Miracle-dz/UniFAR-FTUs huggingface dataset:
Eutrophication Regulation and Control by Combination of Microorganism Agents and Aquatic Plants for Urban Ecological Village Landscape Water

As most of water bodies in urban ecological village landscape are closed or sluggish, in addition to point source and non-point source pollution, they are easy to be eutrophicated. Life and environment nearby will be influenced. In this paper, the combination of microorganism agents and aquatic plants were conducted to treat Xinhe East Canal water body. As a result, after 40 days of running, the removal rates of CODCr, NH3-N, TN and TP were around 58.34%, 92.84%, 89.10% and 86.44%, respectively. And the concentration of Chlorophyll a decreased to less than 3 mg/m3. The main parameters can meet the demands of the standard of fifth type water body according to the Chinese environmental quality standards for surface water.
Smoking and Overweight: Negative Prognostic Factors in Stage III Epithelial Ovarian Cancer

Objective: Smoking and overweight are associated with poorer prognosis in several cancer types. The prognostic effect of smoking and body mass index (BMI) on ovarian cancer is unknown. Methods: Ovarian cancer cases were from the Danish MALOVA (MALignant OVArian cancer) study. Information on smoking status and BMI was obtained from a personal interview conducted closely after primary surgery. Cox regression models were used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (95% CI) for ovarian cancer–specific death in relation to smoking variables and BMI. Results: A total of 295 women with stage III epithelial ovarian cancer were identified and followed to death or for a median of 7.3 years (range, 5.4-9.5 years). Median survival time for normal-weight never smokers was 2.8 years (95% CI, 2.3-3.2) compared with 1.2 years (95% CI, 0.8-2.3) for overweight current smokers. Current smokers had a significantly increased risk of ovarian cancer death compared with never smokers in multivariate Cox analysis (HR, 1.65; 95% CI, 1.22-2.24). The negative effect of smoking diminished with increasing time since a former smoker had stopped smoking (HR, 0.89; 95% CI, 0.80-0.98 per 5 years since stop of smoking). Overweight women also had an increased risk of ovarian cancer death (HR, 1.83; 95% CI, 1.38-2.42) compared with normal-weight women. Conclusion: Smoking at the time of diagnosis and premorbid overweight were negative prognostic factors for ovarian cancer–specific survival. The negative effect of smoking decreased with increasing time since stop of smoking. (Cancer Epidemiol Biomarkers Prev 2006;15(4):798–803)
Behavior of Small, Asymptomatic, Nonfunctioning Pancreatic Neuroendocrine Tumors (NF-PNETs)

AbstractSmall nonfunctioning pancreatic neuroendocrine tumors (NF-PNETs) usually exhibit minimal or no growth over many years. However, there is a controversy regarding the optimal management of incidentally discovered, small NF-PNETs. This study aimed to gain insights into tumor behavior and potential strategies for clinical management.We retrospectively reviewed a total of 202 patients with a suspected PNET (size 2 cm or smaller) at Samsung Medical Center from January 1, 1995 to April 30, 2012. Among these patients, 72 patients were excluded and 145 patients were enrolled in our study. Patients were included if the size of the tumor was ⩽2 cm without familial syndrome, radiographic evidence of local invasion or metastases.Among the 145 patients, 76 patients (52.4%) had pathologically confirmed PNETs. Eleven (14.5%) and 3 (3.9%) of these 76 patients were diagnosed with NET G2 and G3, respectively. PNETs measuring 1.5 cm or more in size had a higher probability of being classified as NET G2 or G3 compared with PNETs measuring <1.5 cm (P = 0.03). Older age (≥55 years) and a meaningful tumor growth (≥20% or ≥5 mm) were significantly associated with NET G2 or G3 (P < 0.05). Older age (≥55 years), larger tumor size (≥1.5 cm), and a meaningful tumor growth (≥20% or ≥5 mm) were associated with NET G2 or G3. Intensive follow-up could be an acceptable approach in small (especially <1.5 cm), asymptomatic, NF-PNETs.
Fine Structure Constant Defines Visual Transparency of Graphene

There are few phenomena in condensed matter physics that are defined only by the fundamental constants and do not depend on material parameters. Examples are the resistivity quantum, h/e2 (h is Planck's constant and e the electron charge), that appears in a variety of transport experiments and the magnetic flux quantum, h/e, playing an important role in the physics of superconductivity. By and large, sophisticated facilities and special measurement conditions are required to observe any of these phenomena. We show that the opacity of suspended graphene is defined solely by the fine structure constant, a = e2/hc � 1/137 (where c is the speed of light), the parameter that describes coupling between light and relativistic electrons and that is traditionally associated with quantum electrodynamics rather than materials science. Despite being only one atom thick, graphene is found to absorb a significant (pa = 2.3%) fraction of incident white light, a consequence of graphene's unique electronic structure.
Contribution Association of Summer Temperatures With Hospital Admissions for Renal Diseases in New York State : A Case-Crossover Study

