Automatic modeling of the linguistic values for database fuzzy querying

In order to evaluate vague queries, each linguistic term is considered according to its fuzzy model. Usually, the linguistic terms are defined as fuzzy sets, during a classical knowledge acquisition off-line process. But they can also be automatically extracted from the actual content of the database, by an online process. In at least two situations, automatically modeling the linguistic values would be very useful: first, to simplify the knowledge engineer’s task by extracting the definitions from the database content; and second, where mandatory, to dynamically define the linguistic values in complex criteria queries evaluation. Procedures to automatically extract the fuzzy model of the linguistic values from the existing data are presented in this paper

Brownfield management opportunities to reduce the back pressure effects on the gas wells

Gas mature fields are associated with challenges to optimize the hydrocarbon flow from reservoir to the sales point in a cost effective manner due to declining well productivity. Laslau Mare field is a mature gas field in Transylvanian basin (Mures County) developed in 1970s and is producing∼99% methane with low water-gas ratio. As any brown field, the state of depleted reservoir will generate several constraints for gas flow from formation to surface facilities and further to delivery point. During the exploitation has been observed that the operation conditions are facing with unstable pressure in the system due to low demand. Therefore, the back pressure effect will affect the wells in terms of inability to unload the bottomhole accumulated liquids and the reservoir will suffer a higher pressure drawdown. The best fit-for-purpose solution to overcome the above challenges is represented by installation of group compressor. Laslau Mare field has 3 group compressors running and shows positive results, especially when external pressure fluctuates continuously. This paper explain the challenges seen in 2016 in Laslau Mare field with back pressure effects and how the compression overcome them, and also other solutions that should be considered to optimize the well production

Magnetic resonance imaging of vaginal support structure before and after Vecchietti procedure in women with Mayer–Rokitansky–Küster–Hauser syndrome

IntroductionIt is unclear how pelvic floor supporting structures might be affected by the absence of the vagina. It was the aim of this prospective study to analyze the magnetic resonance imaging morphology of pelvic support prior and after a Vecchietti procedure in women suffering Mullerian agenesis (Mayer–Rokitansky–Küster–Hauser syndrome).Material and methods26 women with a diagnosis of Mayer–Rokitansky–Küster–Hauser syndrome associated vaginal agenesis were recruited prospectively prior to the laparoscopic creation of a neovagina according to the Vecchietti procedure. The primary outcome measure was the magnetic resonance imaging morphology of supporting structures. Secondary outcome measures were anatomical and functional vaginal length. Follow up was conducted six months after surgery.ResultsTwenty‐six women were analyzed. Mean age was 19.8 ± 4.4 years (±SD) and mean body mass index was 23.7 ± 4.3 kg/m2 (±SD). All were Caucasian. Supporting structures consistent with cardinal and uterosacral ligaments were visible on magnetic resonance imaging in all cases (100%). There were no levator ani defects. The vaginal apex could be visualized postoperatively in 12 women (46.2%) reaching up to Level I. The vagina was visible in both Level II and III with normal relations to the pelvic walls in all cases. On gynecological examination, vaginal length was 8.8 ± 2.1 cm (mean ± SD) anatomically and 10.2 ± 2.2 cm (mean ± SD) functionally.ConclusionsThe preoperative presence of pelvic support structures into which the vagina is lengthened by the surgery likely explains the uncommon occurrence of vaginal prolapse in women who had the Vecchietti procedure.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144648/1/aogs13350_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144648/2/aogs13350.pd

Impact of the Psychiatric Comorbidities in Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is one of the main causes of death with a significant impact on the quality of life and mental health of the patients as well as on the health system. The social costs of COPD are significant, because this pathology has a negative impact on patients's professional performance and daily activity. The major risk factors for COPD are age and smoking. Extrapulmonary comorbidities are frequently associated with COPD and may have an influence on the symptoms severity, and the frequency of the exacerbations, hospitalizations and mortality. Psychiatric disorders, especially anxiety and depression, have been observed in clinical trials with an increased prevalence of COPD. The relationship between anxiety, depression and COPD is complex. Psychiatric pathology is involved in influencing the pathophysiology of COPD with a proven impact on the patient's prognosis. COPD sleep disorders can aggravate pre-existing psychiatric pathology, the relationship between the two pathologies being bidirectional. The aim of this paper is to review the latest clinical trials on the existing evidence of psychiatric comorbidities impact on the evolution and prognosis of COPD and the therapeutic alternatives for their improvement. The conclusion of the present study is that anxiety and depression should be periodically assessed by a multidisciplinary team in order to provide a complete management (pharmacological, pulmonary rehabilitation and cognitive-behavioral therapy), improving the patient's quality of life and prognosis.</em

