Miracle-dz/UniFAR-FTUs huggingface dataset:
A Biographical Dictionary of the Qin, Former Han and Xin Periods (221 BC - AD 24)

This is a unique and conclusive reference work about the 6,000 individual men and women known to us from China's formative first empires. Over decennia Michael Loewe (Cambridge, UK) has painstakingly collected all biographical information available. Not only those are dealt with who set the literary forms and intellectual background of traditional China, such as writers, scholars, historians and philosophers, but also those officials who administered the empire, and the military leaders who fought in civil warfare or with China's neighbours. The work draws on primary historical sources as interpreted by Chinese, Japanese and Western scholars and as supplemented by archaeological finds and inscriptions. By devoting extensive entries to each of the emperors the author provides the reader with the necessary historical context and gives insight into the dynastic disputes and their far-reaching consequences. No comparable work exists for this important period of Chinese history. Without exaggeration a real must for historians of both China and other cultures.
3D point cloud segmentation using a fully connected conditional random field

Traditional image segmentation methods working with low level image features are usually difficult to adapt to higher level tasks, such as object recognition and scene understanding. Object segmentation emerges as a new challenge in this research field. It aims at obtaining more meaningful segments related to semantic objects in the scene by analyzing a combination of different information. 3D point cloud data obtained from consumer depth sensors has been exploited to tackle many computer vision problems due to its richer information about the geometry of 3D scenes compared to 2D images. Meanwhile, new challenges have also emerged as the depth information is usually noisy, sparse and unorganized. In this paper, we present a novel point cloud segmentation approach for segmenting interacting objects in a stream of point clouds by exploiting spatio-temporal coherence. We pose the problem as an energy minimization task in a fully connected conditional random field with the energy function defined based on both current and previous information. We compare different methods and prove the improved segmentation performance and robustness of the proposed approach in sequences with over 2k frames.
Efficacité de la triple association Méthotrexate Sulfasalazine et Hydroxychloroquine dans la polyarthrite récente ayant une réponse insuffisante au Méthotrexate : méta-analyse d'essais contrôlés randomisés

Evaluer l'efficacite de la triple association de sDMARDs comprenant du methotrexate, de la sulfasalazine et de l'hydroxychloroquine par rapport a un traitement par biotherapie (bDMARD) dans le traitement de la polyarthrite rhumatoide precoce. Methodes : Une recherche systematique de la litterature a ete realisee en utilisant PubMed, la base de donnees Cochrane et les resumes presentes lors de congresde rhumatologie jusqu'en Decembre 2013. Les essais controles randomises comparant l'efficacite et la securite des bDMARD a la triple combinaison ont ete inclus. Les donnees recuperees etait le score de Sharp modifie par Van der Heijde(SHS), le taux de remission, la reponse ACR, les evenements indesirables. Les differences entre les groupes ont ete evaluees par la difference moyenne standardisee (SMD). Resultats : Nous avons analyse 1348 articles. Nous avons extrait les donnees de cinq essais comprenant 1412 patients (648 dans le groupe de triple association et 764 dans le groupe bDMARDs). A un an, la reponse clinique et radiologique etaient en faveur d'un traitement biologique. A deux annees, la progression radiologique etait moindre dans le groupe bDMARD (SMD = 0,45 IC 95% [0,17, 0,72], p = 0.001, I² = 68%). La proportion d'effets indesirables graves etait similaire dans les deux groupes OR (Odds Ratio) = 1,02 (IC a 95% [0.68,1.52],p = 0,92, I² = 0%). Conclusion : Le traitement biologique semble etre plus efficace que la combinaison triple en terme de progression radiologique dans la PR avec reponse inadequate au methotrexate.
Analysis of the roles of antilipopolysaccharide and anti-cholera toxin immunoglobulin A (IgA) antibodies in protection against Vibrio cholerae and cholera toxin by use of monoclonal IgA antibodies in vivo

