Miracle-dz/UniFAR-FTUs huggingface dataset:
Pancreas transplantation in crossmatch‐positive recipients

Abstract: Background: Prolonged cold preservation time can unfavorably affect outcome in pancreas transplantation. To reduce this ischemic time, cadaver pancreas grafts, in selected cases, are sometimes transplanted before crossmatch results are known. We report our experience with pancreas transplants in recipients with either current or historically positive T‐ or B‐cell crossmatches.
Exploiting Page Correlations for Write Buffering in Page-Mapping Multichannel SSDs

Advanced solid-state disks (SSDs) have been equipped with page-mapping flash translation layers and multichannel architectures. The SSDs employ a RAM-based write buffer, which delays write requests for reducing write traffic, reorders requests for mitigating garbage-collection overhead, and produces parallel page writes for improving channel time utilization. This work presents a novel write buffer algorithm that exploits temporal and spatial correlations among buffer pages. The write-buffer groups temporally or spatially correlate buffer pages and then write the grouped buffer pages to the same flash block. In this way, when the correlated page data are updated in the future, flash blocks will receive bulk page invalidations and become good candidates for garbage collection. With multichannel architectures, the write buffer adaptively disperses read-most sequential data over channels for high page-level parallelism of sequential reads, while clustering write-most sequential data in the same channel for a reduced cost of garbage collection. We evaluated the proposed method and previously proposed buffer algorithms. Our method was shown to outperform the existing methods by up to 134%. We also implemented our buffer design on the OpenSSD platform; the time and space overheads of our design were reported to be very low.
Prevalence of protein-energy wasting (PEW) and evaluation of diagnostic criteria in Japanese maintenance hemodialysis patients.

BACKGROUND AND OBJECTIVES The International Society of Renal Nutrition and Metabolism (ISRNM) has recently recommended the use of the term "protein-energy wasting" (PEW). PEW is a state of malnutrition with decreased body stores of protein and energy fuel in hemodialysis patients and is known as a risk factor for morbidity and mortality. We examined the prevalence of PEW and the characteristics of PEW patients in a hemodialysis center in Japan. METHODS AND STUDY DESIGN Fifty-nine outpatients undergoing maintenance hemodialysis at Iga City General Hospital were evaluated. We observed their biochemical data, body composition, dietary intake, and the number of steps prospectively. PEW was defined according to ISRNM criteria. RESULTS Nine patients (15% of total) were diagnosed as having PEW. Among indicators of PEW criteria, the relevance ratios of "reduced muscle mass" and "unintentional low dietary energy intake" were significantly higher in PEW than in non-PEW. The number of steps was lower, and serum levels of glucose and C-reactive protein were higher in PEW. CONCLUSION About 15% of Japanese hemodialysis patients are estimated to have PEW. Our results suggested that major contributing factors to PEW were reduced muscle mass, unintentional low dietary energy intake, lower amount of exercise, insulin resistance, and chronic inflammation.
Programmier-und Modellierungssprachen Oettingenstraße 67 , D – 80538 München Temporal Constructs for a Web Language

This paper reports on enriching a (logic-based) query and transformation language for the Web, called Xcerpt, with temporal constructs and temporal reasoning capabilities. Advanced Web applications often refer to temporal data, especially to time points, complex time intervals, and durations. Salient to many advanced Web applications is that they often refer to various calendars. However, current Web languages and formalisms have rather primitive temporal constructs and temporal data processing capabilities – if any. The focus of the project this paper reports on is not to specify yet another temporal logic and/or calculus. Instead, it is to select from existing temporal logics and calculi a coherent set of concepts and processing primitives to be added to a Web query and transformation language.
Feature Selection for Classification Using an Ant Colony System

Many applications such as pattern recognition require selecting a subset of the input features in order to represent the whole set of features. The aim of feature selection is to remove irrelevant or redundant features while keeping the most informative ones. In this paper, an ant colony system approach for solving feature selection for classification is presented. The proposed algorithm was tested using artificial and real-world datasets. The results are promising in terms of the accuracy of the classifier and the number of selected features in all the used datasets. The results of the proposed algorithm have been compared with other results available in the literature and found to be favorable.
Nitric Oxide Influences Blood Flow Distribution in Renovascular Hypertension

