Miracle-dz/UniFAR-FTUs huggingface dataset:
Case Article - Beijing Opera Mask Sales in Four Cities in the United States

The Beijing Opera Theater Company organizes four shows a year in the United States, each in a different city. The company sells two styles of souvenir masks during each show. The case narrative is created as the retail manager of the Beijing Opera Theater Company consults her previous MBA professor to seek guidance on available resources to make cost-and service-effective ordering decisions. Available information includes historic demand data of masks and relevant costs and revenues. Other issues discussed include development of a demand forecast for a new site, analysis of the impact of exchange rate fluctuations on the orders, and leftover shipping options. EasyFitXL, a module of Excel, is used to conduct all analyses to arrive at final decisions. The methodology used to solve the case is the newsvendor model, which is appropriate for making ordering decisions in respect to seasonal, perishable, and short life-cycle items that face uncertain demand. The case requires curve-fitting skills and use of expertise related to the the newsvendor model. It can be utilized by faculty, students, consultants, and practitioners in the areas of operations and supply chain management, operations research, management science, quantitative methods, and industrial engineering to enhance inventory planning expertise. Case Teaching Note: Interested Instructors please see the Instructor Materials page for access to the restricted materials. To maintain the integrity and usefulness of cases published in ITE, unapproved distribution of the case teaching notes and other restricted materials to any other party is prohibited.
Fault-tolerant training with on-line fault detection for RRAM-based neural computing systems

An RRAM-based computing system (RCS) is an attractive hardware platform for implementing neural computing algorithms. On-line training for RCS enables hardware-based learning for a given application and reduces the additional error caused by device parameter variations. However, a high occurrence rate of hard faults due to immature fabrication processes and limited write endurance restrict the applicability of on-line training for RCS. We propose a fault-tolerant on-line training method that alternates between a fault-detection phase and a fault-tolerant training phase. In the fault-detection phase, a quiescent-voltage comparison method is utilized. In the training phase, a threshold-training method and a re-mapping scheme is proposed. Our results show that, compared to neural computing without fault tolerance, the recognition accuracy for the Cifar-10 dataset improves from 37% to 83% when using low-endurance RRAM cells, and from 63% to 76% when using RRAM cells with high endurance but a high percentage of initial faults.
Managing uncertainty: a review of food system scenario analysis and modelling

Complex socio-ecological systems like the food system are unpredictable, especially to long-term horizons such as 2050. In order to manage this uncertainty, scenario analysis has been used in conjunction with food system models to explore plausible future outcomes. Food system scenarios use a diversity of scenario types and modelling approaches determined by the purpose of the exercise and by technical, methodological and epistemological constraints. Our case studies do not suggest Malthusian futures for a projected global population of 9 billion in 2050; but international trade will be a crucial determinant of outcomes; and the concept of sustainability across the dimensions of the food system has been inadequately explored so far. The impact of scenario analysis at a global scale could be strengthened with participatory processes involving key actors at other geographical scales. Food system models are valuable in managing existing knowledge on system behaviour and ensuring the credibility of qualitative stories but they are limited by current datasets for global crop production and trade, land use and hydrology. Climate change is likely to challenge the adaptive capacity of agricultural production and there are important knowledge gaps for modelling research to address.
Learning and Generalization under Ambiguity: An fMRI Study

Adaptive behavior often exploits generalizations from past experience by applying them judiciously in new situations. This requires a means of quantifying the relative importance of prior experience and current information, so they can be balanced optimally. In this study, we ask whether the brain generalizes in an optimal way. Specifically, we used Bayesian learning theory and fMRI to test whether neuronal responses reflect context-sensitive changes in ambiguity or uncertainty about experience-dependent beliefs. We found that the hippocampus expresses clear ambiguity-dependent responses that are associated with an augmented rate of learning. These findings suggest candidate neuronal systems that may be involved in aberrations of generalization, such as over-confidence.
Silver Space-Time Trellis-Coded Modulation