Secretory immunoglobulin A (IgA) antibodies (sIgA) directed against cholera toxin (CT) and surface components of Vibrio cholerae are associated with protection against cholera, but the relative importance of specific sIgAs in protection is unknown. A monoclonal IgA directed against the V. cholerae lipopolysaccharide (LPS), secreted into the intestines of neonatal mice bearing hybridoma tumors, was previously shown to provide protection against a lethal oral dose of 10(7) V. cholerae cells. We show here that a single oral dose of 5 to 50 micrograms of the monoclonal anti-LPS IgA, given within 2 h before V. cholerae challenge, protected neonatal mice against challenge. In contrast, an oral dose of 80 micrograms of monoclonal IgA directed against CT B subunit (CTB) failed to protect against V. cholerae challenge. A total of 80 micrograms of monoclonal anti-CTB IgA given orally protected neonatal mice from a lethal (5-micrograms) oral dose of CT. Secretion of the same anti-CTB IgA antibodies into the intestines of mice bearing IgA hybridoma backpack tumors, however, failed to protect against lethal oral doses of either CT (5 micrograms) or V. cholerae (10(7) cells). Furthermore, monoclonal anti-CTB IgA, either delivered orally or secreted onto mucosal surfaces in mice bearing hybridoma tumors, did not significantly enhance protection over that provided by oral anti-LPS IgA alone. These results demonstrate that anti-LPS sIgA is much more effective than anti-CT IgA in prevention of V. cholerae-induced diarrheal disease.
A Disease Diagnostic Assistant System Using DTI and Extreme Learning Machine

There is a growing interest in applying diffusion tensor imaging (DTI) to the evaluation of brain and spinal cord related disease. In the present study, the DTI data and extreme learning machine were employed to identify the levels with cervical spondylotic myelopathy (CSM) in spinal cord. In this work, there are 40 volunteers including 20 healthy people and 20 patients with CSM ranging from 24 to 81 years old. Experiment results show that the extreme learning machine based classifier performs well in detecting the patients with CSM (accuracy 93.6%, sensitivity: 91.2%, specificity 94.7%). The current work reveals the potential of using diffusion tensor imaging in conjunction with extreme learning machine to automate the classification of healthy subjects and subjects with brain and spinal cord related disease.
Migration patterns and breast cancer risk in Asian-American women.

BACKGROUND Breast cancer incidence rates have historically been 4-7 times higher in the United States than in China or Japan, although the reasons remain elusive. When Chinese, Japanese, or Filipino women migrate to the United States, breast cancer risk rises over several generations and approaches that among U.S. Whites. PURPOSE Our objective was to quantify breast cancer risks associated with the various migration patterns of Asian-American women. METHODS A population-based, case-control study of breast cancer among women of Chinese, Japanese, and Filipino ethnicities, aged 20-55 years, was conducted during 1983-1987 in San Francisco-Oakland, California, Los Angeles, California, and Oahu, Hawaii. We successfully interviewed 597 case subjects (70% of those eligible) and 966 control subjects (75%). RESULTS A sixfold gradient in breast cancer risk by migration patterns was observed. Asian-American women born in the West had a breast cancer risk 60% higher than Asian-American women born in the East. Among those born in the West, risk was determined by whether their grandparents, especially grandmothers, were born in the East or the West. Asian-American women with three or four grandparents born in the West had a risk 50% higher than those with all grandparents born in the East. Among the Asian-American women born in the East, breast cancer risk was determined by whether their communities prior to migration were rural or urban and by the number of years subsequently lived in the West. Migrants from urban areas had a risk 30% higher than migrants from rural areas. Migrants who had lived in the West for a decade or longer had a risk 80% higher than more recent migrants. Risk was unrelated to age at migration for women migrating at ages less than 36 years. Ethnic-specific incidence rates of breast cancer in the migrating generation were clearly elevated above those in the countries of origin, while rates in Asian-Americans born in the West approximated the U.S. White rate. CONCLUSIONS Exposure to Western lifestyles had a substantial impact on breast cancer risk in Asian migrants to the United States during their lifetime. There was no direct evidence of an especially susceptible period, during either menarche or early reproductive life. IMPLICATIONS Because heterogeneity in breast cancer risk in these ethnic populations is similar to that in international comparisons and because analytic epidemiologic studies offer the opportunity to disentangle correlated exposures, this study should provide new insights into the etiology of breast cancer.
Tumor-Promoting Effects of Both Iodine Deficiency and Iodine Excess in the Rat Thyroid