This study assessed the association between high temperatures and increased odds of hospitalization for renal diseases that, to date, has been examined in only a small number of studies. A case-crossover design was used to study 147,885 hospital admissions with renal diagnoses during July and August, 1991–2004, in New York State. Regional temperature, humidity, and barometric pressure data from automated monitors were used as exposure indicators. By use of time-stratified referent selection and conditional logistic regression analysis, an overall 9% increase in odds of hospitalization for acute renal failure per 5 F (2.78 C) was found for mean temperature at a 1-day lag (odds ratio1⁄4 1.09, 95% confidence interval: 1.07, 1.12). The results suggest increased susceptibility to hospitalization for acute renal failure for blacks, Hispanics, people aged 25–44 years, and those in the lowest income quartile. The odds varied geographically with the largest associations found in the more urban regions. Increased odds of hospitalization were also found for urinary tract infections, renal calculi, lower urinary calculi, and other lower urinary tract disorders. The findings can help to identify vulnerable subpopulations and to inform decisions and policies regarding adaptation strategies and heat-warning systems.
Looking Through the Patients’ Eyes

Objective: Patient satisfaction is a personal evaluation of health-care services that is often used as an indicator of quality of care. The aim of this study was to identify aspects of hospital care that affect patient satisfaction by examining the structural and convergent validity of an in-house questionnaire. Methods: The sample consisted of 3320 patients discharged from an Italian public hospital. The questionnaire included items exploring communication with nurses and physicians, pain management, quality of accommodation, and discharge information. Data were analyzed using the Rasch model. Results: From the patients’ perspective, the number of response options was excessive and the questionnaire proved to have both medical and accommodation dimensions. Patients, on average, gave higher satisfaction scores to the medical dimension over the accommodation dimension. Higher satisfaction was associated with kindness and courtesy of the nursing staff, doctors’ courtesy, and the quality of bed linen. Conclusion: The results support the administration of the questionnaire but suggest change in the hospital’s analytical procedures in order to match the drivers of satisfaction as seen by the patients.
Practice-based interprofessional education: Looking into the black box

This paper reports on part of the evaluation of “The Common Learning Programme in the North East”, which offered practice-based interprofessional education (IPE) to pre-qualification students. A realistic evaluation approach was used and data collection methods included interviews and observations in an attempt to look into “the black box” of practice-based IPE. The contexts of the sessions covered a number of clinical settings and involved a range of participants. Mechanisms included the content of the sessions and the procedures involved. Findings illustrate the complex and unpredictable ways in which discussions arise and evolve during IPE sessions and how interplay exists both between the contexts and the mechanisms, and between knowledge types. Issues are raised regarding the facilitation of IPE and the influence of the current evidence-based movement on research types. This study highlights the complexity and unpredictability of practice-based IPE and the usefulness of research approaches that look into the black box of educational practice.
Network Analysis and Modeling: Special Issue of European Journal of Applied Mathematics

This special issue of the European Journal of Applied Mathematics features research articles on networks , one of the most exciting areas of applied mathematics. The study of networks incorporates tools from a wide variety of areas — including graph theory (of course), dynamical systems, optimization, statistical physics, probability, statistics, and more — and is important for applications in just about any area that one might imagine. Scholars who study networks ask questions like the following: Who are the most important people and collaborations in a network of political committee memberships? How have ideas spread over Twitter and other social media in the #Brexit debate, and how has this spread of ideas inﬂuenced opinions and events? What are the properties of entropy and random walks in networks with multiple subsystems or with multiple types of social ties? What is a good movie-recommendation strategy in a social network? Which parts of a granular material are the least stable, and how should one measure this? How can one improve transportation systems and building layouts to ease traﬃc congestion? How can one control cascading failures in infrastructure or ﬁnancial networks? Which species are the most important ones in an ecosystem? What is the best vaccination strategy to contain a disease? Which sets of genes and molecular interactions are responsible for a given disease? Which molecular network properties explain the comorbidity of two diseases? In its broadest form, a network is a representation of a complex systems of interacting entities [16,20,23,30,32]. Most traditionally, a network is represented mathematically as a graph, with “nodes” encoding entities and “edges” encoding the interactions between those entities. However, the term “network” is more general than a graph, as a network can encompass connections among an arbitrary number of entities, can have nodes and/or edges that change in time, can include multiple types of edges, often have associated dynamical processes both on the networks and of the networks, and so on. Our special issue surveys a diverse cross section of topics in the mathematical study of networks, including a variety of methods and applications, but there are also many others. A few of the many other popular topics in network science are multilayer networks [4,19],
A linguistic 2-tuple multicriteria decision making model dealing with hesitant linguistic information

