Miracle-dz/UniFAR-FTUs huggingface dataset:
Prognostic factors in patients with primary invasive vaginal carcinoma.

AIM OF THE STUDY Aim of the study was the assessment of prognostic factors in the group of primary invasive vaginal carcinoma (PIVC) patients subjected to radical radiation therapy MATERIAL AND METHODS The analysis was performed for the group of 152 PIVC patients treated with intracavitary brachytherapy alone (16.5%), the combination of brachytherapy and external radiotherapy (78.9%), or external radiotherapy alone (4.6%). The relationship was investigated between treatment outcome and the following demographic, clinical and histopathological features: age, duration of pathological symptoms, number of births given, prior hysterectomy haemoglobin level, Karnofsky performance status score, primary tumour location in vagina, length of vagina involved, FIGO stage, gross appearance, histological type, and tumour grade. RESULTS Five-year disease-free survival was observed in 46.1% of the patients (70/152). Patients below 60 years of age, with Karnofsky score of 80-90, diagnosed with PIVC in stage 10 or 110, and with tumour of grade G1 or G2 had significantly higher 5-year disease-free survival. Multifactoral analysis showed that age below 60 and FIGO stage 10 and 110 are independent favourable prognostic factors. CONCLUSIONS The independent prognostic factors in PIVC patients treated with radical radiotherapy are patient age and FIGO stage.
Difference tools for analysis and design documents

This paper presents a concept and tools for the detection and visualization of differences between versions of graphical software documents such as ER, class or object diagrams, state charts, etc. We first analyze the problems which occur when comparing graphical documents and displaying their similarities and differences. Our basic approach is to use a unified document which contains the common and specific parts of both base documents with the specific parts being highlighted. The central problem is how to reduce the amount of highlighted elements and enable the developer to have a certain amount of control over the changes be selectively highlighted. With regard to tool construction, we assume that software documents are modeled in a fine-grained way, that they are stored as syntax trees in XML (eXtensible Markup Language) files or a repository system and that a version management system is used. By using the features of the data model and the version model we are able to detect and visualize differences between diagram versions, including structural changes (e.g. shifting of a method from one class to another). We further exploit information about the version history delivered by the underlying version management system by highlighting only differences based on structural or logical changes.
Into the dark: patterns of middle ear adaptations in subterranean eulipotyphlan mammals

Evolution of the middle ear ossicles was a key innovation for mammals, enhancing the transmission of airborne sound. Radiation into various habitats from a terrestrial environment resulted in diversification of the auditory mechanisms among mammals. However, due to the paucity of phylogenetically controlled investigations, how middle ear traits have diversified with functional specialization remains unclear. In order to identify the respective patterns for various lifestyles and to gain insights into fossil forms, we employed a high-resolution tomography technique and compared the middle ear morphology of eulipotyphlan species (moles, shrews and hedgehogs), a group that has radiated into various environments, such as terrestrial, aquatic and subterranean habitats. Three-dimensional geometric morphometric analysis was conducted within a phylogenetically controlled framework. Quantitative shapes were found to strongly reflect the degree of subterranean lifestyle and weakly involve phylogeny. Our analyses demonstrate that subterranean adaptation should include a relatively shorter anterior process of the malleus, an enlarged incus, an enlarged stapes footplate and a reduction of the orbicular apophysis. These traits arguably allow improving low-frequency sound transmission at low frequencies and inhibiting the low-frequency noise which disturbs the subterranean animals in hearing airborne sounds.
Polyacrylamide gel electrophoresis of the capsular polysaccharides of Escherichia coli K1 and other bacteria