Thyroid tumor-promoting effects of iodine deficiency and iodine excess were investigated in a rodent 2-stage model to estimate an optimal iodine intake range that would not effectively promote development of thyroid neoplasia. Six-week-old male F344 rats were given a single subcutaneous injection of 2,800 mg/kg body weight N-bis(2-hydroxypropyl)-nitrosamine (DHPN) or saline vehicle, maintained on Remington's iodine-deficient diet (21 ± 2 ng/g iodide), and supplemented with various amounts of potassium iodide up to 260 mg/liter in drinking water to generate conditions ranging from severe iodine deficiency to severe iodine excess. In DHPN-treated rats, both conditions significantly increased thyroid follicular tumorigenesis. In DHPN-untreated rats, iodine deficiency produced diffuse thyroid hyperplasia, characterized by small follicles with tall epithelium and reduced colloid, together with a decrease in thyroxine (T4) and an increase in thyroid-stimulating hormone (TSH). On the other hand, iodine excess produced colloid goiter, characterized by large follicles with flat epithelium and abundant colloid admixed with normal or small-sized follicles lined by cpithelium of normal height, together with normal serum T4 and slightly decreased TSH. These effects were directly proportional to the severity of iodine deficiency or extent of iodine excess and suggest that each condition has a different thyroid tumor promotion mechanism. Iodine intakes that showed the least tumor promotion were 2.6 and 9.7 μg/rat/day in this study. Promoting mechanisms and the problem of statistically estimating recommended daily iodine intake range are briefly discussed.
Islet Transplantation in Seven Patients with Type 1 Diabetes Mellitus Using a Glucocorticoid-Free Immunosuppressive Regimen

A BSTRACT Background Registry data on patients with type 1 diabetes mellitus who undergo pancreatic islet transplantation indicate that only 8 percent are free of the need for insulin therapy at one year. Methods Seven consecutive patients with type 1 diabetes and a history of severe hypoglycemia and metabolic instability underwent islet transplantation in conjunction with a glucocorticoid-free immunosuppressive regimen consisting of sirolimus, tacrolimus, and daclizumab. Islets were isolated by ductal perfusion with cold, purified collagenase, digested and purified in xenoprotein-free medium, and transplanted immediately by means of a percutaneous transhepatic portal embolization. Results All seven patients quickly attained sustained insulin independence after transplantation of a mean (±SD) islet mass of 11,547±1604 islet equivalents per kilogram of body weight (median follow-up, 11.9 months; range, 4.4 to 14.9). All recipients required islets from two donor pancreases, and one required a third transplant from two donors to achieve sustained insulin independence. The mean glycosylated hemoglobin values were normal after transplantation in all recipients. The mean amplitude of glycemic excursions (a measure of fluctuations in blood glucose concentrations) was significantly decreased after the attainment of insulin independence (from 198±32 mg per deciliter [11.1±1.8 mmol per liter] before transplantation to 119±37 mg per deciliter [6.7±2.1 mmol per liter] after the first transplantation and 51±30 mg per deciliter [2.8±1.7 mmol per liter] after the attainment of insulin independence; P<0.001). There were no further episodes of hypoglycemic coma. Complications were minor, and there were no significant increases in lipid concentrations during follow-up. Conclusions Our observations in patients with type 1 diabetes indicate that islet transplantation can result in insulin independence with excellent metabolic control when glucocorticoid-free immunosuppression is combined with the infusion of an adequate islet mass. (N Engl J Med 2000;343:230-8.)
Quantitative Decision-making in Software Engineering

Our thesis is that software repositories contain latent information that can be mined to enable quantitative decision making . The decision-making process in software development and maintenance is mostly dependent on software practitioner's experience and intuition. For example, developers use their experiences when prioritizing bug fixes, managers allocate development and testing resources based on their intuition and so on. Often these human driven decisions lead to wasted resources and increased cost of building and maintaining large complex software systems. The fundamental problem that motivates this dissertation is the lack of techniques that can automate decision-making process in software engineering. As data mining techniques became more mature, mining software repositories has emerged as a novel methodology to analyze the massive amounts of data created during software development process. Significant, repeatable patterns and behaviours in software development can be identified as a result of this mining which are often used for predicting various aspects of software development and maintenance, such as predicting defect-prone releases, software quality, or bug fix time. In this dissertation we show techniques to effectively mine software repositories, identify significant patterns during software development and maintenance, and recommend actionable aspects that can automate the decision-making process in software engineering. We demonstrate efficient techniques to use the information stored in software repositories and produce results to guide software practitioners so that they can depend less on their intuition and experience and more on actual data. To this end, in this dissertation, we make several contributions. First, we perform several empirical studies to characterize information needs of software developers and managers in the context of decision making during software development and maintenance. For example, we study what kinds of decision-making problems are important to software practitioners on a daily basis. Second, to facilitate analysis of various types of decision-making problems using a common platform, we design a generic mixed-graph model to capture associations of different software elements. We illustrate how we can build different types of hyper-edges on this mixed-graph to quantify amorphous behaviour and dependencies among various software elements. Third, to demonstrate the effectiveness of our framework, we formalize a set of four important decision-making problems that are challenging to address with the state-of-the-art. We show that our framework can achieve high-levels of prediction accuracies for different types of decision-making problems when tested on large, widely-used, real-world, long-lived software projects.
Recent Advances On Soil Moisture Data Assimilation