Decision making has become a core research area in different fields such as evaluation, engineering, medicine, etc. Usually, decision making problems are defined in contexts with vague and imprecise information. The use of linguistic modeling has provided successful results in decision making problems. However, most of the linguistic approaches are limited, because they restrict the elicitation of linguistic information to single linguistic terms and sometimes due to the lack of information, time or knowledge, decision makers hesitate among several linguistic terms to elicit their assessments and the use of only one linguistic term cannot reflect their assessments in a proper way. Therefore, more elaborated expressions than single linguistic terms might support decision makers in such hesitant situations and improve the elicitation of hesitant linguistic information. The use of hesitant fuzzy linguistic term sets (HFLTS), allows modeling this hesitation and facilitates the generation of comparative linguistic expressions similar to the expressions used by human beings in real world decision making problems using context-free grammars. There are different decision making models that deal with HFLTS, however they do not provide linguistic results as the computing with words scheme proposed to facilitate their comprehension. Therefore, the aim of this contribution is to present a multicriteria decision making model that not only improves the elicitation of hesitant linguistic information, but also obtains linguistic results easy to understand by decision makers. To achieve this latter goal the proposed model will make use of the linguistic 2-tuple model.
Low Spatial Frequency Bias in Schizophrenia is Not Face Specific: When the Integration of Coarse and Fine Information Fails

Studies have shown that patients with schizophrenia exhibit visual processing impairments, particularly regarding the processing of spatial frequencies. In a previous work, we found that, compared to healthy volunteers, patients were biased toward low spatial frequencies (LSF) to identify facial expression at a glance. Given the ubiquity of faces in visual perception, it remains an open question whether the LSF bias is face specific or also occurs with other visual objects. Here, 15 patients with schizophrenia and 11 healthy control adults performed a categorization task with hybrid stimuli. These stimuli were single images consisting of two different objects, a fruit and an animal, each in a specific spatial frequency range, either low (LSF) or high (HSF). Observers were asked to report if they saw an animal or a fruit. The reported category demonstrated which spatial scale was preferentially perceived in each trial. In a control experiment, participants performed the same task but with images of only a single object, either a LSF or HSF filtered animal or fruit, to verify that participants could perceive both HSF or LSF when presented in isolation. The results on the categorization task showed that patients chose more frequently LSF with hybrid stimuli compared to healthy controls. However, both populations performed equally well with HSF and LSF filtered pictures in the control experiment, demonstrating that the LSF preference found with hybrid stimuli in patients was not due to an inability to perceive HSF. The LSF preference found in schizophrenia confirms our previous study conducted with faces, and shows that this LSF bias generalizes to other categories of objects. When a broad range of spatial frequencies are present in the image, as in normal conditions of viewing, patients preferentially rely on coarse visual information contained in LSF. This result may be interpreted as a dysfunction of the guidance of HSF processing by LSF processing.
PSO-HC: Particle swarm optimization protocol for hierarchical clustering in Wireless Sensor Networks

Clustering is an efficient topology control approach for maximizing the lifetime and scalability of Wireless Sensor Networks (WSNs). Many cluster-based routing techniques have been proposed in the literature. However, in most of the proposed protocols, the communication between a sensor node and its designated cluster head (CH) is assumed to be single-hop. Multi-hop communication can be used when the communication range of the sensor nodes is limited or the number of sensor nodes is very large in a network. Moreover, they used a predetermined percentage of CHs regardless of the network density or the number of live nodes. Clustering is known to be non-deterministic polynomial (NP)-hard problems for a WSN. Particle Swarm Optimization (PSO) is a swarm intelligent approach that can be applied for finding fast and efficient solutions of such problems. In this paper, we propose a novel centralized PSO protocol for Hierarchical Clustering (PSO-HC) in WSNs. Our objective is to maximize the network lifetime by minimizing the number of active CHs and to maximize the network scalability by using two-hop communication between the sensor nodes and their respective CHs. The effect of using a realistic network and energy consumption model in cluster-based communication for WSN was investigated. Extensive simulations show that PSO-HC outperforms the well-known cluster-based sensor network protocols in terms of average consumed energy and throughput.
An improved algorithm for eye corner detection

In this paper, a modified algorithm for the detection of nasal and temporal eye corners is presented. The algorithm is a modification of the Santos and Proenka Method. In the first step, we detect the face and the eyes using classifiers based on Haar-like features. We then segment out the sclera, from the detected eye region. From the segmented sclera, we segment out an approximate eyelid contour. Eye corner candidates are obtained using Harris and Stephens corner detector. We introduce a post-pruning of the Eye corner candidates to locate the eye corners, finally. The algorithm has been tested on Yale, JAFFE databases as well as our created database.
DYMS (Dynamic Matcher Selector) - Scenario-based Schema Matcher Selector