Methods were developed for the polyacrylamide gel electrophoretic analysis of capsular polysaccharides of bacteria with Escherichia coli K1 as a model. Conditions were determined for the rapid and gentle extraction of the K1 polysaccharide by incubation of the bacteria in a volatile buffer and for the subsequent removal of the putative phospholipid moiety attached to the reducing end of the polysaccharide. Detection of the polysaccharides after gel electrophoresis was carried out by fluorography of samples labeled by sodium borotritiide reduction or by combined alcian blue and silver staining. The smallest components could be detected only by fluorography, owing to diffusion during staining. Components of the E. coli K1 polysialic acid capsule ranging from monomers to 80 sialic-acid-unit-containing polymers could be separated as distinct bands in a ladderlike pattern. A maximum chain length of 160 to 230 sialyl residues was estimated for the bulk of the K1 polysaccharide from the nearly linear reciprocal relationship between the logarithm of the molecular size and the distance of migration. Gel electrophoresis of capsular polysaccharides of other bacterial species revealed different electrophoretic mobilities for each polysaccharide, with a ladderlike pattern displayed by the fastest-moving components. There are many potential applications of this facile method for the determination of the sizes of molecules present in a polydisperse polysaccharide sample. When combined with the simple method for the isolation of the capsule, as in the case of the K1 capsule, it provides an efficient tool for the characterization and comparison of the capsular polysaccharides of bacteria.
Comedogenicity and irritancy of commonly used ingredients in skin care products

A survey, using the rabbit ear, of the comedogenicity and irritancy of several groups of skin care products indicates that many contain follicular and surface epithelial irritating ingredients. These ingredients fall into several chemical classes. Certain generalizations can be deduced by examining the results: (1) me-dium-chain-length fatty acids are more potent than short- or long-chain fatty acids in producing follicular keratosis, (2) the comedogenicity and irritancy of an organic material can be reduced by combining the molecule with a polar sugar or a heavy metal, (3) increasing the degree of ethoxylation in a molecule tends to reduce the comedogenicity and irritancy of the chemical, and (4) the longer chain lipids, i.e., waxes, appear too large to produce a reaction. By following the guidelines developed in this study, it is possible to formulate nonirritating, noncomedogenic moisturizers, sunscreens, hair pomades, cosmetics, and condi-tioners.
Fast and Accurate PSD Matrix Estimation by Row Reduction

SUMMARY Fast and accurate estimation of missing relations, e.g. , similarity, distance and kernel, among objects is now one of the most important techniques required by major data mining tasks, because the missing information of the relations is needed in many applications such as economics, psychology, and social network communities. Though some approaches have been proposed in the last several years, the practical balance between their required computation amount and obtained accuracy are insu ﬃ cient for some class of the relation estimation. The objective of this paper is to formalize a problem to quickly and e ﬃ ciently estimate missing relations among objects from the other known relations among the objects and to propose techniques called “ PSD Estimation ” and “ Row Reduction ” for the estimation problem. This technique uses a characteristic of the relations named “ Positive Semi-Deﬁniteness (PSD)” and a special assumption for known relations in a matrix. The superior performance of our approach in both e ﬃ ciency and accuracy is demonstrated through an evaluation based on artiﬁcial and real-world data sets.
The influence of documenting assumed values of product properties on the number of iterations in the design process - first observations

Iterations are an integral part of the product design process and can become necessary when there are inconsistencies between the requirements and the solution at hand. However, not all iterations are beneficial - some are unnecessary, for example, those arising from inappropriate return points. The identification of potentially wrong assumptions about product properties can indicate promising iteration return points. This paper presents the results of survey of product development engineers about iterations and assumed values of properties in their work. Additionally, we conducted a design experiment to further analyse the influence of documenting assumed values of properties on the number of iterations, the ratio of unnecessary to useful iterations and task success. Based on the results, we recommend a network-based documentation of assumptions with meta-information about confidence in the assumptions to aid identification and prioritisation of potential iteration return points.
Theoretical efficacy of using albumin/plasma versus full plasma replacement in TTP