Endothelium-derived nitric oxide contributes to the regulation of regional blood flow. Inhibition of endothelium-derived nitric oxide synthesis increases blood pressure and vascular resistance. Using the substrate antagonist Nω-nitro-Larginine- methyl ester to block endothelium-derived nitric oxide synthesis, we tested the hypothesis that, in two-kidney, one clip renovascular hypertension, endothelium-derived nitric oxide plays an increased role in maintaining blood flow to the nonclipped kidney and other visceral organs compared with normotensive controls. This could be due to increased vascular shear stress, a primary stimulus for endothelium-derived nitric oxide synthesis, after the onset of hypertension. In hypertensive rats with mild renal artery stenosis, basal renal blood flow normalized by kidney weight was similar in the nonclipped and clipped kidneys. Basal blood pressure of controls was 98±2 mm Hg compared with 145±3 mm Hg in the two-kidney, one clip hypertensive rats. Nω-nitro-L-arginine-methyl ester increased blood pressure by 20±2 and 43±3 mm Hg in control and hypertensive rats, respectively. Compared with normotensive controls, basal resistance was higher in all organ beds in the hypertensive rats including brain, heart, intestine, and kidney. With the exception of the renal circulation, the increase in vascular resistance after W-nitro-L-arginine-methyl ester was greater in hypertensive rats compared with normotensive controls. In the hypertensive rats, W-nitro-L-arginine- methyl ester caused a similar increase in vascular resistance in both the nonclipped and clipped kidneys, and this was not different from normotensive controls. These results suggest that, in two-kidney, one clip hypertensive rats, as in normotensive rats, endothelium-derived nitric oxide synthesis plays an important role in regulating regional hemodynamics. In this model of hypertension, the endothelium is not dysfunctional but is a critical component in the adaptation of local organ perfusion to increased blood pressure. (Hypertension.
Does Cohesion Equal Discipline?: Towards a Conceptual Delineation

The last decades of the twentieth century saw a world of remarkable transformation and re-establishment of parliaments, as existing legislatures were rebuilt and new ones built. Contrary to the literature of the 1960s and 1970s on the decline of parliaments, legislatures have actually innovated their institutional structures and developed new and vital political roles. Parliaments have thus become almost ubiquitous as institutions of modern governance. If Lijphart was correct when he argued, ‘Legislatures should probably be regarded as the most important institutions in a democracy’, then it is essential to assess the most crucial functional organs of these influential bodies – the political parties. For, as Schattschneider declared, ‘Modern democracy is unthinkable save in terms of the parties’. Modern representative government has become party government, for good and for bad, and thus the basic pre-condition for the establishment and survival of governments depends on the ability of the political parties to control their representatives, to aggregate positions and policies, to present a coherent ideological image, to operate effectively in the legislative arena and to function as a stable basis for the political process. The existence of noticeably ‘unified’ parties is central to the theory and practice of democracy in general, and to parliamentary democracy in particular. However, according to Bowler, Farrell and Katz, because this ‘hidden assumption’ has reached normative status for a variety of scholars, its study is relatively underdeveloped. Legislative studies scholars have good reason to cease treating parties as monolithic, unitary actors, for they evidently are
Relapsed non‐Hodgkin's lymphoma diagnosed by flexible bronchoscopy

Pulmonary relapse of non‐Hodgkin's lymphoma (NHL) occurred in a 10‐year‐old girl who presented with cough, blood‐tinged sputum, and chest tightness. The diagnosis of Ki‐1 (CD30) anaplastic large‐cell lymphoma was established using bronchoalveolar lavage (BAL) and transbronchial biopsy (TBB). These procedures demonstrated malignant cells that stained positive for CD30 and had the t(2;5) translocation, thereby avoiding the need for an open lung biopsy. Pediatr Pulmonol. 2002; 34:488–490. © 2002 Wiley‐Liss, Inc.
The relationship between multi-dimensional self-compassion and fetal-maternal attachment in prenatal period in referred women to Mashhad Health Center