Silver Code (SilC) was originally discovered in [1-4] for 2×2 multiple-input multiple-output (MIMO) transmission. It has non-vanishing minimum determinant 1/7, slightly lower than Golden code, but is fast-decodable, i.e., it allows reduced-complexitymaximum likelihood decoding [5-7]. In this paper, we present a multidimensional trellis-coded modulation scheme for MIMO systems [11] based on set partitioning of the Silver Code, named Silver Space-Time Trellis Coded Modulation (SST-TCM). This lattice set partitioning is designed specifically to increase the minimum determinant. The branches of the outer trellis code are labeled with these partitions. Viterbi algorithm is applied for trellis decoding, while the branch metrics are computed by using a sphere-decoding algorithm. It is shown that the proposed SST-TCM performs very closely to the Golden Space-Time Trellis Coded Modulation (GST-TCM) scheme, yet with a much reduced decoding complexity thanks to its fast-decoding property.
The co-morbidity of anxiety and depression in the perspective of genetic epidemiology. A review of twin and family studies

Background. Co-morbidity within anxiety disorders, and between anxiety disorders and depression, is common. According to the theory of Gray and McNaughton, this co-morbidity is caused by recursive interconnections linking the brain regions involved in fear, anxiety and panic and by heritable personality traits such as neuroticism. In other words, co-morbidity can be explained by one disorder being an epiphenomenon of the other and by a partly shared genetic etiology. The aim of this paper is to evaluate the theory of Gray and McNaughton using the results of genetic epidemiological studies. Method. Twenty-three twin studies and 12 family studies on co-morbidity are reviewed. To compare the outcomes systematically, genetic and environmental correlations between disorders are calculated for the twin studies and the results from the family studies are summarized according to the method of Klein and Riso. Results. Twin studies show that co-morbidity within anxiety disorders and between anxiety disorders and depression is explained by a shared genetic vulnerability for both disorders. Some family studies support this conclusion, but others suggest that co-morbidity is due to one disorder being an epiphenomenon of the other. Conclusions. Discrepancies between the twin and family studies seem partly due to differences in used methodology. The theory of Gray and McNaughton that neuroticism is a shared risk factor for anxiety and depression is supported. Further research should reveal the role of recursive interconnections linking brain regions. A model is proposed to simultaneously investigate the influence of neuroticism and recursive interconnections on co-morbidity.
Prognostic importance of myocardial infarct characteristics.

Left ventricular (LV) systolic function and volumes are independent predictors of long-term survival after myocardial infarction (MI). 1,2 The prognostic importance of LV pump function is mainly based on the association between systolic function and future risk of cardiac mortality related to heart failure and its consequences. Furthermore, the evidence-base for post-MI cardioprotective drug therapies, such as beta-blockers3 and angiotensin-converting enzyme inhibitors,4 is at least in part attributable to improvements in LV systolic function and attenuation of remodelling.5,6 This commentary focuses on the additive clinical utility of infarct characteristics, in addition to LV function, for prognostication after MI. Our commentary is stimulated by the publication by Lonborg et al . ,7 who studied the prognostic importance of final infarct size 3 months after MI. To appreciate how their paper might be important, one must first understand the strengths and limitations of what is currently known about the clinical significance of infarct characteristics. Until recently, the assessment of myocardial infarct characteristics, such as infarct scar, microvascular obstruction (MVO), and myocardial haemorrhage, was the exclusive domain of pathologists at post-mortem examination. Since the clinical significance of these problems in vivo was not known no specific treatments exist. Cardiac magnetic resonance imaging (CMR) provides pathological information non-invasively. CMR reveals infarct scar as a bright area of late gadolinium enhancement ∼15 min after gadolinium contrast administration.8,9 MVO is delineated by a central dark area within the hyper-enhanced infarct zone and occurs in about two-fifths of patients after MI.10 Focal haemorrhagic transformation within the infarct zone is revealed by a central dark zone on T2- or T2*-weighted CMR11–14 and occurs in about one-third of patients.12–14 Myocardial salvage is the amount of ischaemically injured, but …
Neutrophil Dysfunction in Sepsis