To the Editor: The standard of care for the treatment of thrombotic thrombocytopenia purpura (TTP) is daily plasma exchange (PLEX) with fresh frozen plasma (FFP) or cryopoor plasma (CPP) replacement. This therapy both removes inhibitors of ADAMTS13 (as seen in most cases of idiopathic TTP) and provides exogenous ADAMTS13. However, limited data suggest that the use of albumin as the replacement fluid for the first half of the exchange followed by FFP or CPP is equally efficacious in the treatment of TTP [1]. It has been further suggested that the use of albumin for the first half of the PLEX procedure may be particularly beneficial in the setting of (i) limited availability of compatible plasma (e.g., a group AB patient) or (ii) in the case of patients with frequent and or severe allergic reactions to plasma (thereby reducing the allergenic exposure) [2,3]. We were curious as to the theoretical efficacy of an exchange in which the first half of the replacement was albumin, followed by FFP or CPP compared to an exchange with full plasma replacement. We used a formula supported by a previously described calculus-based one-compartment model for the kinetics of partial or full replacement for PLEX [4]:
A new efficient excitation scheme for the FDTD method based on the field and impedance template

We have presented a new excitation scheme for the FDTD analysis of guided wave problems. Tangential E-field components in the input plane are driven by elementary sources with both amplitude and output impedance determined by the modal template. This permits accurate FDTD simulations using only short sections of input feeds. For typical microwave circuits such as a patch antenna considered in the present paper, a reduction in computer resources by a factor of two is achieved. The templates are established automatically by the 2DV FDTD algorithm operated in an optimization loop. By using the 2DV rather than 3D FDTD template generation, we can easily consider a fundamental mode or any higher mode, and distinguish between two propagating modes such as an odd and even mode in the presented example of asymmetrical coupled microstrip lines.
Research on the Personalized Recommendation Algorithm for Hairdressers

In order to retain customers, hairdressers usually persuade customers to be their members by offering membership card. This paper studies how to set up their recommendation system in the hairdressers. According to the membership information and consumer behavior, the hairdresser provides personalized recommendation to different members and lets customers experience personalized choices. A recommendation algorithm based on customer ratings and a customer classification method based on Logistic Regression Model are discussed in this paper. The former is used to recommend hair style and color to a customer. The latter is used to determine whether to recommend some maintenance programs to a customer or not.
The application of AUV navigation based on cubature Kalman filter

Precise positioning of AUV plays an important role in the efficient and reliable underwater operation. The extended Kalman filter (EKF) is the most commonly used method, because this algorithm is easy to implement. However, EKF is only effective for nonlinear systems with approximate linearity, then truncation error is introduced. When the initial state error is large or the system model has high nonlinearity, the estimation effect is poor and the convergence rate is slow. In order to overcome the shortcomings of the EKF, Ienkaran Arasaratnam and Simon Haykin put forward the cubature Kalman filter (CKF). Cubature Kalman filter (CKF) based on the third-degree spherical-radial cubature rule has been proposed and used in many applications, such as positioning, sensor data fusion, and attitude estimation [1]. A large number of experiments by the Swordfish-AUV system platform were carried out in Yantai Menlou reservoir. We analyze the experimental data and conclude that CKF algorithm is closer to the real trajectory than the EKF algorithm.
Enhanced Gene Transfer with Fusogenic Liposomes Containing Vesicular Stomatitis Virus G Glycoprotein

ABSTRACT Exposure of Lipofectin-DNA complexes to the partially purified G glycoprotein of the vesicular stomatitis virus envelope (VSV-G) results in loss of serum-mediated inhibition and in enhanced efficiency of gene transfer. Sucrose density gradient sedimentation analysis indicated that the VSV-G associates physically with the DNA-lipid complex to produce a VSV-G liposome. The ability to incorporate surrogate viral or cellular envelope components such as VSV-G into liposomes may allow more-efficient and possibly targeted gene delivery by lipofection, both in vitro and in vivo.
Functional analysis of drought-resistant genes in barley using VIGS