Background: Multi-dimensional self-compassion is one of the important factors predicting fetal-maternal attachment which vary among different cultures and countries. So the aim of this study was to determine the relationship between multi-dimensional, self-compassion, and fetal-maternal attachment in the prenatal period. Subjects and Methods: This cross-sectional study was carried on 394 primigravida women to Mashhad Health Care Centers in with two stage sampling method (cluster-convenience) in the year 2014. Demographic/prenatal characteristics, multi-dimensional self-compassion (26Q) with five dimension (including self-kindness, self-judgment, common humanity, isolation items, mindfulness, over-identified), and fatal-maternal attachment (21Q) were completed by the participants. The statistical analysis was performed with various statistical tests such as Pearson correlation coefficient, t-test, one-way ANOVA, and linear regression using SPSS statistical software (version 14). Results: Based on the findings, the mean (standard deviation) value for multi-dimensional self-compassion was 59.81 (6.4) and for fatal-maternal attachment was 81.63 (9.5). There was a positive correlation between fatal-maternal attachment and total self-compassion (P = 0.005, r = 0.30) and its dimension including self-kindness (P = 0.003, r = 0.24), self-judgment (P = 0.001, r = 0.18), common humanity (P = 0.004, r = 0.28), isolation items (P = 0.006, r = 0.17), mindfulness (P = 0.002, r = 0.15), over-identified (P = 0.001, r = 0.15). Conclusions: There was a correlation between the multi-dimensional self-compassion and fetal-maternal attachment in pregnant women. Hence, educating people like caregivers by community health midwives regarding psychological problems in during pregnancy can be effective in early diagnosing and identifying such disorders.
An adaptive bilateral negotiation model for e-commerce settings

This paper studies adaptive bilateral negotiation between software agents in e-commerce environments. Specifically, we assume that the agents are self-interested, the environment is dynamic, and both agents have deadlines. Such dynamism means that the agents' negotiation parameters (such as deadlines and reservation prices) are functions of both the state of the encounter and the environment. Given this, we develop an algorithm that the negotiating agents can use to adapt their strategies to changes in the environment in order to reach an agreement within their specific deadlines and before the resources available for negotiation are exhausted. In more detail, we formally define an adaptive negotiation model and cast it as a Markov decision process. Using a value iteration algorithm, we then indicate a novel solution technique for determining optimal policies for the negotiation problem without explicit knowledge of the dynamics of the system. We also solve a representative negotiation decision problem using this technique and show that it is a promising approach for analyzing negotiations in dynamic settings. Finally, through empirical evaluation, we show that the agents using our algorithm learn a negotiation strategy that adapts to the environment and enables them to reach agreements in a timely manner.
Facial attractiveness computation by label distribution learning with deep CNN and geometric features

Facial attractiveness computation is a challenging task because of the lack of labeled data and discriminative features. In this paper, an end-to-end label distribution learning (LDL) framework with deep convolutional neural network (CNN) and geometric features is proposed to meet these two challenges. Different from the previous work, we recast this task as an LDL problem. Compared with the single label regression, the LDL could improve the generalization ability of our model significantly. In addition, we propose some kinds of geometric features as well as an incremental feature selection method, which could select hundred-dimensional discriminative geometric features from an exhaustive pool of raw features. More importantly, we find these selected geometric features are complementary to CNN features. Extensive experiments are carried out on the SCUT-FBP dataset, where our approach achieves superior performance in comparison to the state-of-the-arts.
Parallel Symbolic Factorization for Sparse LU Factorization with Static Pivoting