Objective:Sepsis is defined as life-threatening organ dysfunction due to a dysregulated host response to infection. In this article, we reviewed the correlation between neutrophil dysfunction and sepsis. Data Sources:Articles published up to May 31, 2016, were selected from the PubMed databases, with the keywords of “neutrophil function”, “neutrophil dysfunction”, and “sepsis”. Study Selection:Articles were obtained and reviewed to analyze the neutrophil function in infection and neutrophil dysfunction in sepsis. Results:We emphasized the diagnosis of sepsis and its limitations. Pathophysiological mechanisms involve a generalized circulatory, immune, coagulopathic, and/or neuroendocrine response to infection. Many studies focused on neutrophil burst or cytokines. Complement activation, impairment of neutrophil migration, and endothelial lesions are involved in this progress. Alterations of cytokines, chemokines, and other mediators contribute to neutrophil dysfunction in sepsis. Conclusions:Sepsis represents a severe derangement of the immune response to infection, resulting in neutrophil dysfunction. Neutrophil dysfunction promotes sepsis and even leads to organ failure. Mechanism studies, clinical practice, and strategies to interrupt dysregulated neutrophil function in sepsis are desperately needed.
Effects of Breathing 10 Per Cent Carbon Dioxide on the Pulmonary Circulation of Human Subjects

The effects on the pulmonary circulation of breathing 10% CO2 for 10 to 20 min were studied in five eucapnic and 11 convalescing hypercapnic patients to recreate the CO2 tensions which they had experienced during respiratory failure. Right heart catheterization permitted measurements of pulmonary arterial and wedge pressures and obtaining samples of mixed venous blood. Breathing CO2 increased mean pulmonary arterial pressures from 33 to 50 mm Hg (52%); pulmonary arterial wedge pressures were unchanged, and cardiac output increased only 22%. In three hypercapnic and two eucapnic subjects reduction of blood hydrogen ion levels by rapid infusion of 120 to 135 mEq NaHCO3 during CO2 breathing did not lower pulmonary arterial pressure significantly, nor raise cardiac output. Neither vascular pressures nor cardiac outputs changed during oxygen breathing. Larger increases in cardiac output, which were produced by exercise, raised pulmonary artery pressure only half as much as breathing 10% CO2 did. Therefore, pulmonary vascular resistance (PVR) that was elevated to an average of 4.8 mm Hg/L/min at rest while breathing air was increased to 6.5 mm Hg/L/min during CO2 breathing (P<0.01). In contrast, PVR was unchanged (4.6 mm Hg/L/min) during exercise. This difference between PVR while breathing CO2 and during exercise was statistically significant (P<0.02). Restoration of the pH of the blood toward normal by the infusion of bicarbonate during breathing of CO2 raised the pulmonary arterial pressure. The five eucapnic subjects showed similar changes during CO2 breathing and exercise, although their base-line values were significantly different. The differences were due, at least in part, to lower Paco2. This evidence suggests that CO2 acts on pulmonary arterioles and capillaries that are exposed to alveolar gases to increase the pulmonary vascular impedance.
Orthogonal complement component analysis for positive samples in SVM based relevance feedback image retrieval

Relevance feedback (RF) is an important tool to improve the performance of content-based image retrieval system. Support vector machine (SVM) based RF is popular because it can generalize better than most other classifiers. However, directly using SVM in RF may not be appropriate, since SVM treats the positive and negative feedbacks equally. Given the different properties of positive samples and negative samples in RF, they should be treated differently. Considering this, we propose an orthogonal complement components analysis (OCCA) combined with SVM in this paper. We then generalize the OCCA to Hilbert space and define the kernel empirical OCCA (KEOCCA). Through experiments on a Corel photo database with 17,800 images, we demonstrate that the proposed method can significantly improve the performance of conventional SVM-based RF.
Mitral Valve Prolapse