The following study analyzed the role of the gamma-aminobutyric acid transaminase (GABAT) gene in the response of barley plants to drought stress. Expression of GABAT in barley was suppressed using virus-induced gene silencing (VIGS). In VIGS, an RNA virus is used to replicate a small portion of the target RNA. In this study, barley stripe mosaic virus (BSMV), that carries a piece of the GABAT gene to infect barley, was used. As the virus replicates inside infected barley plants, it also makes RNA that is complementary to GABAT messenger RNA (mRNA) that is normally made by the host. The presence of this double-stranded RNA triggers the RNA interference (RNAi) pathway, which degrades GABAT, inhibiting its translation. The silenced plants were assessed for their response to drought stress. The amount of GABAT mRNA in the silenced plants was estimated using real-time PCR. The results showed that expression of GABAT was down-regulated by 65-77% in the silenced plants. The silenced plants exposed to drought conditions displayed more drought symptoms than those with a normal amount of GABAT enzyme. This indicates that the GABAT gene plays an important role in the drought tolerance of barley. i FUNCTIONAL ANALYSIS OF BARLEY USING VIGS
Effect of handling stress on resonance ultrasonic vibrations in thin silicon wafers

Resonance Ultrasonic Vibration (RUV) metrology offers a sensitive non-destructive real-time solution to silicon wafer crack detection. The stresses generated in the wafers by the handling device used in the RUV method may have a significant influence on the effectiveness of this method, particularly for thinner wafers. The handling stresses produced by different designs of the vacuum wafer holders and their effects on the resonance properties of the ultrasonically excited wafer are studied using Finite Element Analysis (FEA) and confirmed by RUV tests. FEA results and RUV experiments show that optimization of the wafer handling stress obtained by redesigning the wafer holder does not alter the resonance frequencies and mode shapes of the wafer significantly compared to the free vibration case. Therefore, it is possible to use RUV approach for crack detection in thin silicon wafers without significant modification.
Alcohol screening in primary care

Behind the numbers What should primary care doctors do about screening for alcohol problems? Beich and colleagues (p 590) seem to have provided the answer: Nothing. Some will consider their results authoritative and conclude these activities are ineffective in general practice. But as with all systematic reviews and meta-analyses, there can be devils in the details. Beich et al have addressed a clinically important question: “How effective is screening in general practice for identifying drinkers who can and do benefit from brief intervention? ” The most trustworthy answer would come from a randomized controlled trial of screening and brief intervention compared with no systematic screening or intervention, but no such studies exist.1 The results of such a trial would provide a direct measurement of the number needed to screen (NNS) to benefit one patient.2 In the absence of studies evaluating such direct evidence, reviewers are forced to examine and link separate bodies of evidence (Is the screening test accurate? How effective is the intervention? ). With the …
Classification of heart sounds using a multilayer feed-forward neural network

Cardiovascular diseases are among chronic diseases that seriously threaten human health. Medical experts sometimes listen to heart sounds through auscultation system, either from stethoscope or PCG (phonocardiogram), as one of the ways in diagnosing cardiovascular diseases. The auscultation process is subjective and largely depends on the experience, skill, knowledge or hearing ability of the physician to interpret heart conditions. This paper examines heart valve-related diseases using a multilayer feed-forward neural network (MFNN). The heart sounds were digitally filtered with moving average filter, segmented with sliding window and then reduced to an arbitrary frame of 64 points. After that, it is pre-processed by fast Fourier transform prior to feeding into the neural network for classification. To check for network robustness, the heart sound samples were injected with different level of noise. A total of 55 types of sample data were generated and used for classification. The study produces a 100% correct classification of eleven heart-valve diseases.
The Evolving Genome Project: current and future impact.