Schema matching is one of the main challenges in different information system integration contexts. Over the past 20 years, different schema matching methods have been proposed and shown to be successful in various situations. Although numerous advanced matching algorithms have emerged, schema matching research remains a critical issue. Different algorithms are implemented to resolve different types of schema heterogeneities, including differences in design methodologies, naming conventions, and the level of specificity of schemas, amongst others. The algorithms are usually too generic regardless of the schema matching scenario. This situation indicates that a single matcher cannot be optimized for all matching scenarios. In this research, I proposed a dynamic matcher selector (DYMS) as a probable solution to the aforementioned problem. The proposed DYMS analyzes the schema matching scenario and selects the most appropriate matchers for a given scenario. Selecting matchers are weighted based on the parameter optimization process, which adopts the heuristic learning approach. The DYMS returns the alignment result of input schemas.
Epoxy Resin Modified with Epoxidized Soybean Rubber

Abstract Epoxy resin is widely used for coatings, adhesives, casting, electrical insulation materials, and other applications. However, unsolved problems still remain in these applications. The main problem is low toughness: cured epoxy resin is rather brittle with poor resistance to the propagation of cracks, derived from the internal stress generated from shrinkage in the cooling process from cure temperature to room temperature. To solve this problem epoxidized soybean oil (ESO) has been used to toughen epoxy resin cured with an ambient temperature hardener, Tris-2,4,6-(N,N-dimethyl amino methyl) phenol to reduce the internal stress, by introducing a two-phase structure. The ESO was prepolymerized with the amine hardener to obtain the liquid epoxidized soybean rubber (ESR). The ESR-modified epoxy networks were evaluated for their impact and adhesive properties. The epoxy-ESR compositions were systematically varied to study the effect of modifier concentration on adhesion and impact strength. Optimum properties were obtained at a concentration of 20% ESR polymerized for 60 hr. The scanning electron microscopy analysis indicates phase separation between the epoxy-rich phase and ESO-rich phase.
Software Artefact Traceability: the Never-Ending Challenge

Software artefact traceability is widely recognised as an important factor for the effective development and maintenance of a software system. Unfortunately, the lack of automatic or semi-automatic supports makes the task of maintaining links among software artefacts a tedious and time consuming one. For this reason, often traceability information becomes out of date or it is completely absent during software development. In this working session, we discuss problems and challenges related to various aspects of trace-ability in software systems.
A Mechanics Model of Skin Penetration

Experiments are performed to show that sharp-tipped needles and high pressure liquid jets pierce skin and silicone rubbers by a similar penetration mechanism. The solid tears to form a crack, which opens to accommodate the punch. A model is presented for the penetration of soft solids, such as skin and rubber, by a sharp-tipped punch. Both the model and the experiments reveal that to penetrate the solid, the average pressure across the punch tip increases with diminishing punch radius. It is also shown that the penetration pressure increases for tougher solids with stronger strain hardening capacities.Copyright © 2003 by ASME
From gene to protein—experimental and clinical studies of ACE2 in blood pressure control and arterial hypertension

Hypertension is a major risk factor for stroke, coronary events, heart and renal failure, and the renin-angiotensin system (RAS) plays a major role in its pathogenesis. Within the RAS, angiotensin converting enzyme (ACE) converts angiotensin (Ang) I into the vasoconstrictor Ang II. An “alternate” arm of the RAS now exists in which ACE2 counterbalances the effects of the classic RAS through degradation of Ang II, and generation of the vasodilator Ang 1-7. ACE2 is highly expressed in the heart, blood vessels, and kidney. The catalytically active ectodomain of ACE2 undergoes shedding, resulting in ACE2 in the circulation. The ACE2 gene maps to a quantitative trait locus on the X chromosome in three strains of genetically hypertensive rats, suggesting that ACE2 may be a candidate gene for hypertension. It is hypothesized that disruption of tissue ACE/ACE2 balance results in changes in blood pressure, with increased ACE2 expression protecting against increased blood pressure, and ACE2 deficiency contributing to hypertension. Experimental hypertension studies have measured ACE2 in either the heart or kidney and/or plasma, and have reported that deletion or inhibition of ACE2 leads to hypertension, whilst enhancing ACE2 protects against the development of hypertension, hence increasing ACE2 may be a therapeutic option for the management of high blood pressure in man. There have been relatively few studies of ACE2, either at the gene or the circulating level in patients with hypertension. Plasma ACE2 activity is low in healthy subjects, but elevated in patients with cardiovascular risk factors or cardiovascular disease. Genetic studies have investigated ACE2 gene polymorphisms with either hypertension or blood pressure, and have produced largely inconsistent findings. This review discusses the evidence regarding ACE2 in experimental hypertension models and the association between circulating ACE2 activity and ACE2 polymorphisms with blood pressure and arterial hypertension in man.