For half a century the systolic click and late systolic murmur lay dormant as innocent auscultatory curiosities. The thirteen years since Barlow related these phenomena to mitral leaflet prolapse have witnessed an astonishing information explosion. We have sought to bring together the accumulated data in this review.An Historical Perspective traces the evolution from the now abandoned “pericardial” or “extracardiac” phase, through the leafletchordal phase (redundancy), the myocardial phase (segmental left ventricular contraction abnormalities), to the anular phase (dilatation and faulty systolic contraction). Functional Anatomy is dealt with in terms of pathology, pathophysiology, hemodynamics, angiocardiography, echocardiography, and physical and pharmacological interventions. Clinical Manifestations are concerned with prevalence, natural history, symptoms, physical signs, electrocardiographic abnormalities and roentgen findings. The four Major Complications - sudden death, infective endocarditis, spontaneous rupture of chordae tendineae, and progressive mitral regurgitation — are examined. Associated Cardiac Diseases, i.e., Marfan's syndrome, ostium secundum atrial septal defect and atherosclerotic coronary artery disease, are discussed, and a section on Treatment deals chiefly with prophylaxis for infective endocarditis and the management of arrhythmias and chest pain. A final section on Evolving Information considers etiologic concepts, the nature of left ventricular contraction abnormalities, the cause of chest pain, the relationship to Marfan's syndrome and ostium secundum atrial septal defect, and the effect of aging and sex differences on leaflet-chordal redundancy.
An endmember dissimilarity based Non-negative Matrix Factorization method for hyperspectral unmixing

Non-negative Matrix Factorization has recently been proposed for application in the field of hyperspectral imagery. And for hyperspectral unmixing, high mixing degree and signature variability always affect the unmixing accuracy. To solve this, this paper proposed a novelmethod based on NMF to unmix hyperspectral data. Using the low similarity between endmember signatures in hyperspectral image, we proposes a constraint named endmember dissimilarity constraint which employs the spectral information divergence between signatures in the basic NMF to search a set of vectors with least similarity. This is consistent with the endmember property of the hyperspectral image. The minimum volume constraint NMF and the Piecewise Smoothness NMF with Sparseness Constraint are used to evaluate the proposed method in different mixing degree and signature variability. The experimental results in synthetic data shows that the proposed method performs best in higher mixing degree and signature variability than the other two approaches and the real AVIRIS with highly mixing degree data results also demonstrate that the proposed method performs well in identifying highly mixed endmembers.
Multiple Referrals and Multidimensional Cheap Talk

Cheap talk games have been widely used to analyze situations in which a policy maker needs expert advice. In previous work, agent uncertainty has almost always been modeled using a single-dimensional state variable. In this paper we prove that the dimensionality of the uncertain variable has an important qualitative impact on results and yields interesting insights into the 'mechanics' of information transmission. Contrary to the unidimensional case, with more than one dimension full transmission of information in all states of nature is typically possible, provided a very simple and intuitive condition is satisfied. When utilities are quadratic and there are simultaneous reports, linear independence of senders' ideal points is a sufficient condition to guarantee full revelation; with sequential reports, linear independence and a simple condition on the gradients of senders' utilities at the receiver's ideal point are sufficient. In particular as an application of the theory we are able to explain an empirical puzzle related to informational theories of legislative organization. These theories predict that legislative committees (senders) should have strong alignment of preferences with the Floor; but this doesn't fit with empirical facts. We prove that what really matters in transmission of information is the local behavior of the utilities of the senders at the ideal point of the policy maker (receiver), not the distances between the ideal points of players. We interpret this as an argument in support of informational theories of legislative organizations.
A simulation study of traffic efficiency improvement based on Car-to-X communication