The National Institutes of Health/Department of Energy Human Genome Project has been funding directed research for only 5 years, and it is understandably difficult to cite important research advances directly attributable to the project. However, the project has been constructive in fostering multidisciplinary group research and an inspiring and synergistic "just do it" attitude in both political and scientific circles, domestically and abroad. This collaborative spirit has spawned large-scale genetic and physical mapping projects, with the most impressive and useful results to date being the dense genetic maps produced by the Généthon, a French organization largely supported by the French muscular dystrophy association. With the genetic and physical map reagents now becoming available, disease-gene cloning is proceeding at an increasingly rapid pace. More important than the predictable acceleration of disease-gene mapping are the unpredictable benefits: Will a dense PCR-based dinucleotide-repeat genetic map open novel alternative approaches to disease-gene isolation? Will it become possible to localize disease genes by simply analyzing unrelated, isolated probands rather than the rarer "extended family"? Proband-based "linkage-disequilibrium cloning" may become possible if adequate density, informativeness, and stability of polymorphic loci are obtained. In addition, "genome exclusion cloning" will be added to the established positional, candidate-gene, and functional-disease-gene-cloning experimental approaches. The anticipated exponential expansion of human genetic disease information over the remainder of the 10-year tenure of the Human Genome Project unveils critical yet unresolved issues for medical education and the practice of medicine. (ABSTRACT TRUNCATED AT 250 WORDS)
Underwater image segmentation method based on MCA and fuzzy clustering with variational level set

Noise and non-uniform gray level in underwater image cause the low segment precision, this paper presents a segmentation framework based on morphological component analysis (MCA) and fuzzy clustering with variational level set. The framework uses MCA method to sparse decompose the image into texture and cartoon parts. The cartoon part contains the mainly information with less noise, which is good for segmentation. In order to obtain the cartoon part's weaken edges, we have proposed the variational level set method combine with fuzzy clustering. The segmentation algorithm utilizes the subordinate properties of the fuzzy clustering membership function to construct the new variational level set, and uses the minimization of energy functional to get the evolution equation of the level set function. That process can get the final segmentation. The experiment results illustrate that the proposed algorithm, compared with classical segmentation methods, as Fuzzy C-means clustering model, Chan-Vese model and Local Binary Fitting model, can reduce the influence of the noise and obtain a better segmentation result for underwater images.
Convex optimization based multiuser detection for uplink large-scale MIMO under low-resolution quantization

In large-scale Multiple-Input-Multiple-Output, the Base Station (BS) is equipped with a large-size antenna array containing tens even hundreds Radio Frequency channels. If so many RF front-ends adopt the classical receivers, their cost and power consumption during the receiving mode would increase quickly. Therefore, we exploit low-resolution Analog-to-Digital-Convertor to design low-power and low-cost software defined radio receivers for the BS. However, the new problem is how the BS fulfills channel estimation and Multiuser Detection (MUD) under low-resolution quantization. In this paper, first, least square method is used for channel estimation, and a robust Maximum Likelihood (ML) MUD problem is constructed to take into account the channel estimation errors. Second, an iterative multiuser detector is constructed by relaxing the ML MUD problem as a convex optimization problem and then solving the convex problem through the nonmonotone spectral projected gradient method. Compared with the Minimum Mean Square Error (MMSE) detector, the proposed detector has lower computational complexity, and is more suitable for hardware implementation. Simulation results show that it also outperforms MMSE.
Intelligent Agriculture Greenhouse Environment Monitoring System Based on the Android Platform

Agriculture is the backbone of any Countrys economy and there is a strong correlation between agricultural growth and economic prosperity. The traditional automated monitoring systems are wired and larger in size. It mostly uses only PC as a surveillance terminal, which works efficiently but does not give portability. This article proposed an intelligent Monitoring System which is based on android platform gives facility to access monitored parameters quickly on mobile handsets anywhere from the world, real-time video monitoring, maintenance and management. The test and application shows that is stable, cheap, good mobility and easy to operate, it is a strong practicality and application prospects.