This study reviews recent progress on soil moisture data assimilation. Data assimilation is a process of merging observations with a system dynamic model to provide an improved estimate of the states of the environment. The application of data assimilation in hydrology is relatively new, however, rapid progress has been made in the last decade or so with the available remotely sensed soil moisture data. After briefing the history of soil moisture data assimilation, the review focuses on the most common data assimilation methods and recent progress made in soil moisture data assimilation through a case study of the soil moisture initialization activities for NASA's seasonal and interannual climate prediction. The example demonstrates that soil moisture data assimilation has made great progress in the last decade, however is still in its infancy. Good quality remotely sensed soil moisture data with accurate uncertainty information at continental and global scale are needed to ensure the success of the operational use of soil moisture data assimilation technique. Further advancement on the current soil moisture data assimilation methods is necessary to be able to assimilate multisource hydrological remote sensing data into land surface models for the best use of various remote sensing data sources at continental and global scales.
Familial Mediterranean Fever With Complete Symptomatic Remission During Pregnancy

Familial Mediterranean fever (FMF) is an inherited autosomal recessive disorder, ethnically restricted and commonly found among populations surrounding the Mediterranean Sea. FMF is the most prevalent autoinflammatory disease; is characterized by recurrent, self-limited episodes of fever with serositis; and is caused by Mediterranean fever gene (MEFV) mutations on chromosome 16. We describe a case of adult-onset FMF with complete symptomatic remission during pregnancy, without the use of colchicine. A 25-year-old woman had presented with periodic fever, abdominal pain, and vomiting since she was 21. Her abdominal computed tomography scan showed intestinal nonrotation. She underwent exploratory laparotomy and appendectomy for her symptoms 1 year prior. She had a symptom-free pregnancy period, but abdominal pain and fever recurred after delivery. Mutation analysis of the MEFV gene revealed two point mutations (p.Leu110Pro and p.Glu148Gln). We report an adult female patient with FMF in Korea with complete symptomatic remission during pregnancy.
Modeling and control of joint angles of a biped robot leg using PID controllers

The aim of this paper is to get a controlled joint angle plot for a biped robot leg having three links and four degrees of freedom. Biped robots have better mobility than conventional wheeled robots, but the mathematical modeling are complicated than other kind of robots. To design a complete stable walking robot the first necessary thing is to give complete mathematical modeling of a biped robot. In this paper we are considering a part of biped robot and giving formalism to model and control it using basic PID controllers. The Mathematical modeling of this model are done by using DH convention and Lagrange Euler equation. PID controller is applied to each joint separately to control the joint angle. All calculation to find equation of motion performed in MATLAB.
Fluoroquinolone-Resistant Alcaligenes faecalis Related to Chronic Suppurative Otitis Media, Angola

We found that 20 (10.6%) of 188 patients with chronic suppurative otitis media in Angola were co-colonized with fluoroquinolone-resistant Alcaligenes faecalis, commonly found in birds. A likely explanation for our findings was the use of bird feces by residents as a traditional remedy to prevent ear secretions caused by primary ear infection.
Dietary, environmental, and hereditary factors in the development of colorectal cancer

Recent studies have attempted to identify factors that are associated with the development of colorectal cancer both in population groups with genetic predisposition to neoplasia and in individuals in the general population who are at high risk. Environmental and dietary elements suspected of inducing or promoting colon carcinogenesis and abnormalities observed in colonic cell development are under investigation. Colorectal cancer poses a major health problem in the United States and many other countries, and is currently responsible for a high proportion of the malignant neoplasms found in the United States. Recent figures have indicated over 80,000 new cases annually in the United States and high mortality (1). The proportion of individuals who survive the disease varies with the stage at which it is detected, success being higher with earlier detection (2).
A modified BBO algorithm and its application for identifying Hammerstein system under heavy-tailed noises

The Evolutionary algorithm (EA) for researching parameters of nonlinear system is a rapidly growing field of identification. This can owe to the importance of EA for both the theoretical field and the engineering community. However, the identification of the nonlinear system is still a knotty problem, especially when heavy-tailed noises exists. Compared to classical identification methods, EA has more advantages as its fast searching speed and low complexity. In this paper, based on Biogeography Based Optimization (BBO) algorithm which was presented in recent years, a modified BBO (MBBO) is presented to overcome the premature drawback of BBO. A computing method of mutation ratio is added in MBBO to enhance exploration ability. Then, the MBBO algorithm is used for a Hammerstein model with a heavy-tailed perturbation. Experiment results verify that MBBO has much higher accuracy than BBO.