In this paper we consider a direct method to solve a sparse unsymmetric system of linear equations Ax = b, which is the Gaussian elimination. This elimination consists in explicitly factoring the matrix A into the product of L and U , where L is a unit lower triangular matrix, and U is an upper triangular matrix, followed by solving LUx = b one factor at a time. One of the main characteristics of the sparse LU factorization is the notion of fill-in. This notion denotes an element that was zero in the original matrix A, but becomes nonzero during the factorization. As these fill-ins can be computed without referring to the numerical values of the matrix, and to be able to allocate memory and to organize computations before calculating the numerical values of the factors, the resolution of a sparse system is divided into several phases. We present here the specific phases of SuperLU DIST [4], a widely used algorithm to solve large sparse unsymmetric systems on distributed memory computers. The first step consists in choosing a permutation matrix P1 and diagonal matrices D1 and D2 so that P1D1AD2 has large entries on the diagonal. This helps assure accuracy of the final solution. The second step orders equations and variables by choosing a permutation matrix P2 so that the factors L and U of P T 2 P1D1AD2P2 are as sparse as possible. The third step performs a symbolic analysis, that is it identifies the locations of nonzero entries of L and U . And finally, the fourth step computes the numerical values of the factors L and U . We discuss the design and the implementation of a memory scalable symbolic factorization algorithm for unsymmetric matrices on distributed memory machines. Its integration in SuperLU DIST will transform this solver into a fully parallel solver. Earlier work has addressed the parallelization of the numerical factorization (step 4 in SuperLU), because its complexity is generally of higher order compared to the other steps. This is now a well understood problem and the algorithm implemented in SuperLU proved to be highly parallel and efficient. Techniques were proposed for computing fill-reducing ordering in parallel (step 2 in SuperLU), and we will review them briefly later in this section. More recent research focused on the development of efficient parallel algorithms for permuting large entries on the diagonal (step 1 in SuperLU). All these algorithms use distributed data structures, and in particular the input matrix A is distributed over the processors. They offer an overall good scalability. This includes memory scalability, i.e. if both the problem size and the number of processors is increased by the same factor, then the same amount of memory is used per processor.
Recruitment Kinetics of DNA Repair Proteins Mdc1 and Rad52 but Not 53BP1 Depend on Damage Complexity

The recruitment kinetics of double-strand break (DSB) signaling and repair proteins Mdc1, 53BP1 and Rad52 into radiation-induced foci was studied by live-cell fluorescence microscopy after ion microirradiation. To investigate the influence of damage density and complexity on recruitment kinetics, which cannot be done by UV laser irradiation used in former studies, we utilized 43 MeV carbon ions with high linear energy transfer per ion (LET = 370 keV/µm) to create a large fraction of clustered DSBs, thus forming complex DNA damage, and 20 MeV protons with low LET (LET = 2.6 keV/µm) to create mainly isolated DSBs. Kinetics for all three proteins was characterized by a time lag period T0 after irradiation, during which no foci are formed. Subsequently, the proteins accumulate into foci with characteristic mean recruitment times τ1. Mdc1 accumulates faster (T0 = 17±2 s, τ1 = 98±11 s) than 53BP1 (T0 = 77±7 s, τ1 = 310±60 s) after high LET irradiation. However, recruitment of Mdc1 slows down (T0 = 73±16 s, τ1 = 1050±270 s) after low LET irradiation. The recruitment kinetics of Rad52 is slower than that of Mdc1, but exhibits the same dependence on LET. In contrast, the mean recruitment time τ1 of 53BP1 remains almost constant when varying LET. Comparison to literature data on Mdc1 recruitment after UV laser irradiation shows that this rather resembles recruitment after high than low LET ionizing radiation. So this work shows that damage quality has a large influence on repair processes and has to be considered when comparing different studies.
Omalizumab and long-term quality of life outcomes in patients with moderate-to-severe allergic asthma: a systematic review