There are several promising applications for car-to-x communication that aim at the improvement of traffic efficiency. With the increasing maturity of car-to-x communication systems, insights into the impacts of these applications on vehicular traffic are required. In this paper, we present a simulation study of traffic efficiency improvements that can be obtained by the utilization of a merging assistance application ahead of a freeway lane drop. Our investigations are based on the traffic simulation tool AIMSUN. We connect the traffic simulator with a simulation model that implements the merging assistance application as well as the message exchange between vehicles and a roadside unit. Simulation results show significant traffic efficiency improvements indicated by travel time reductions of up to 30% in dense traffic under ideal conditions.
Development and Validation of a PCR-Based Enzyme-Linked Immunosorbent Assay with Urine for Use in Clinical Research Settings To Detect Trichomonas vaginalis in Women

ABSTRACT Trichomonas vaginalis infection is highly prevalent worldwide and is associated with poor birth outcomes and enhanced human immunodeficiency virus transmission. Traditional detection methods rely on microscopic examination of vaginal specimens (wet mount) and culture, which can be insensitive and time-consuming. More than 3,000 women attending two sexually transmitted disease clinics were enrolled in this cross-sectional study to evaluate urine-based PCR for detection of T. vaginalis using a combined reference standard of wet mount and culture from vaginal swab. The prevalence of trichomoniasis in the population was 16.7% (502 of 3,009 women) using the reference standard. PCR with urine combined with agarose gel-based detection was 66.9% sensitive and 98.3% specific compared to the reference standard. Detection of PCR products using an unlabeled enzyme-linked immunosorbent assay (ELISA) improved the sensitivity to 86.4%, but specificity fell to 86.1%. Using a digoxigenin-labeled ELISA for detection of amplified T. vaginalis DNA from urine, the sensitivity and specificity of the PCR improved to 90.8 and 93.4%, respectively, compared to wet mount or culture from vaginal swabs. For clinical research settings in which vaginal specimens are not available and culture conditions are not feasible, urine-based PCR-ELISA may be useful for the detection of trichomoniasis in women.
EARLY REPTILIAN EVOLUTION RE‐VIEWED

Most reptiles, living and fossil, can be arrayed in a small series of subclasses or superorders, clearly distinguishable from one another, and all, presumably, derived from the ancient "stem reptiles," the Cotylosauria. A customary type of classification, based originally on the nature of the temporal openings, was first fully developed by Williston (1925). It is now obvious that other features than the "key characters" of temporal structure must be taken into account, but, with necessary modifications, I have followed this system in successive editions of my "Vertebrate Paleontology" (1933, 1945, 1966) and in my "Osteology of the Reptiles" (1956). Apart from a few debatable points (such as whether all two-arched reptiles should be included in a single subclass Diapsida or divided into Archosauria and Lepidosauria), most recent writers have followed a similar "orthodox" pattern of reptilian classification and phylogeny. Two divergent systems, however, deserve serious consideration, since they have been proposed by major workers on fossil reptiles: Prof. D. M. S. Watson of University College, London, and Prof. F. von Huene of Tiibingen.
An A-RBAC mechanism for a multi-tenancy cloud environment

With the evolution of software technology, companies require more high-performance hardware to enhance their competitiveness. Cloud computing is the result of distributed computing and grid computing processes and is gradually being seen as the solution to the companies. Cloud computing can virtualizes existing software and hardware to reduce costs. Thus, companies only require high Internet bandwidth and devices to access cloud service on the Internet. This would decrease many overhead costs and the number of IT staff required. When many companies rent a cloud service simultaneously, this is called a multi-tenancy cloud service. However, how to access resource safely is important if adopt multi-tenancy cloud computing technology. The cloud computing environment is vulnerable to network-related attacks. This research improves the role-based access control authorization mechanism and combines it with attribute check mechanism to determine which tenant that user can access. The enhanced authorization can improve the safety of cloud computing services and protected the data privacy.