Windborne long-distance migration of malaria mosquitoes in the Sahel

Over the past two decades efforts to control malaria have halved the number of cases globally, yet burdens remain high in much of Africa and the elimination of malaria has not been achieved even in areas where extreme reductions have been sustained, such as South Africa1,2. Studies seeking to understand the paradoxical persistence of malaria in areas in which surface water is absent for 3–8 months of the year have suggested that some species of Anopheles mosquito use long-distance migration3. Here we confirm this hypothesis through aerial sampling of mosquitoes at 40–290 m above ground level and provide—to our knowledge—the first evidence of windborne migration of African malaria vectors, and consequently of the pathogens that they transmit. Ten species, including the primary malaria vector Anopheles coluzzii, were identified among 235 anopheline mosquitoes that were captured during 617 nocturnal aerial collections in the Sahel of Mali. Notably, females accounted for more than 80% of all of the mosquitoes that we collected. Of these, 90% had taken a blood meal before their migration, which implies that pathogens are probably transported over long distances by migrating females. The likelihood of capturing Anopheles species increased with altitude (the height of the sampling panel above ground level) and during the wet seasons, but variation between years and localities was minimal. Simulated trajectories of mosquito flights indicated that there would be mean nightly displacements of up to 300 km for 9-h flight durations. Annually, the estimated numbers of mosquitoes at altitude that cross a 100-km line perpendicular to the prevailing wind direction included 81,000 Anopheles gambiae sensu stricto, 6 million A. coluzzii and 44 million Anopheles squamosus. These results provide compelling evidence that millions of malaria vectors that have previously fed on blood frequently migrate over hundreds of kilometres, and thus almost certainly spread malaria over these distances. The successful elimination of malaria may therefore depend on whether the sources of migrant vectors can be identified and controlled

Uncertainty management using bayesian networks in student knowledge diagnosis

In intelligent tutoring systems, student or user modeling implies dealing with imperfect and uncertain knowledge. One of the artificial intelligence techniques used for uncertainty management is that of Bayesian networks. This paradigm is recommended in the situation when exist dependencies between data and qualitative information about these data. In this work we present a student knowledge diagnosis model based on representation with Bayesian networks. The educational system incorporate a multimedia interface for accomplishes the testing tools. The results of testing sessions are represented and interpreted with probability theory in order to ensure an adapted support for the student. The aims of the computer assisted application that contains this diagnose module are to support the student in personalized learning process and errors explanation

Features of Leadership in Cultural Institutions Case Study Arges County Museums

The leadership has become, increasingly, a concept that combines all the tools, necessary to succeed, for an organization members. Studies have shown a direct relationship between leadership and performance of an organization and demonstrated that the efficacious leaders are those who lead people to a better job building a consensus around a common goal. The purpose of this article is to identify the leadership styles from cultural institutions and highlighting how these influence the organizational performance. The research method used consists of content analysis of literature and quantitative research based on questionnaires, applied among the employees of Arges county�s museums

A hybrid approach to dynamic course generation on the WWW

In recent years, hypermedia has been grown in interest in advanced research on teaching and learning. Futhermore, the extension of hypermedia toward intelligent hypermedia comes more than obviously to meet specific requirements of learning, such as the student modeling, diagnosis and guiding the learner in his investigation.In this paper, we present an architecture for a system based on integrating hypermedia system and intelligent knowledge based system. The object formalism is chosen to represent static and predefined knowledge, whereas the rule formalism is chosen for dynamic knowledge and reasoning processes modeling. The knowledge base can be described by three models of expertise: the domain model, the student model and the didactic model (including the communication model). This architecture allows automatic generation of dynamically individualized courses according to the learner's goal, his or her previous knowledge and the learner's success in acquiring knowlede