Background: Asthma is a highly prevalent chronic inflammatory airways disease, with a considerable impact on quality of life (QoL). To express the effects of asthma on patients’ subjective experience, patient-reported outcomes (PROs) represent an important instrument. The asthma QoL questionnaire (AQLQ) is one of the main PROs among these. Materials and methods: To identify long-term asthma-related QoL outcomes associated with omalizumab therapy in patients with moderate-to-severe asthma, we developed a systematic review according to the PRISMA guidelines. Published real-world effectiveness studies of adults or adolescents (12 years or older) with moderate-to-severe allergic asthma treated with omalizumab for at least 48 weeks were reviewed. Sources used were Medline (PubMed), the Cochrane Library and Google Scholar up to February 2018. In addition, a cross-referencing search was conducted to complete the revision. Results: A total of 255 potential papers were identified in the first search through the database. After full-text viewing, eight articles were finally included in the review. We summarized the results according to the study design, patient baseline characteristics and effectiveness outcomes assessed by AQLQ score results: variation from baseline to the end of study. Results confirmed the long-term benefits of omalizumab as an add-on therapy in patients with uncontrolled moderate-to-severe allergic asthma. Since there is a lot of evidence on omalizumab effectiveness, we aimed to focus on how a therapy can change patient’s QoL in a long time period. Data showed long-term effects of omalizumab treatment on subjective (PROs) and objective (lung function, corticosteroid use, hospitalizations, asthma exacerbation) effectiveness measures. Conclusion: Studies included in our review were observational trials that, due to their design, present a potential risk of selection bias in the patients included. Beyond this limit, the evaluation of QoL using the AQLQ showed a clear increase over time, following both 48 weeks and 9 years of observation, where QoL improvements still were significant over baseline values.
Approval Summary: Sunitinib for the Treatment of Imatinib Refractory or Intolerant Gastrointestinal Stromal Tumors and Advanced Renal Cell Carcinoma

Purpose: To describe the Food and Drug Administration (FDA) review and approval of sunitinib malate (Sutent). Sunitinib received regular approval for the treatment of gastrointestinal stromal tumor (GIST) after disease progression or intolerance to imatinib mesylate (Gleevec). Additionally, sunitinib received accelerated approval for the treatment of advanced renal cell carcinoma. Experimental Design: For the GIST indication, FDA reviewed data from a randomized, placebo-controlled trial with supportive evidence from a single-arm study. For the advanced renal cell carcinoma indication, FDA reviewed data from two single-arm studies of patients with cytokine-refractory metastatic renal cell carcinoma. Results: In patients with imatinib refractory or intolerant GIST, time-to-tumor progression of sunitinib-treated patients was superior to that of placebo-treated patients. Median time-to-tumor progression of sunitinib-treated patients was 27.3 weeks, compared with 6.4 weeks for placebo-treated patients (P < 0.0001). Partial responses were observed in 6.8% of sunitinib-treated patients. In patients with metastatic renal cell carcinoma, partial responses were observed in 25.5% (95% confidence interval, 17.5, 34.9) and 36.5% (95% confidence interval, 24.7, 49.6) of patients treated with sunitinib. Median response durations were 27.1 and 54 weeks. The most common adverse events attributed to sunitinib included diarrhea, mucositis, skin abnormalities, and altered taste. Reductions in left ventricular ejection fraction and severe hypertension were also more common in sunitinib-treated patients. Conclusions: On January 26, 2006, the FDA approved sunitinib for the treatment of patients with imatinib refractory or intolerant GIST. Accelerated approval was granted for the treatment of advanced renal cell carcinoma.
The triphosphoinositide phosphodiesterase of brain tissue.

Preparation of triphosphoinositide phosphodiesterase from brain extracts. The dialysed aqueous extract ofacetone-dried brain powder (Thompson & Dawson, 1964) was held in a water bath at 500 for 30 min. After cooling in an ice bath 0-25 vol. of 0(132 M-tris-HCl buffer, pH 7-2, was added. Saturated (NH4)2SO4 solution (neutralized to pH 7) at 40 was slowly added with stirring to give 30% saturation. After standing for 30 min. in ice, the precipitate was removed by centrifuging at 00 at 10000g,V. for 20 min. The supernatant was brought to 50% saturation with the (NH4)2SO4 solution, and after standing for 30 min. the precipitate was collected by centrifuging as above. The 30-50% saturated (NH4)2SO4 precipitate was dissolved in 0 02M-tris-HCl buffer, pH 7-2 (volume equal to that of the original extract), and dialysed overnight against 11. of 5 mM-tris-HCl buffer, pH 7-2, at 4°. The non-diffusible material was centrifuged in a Spinco centrifuge at 105 000gav. for 60 min. The water-clear colourless supernatant was collected, diluted with an equal volume of water and stored at 40. Conditions of incubation ancl assay of activity. The sodium