanged pattern of absolute incidence. CONCLUSIONS The Brazilian border area is a very important and heterogeneous geographic phenomenon; AIDS programs must recognize different cultural geographies.
Coherent Detection and Channel Coding for Bistatic Scatter Radio Sensor Networking

With rapid advances of scatter radio systems, the principle of reflection rather than active transmission employed by backscatter sensor networks, has emerged as a potential key enabler for low-cost, large-scale and dense ubiquitous sensor networks. Despite the presence of three different unknown channel links due to the bistatic setup (i.e., carrier emitter and receiver are dislocated), as well as multiple unknown scatter radio-related parameters, this work offers a novel coherent receiver of frequency-shift keying (FSK) modulation for the bistatic scatter radio channel. Furthermore, with the objective of range maximization, specific short block-length cyclic channel codes are utilized. The proposed approach requires minimum encoding complexity, ideal for resource-constrained, ultra-low power (e.g. microcontroller unit-based), low-bit rate scatter radio tags, adheres to simple low-complexity decoding at the receiver and achieves high-order signal diversity. Analysis is followed by experimental validation with a commodity software-defined radio (SDR) reader and a custom scatter radio tag; tag-to-reader ranges up to 150 meters are demonstrated with as little as 20 milliWatt transmission power, increasing sensing ranges by approximately 10 additional meters, compared to state-of-the-art bistatic scatter radio receivers. With the imminent emergence of backscatter sensor networks, this work serves as a small step forward towards the realization of low-cost, low-power, increased-range, wireless sensing applications.
In situ field measurements of aquatic animal‐fluid interactions using a Self‐Contained Underwater Velocimetry Apparatus (SCUVA)

We describe the development of a Self‐Contained Underwater Velocimetry Apparatus (SCUVA) that enables a single SCUBA diver to make in situ digital particle image velocimetry (DPIV) measurements of animal‐fluid interactions in real time. The device is demonstrated in a study of the dynamics of Aurelia labiata jellyfish swimming in the coastal waters of Long Beach, California. We analyze the DPIV measurements by computing the kinetic energy in the flow field induced by an animal's swimming motions. As a proof‐of‐concept, we compare these results with an existing theoretical model and find that the results are consistent with one another. However, SCUVA provides details regarding the temporal evolution of the energetics during the swimming cycle, unlike the model. These results suggest the usefulness of SCUVA as a method to obtain quantitative field measurements of in situ animal‐fluid interactions.