Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Adhesive Behaviour of Micron-sized Particles in Turbulent Flow: A Numerical Study Coupling the Discrete Element Method and Large Eddy Simulations

Small particles are commonly observed to stick to one another (typically denoted agglomerate) due to inter-particle attractive forces. When particles agglomerate their interaction with the surroundings is changed significantly. Particles with this behaviour are found in wide range of processes ranging from dust particles in space, that agglomerate to form early stages of planets, to soot particles emitted from various combustion processes on Earth that reduce the efficiency of various industrial processes by sticking to surfaces. Most particles influenced by inter-particle attractive forces have diameters ranging from dp = O(0.1 μm) to dp = O(10 μm). Due to their small size, experimental investigations are limited to single particles colliding with a surface under well-controlled conditions. When adhesive particles interact in a turbulent flow, tracking individual particles in time becomes close to impossible. Due to the difficulties with tracking adhesive particles experimentally, computational methods with varying level of complexity have been developed over the last decades. Recent development within computational methods, such as the Discrete Element Method (DEM), allow more aspects of the agglomeration process to be resolved directly based on the properties of the particles. Despite the increase in computational power in the recent years, simulating the interaction of thousands, millions or even billions particles remains limited by the computational power of modern computers. In this study, focus is first on how to analytically derive a criterion describing how to effectively speed up DEM simulations by altering the physical properties of the particles. For this purpose, simulations involving two particles colliding under various conditions are carried out to ensure the adhesive behaviour remains unchanged after applying the criterion. In conjunction with the criterion proposed, a relation describing the computational speedup is proposed. Secondly, focus is on applying the criterion to investigate how adhesive particles interact in a turbulent pipe flow by coupling Large Eddy Simulations (LES) of turbulent flow to the Discrete Element Method (DEM). Initially, simulations are done to verify the validity of the analytically-derived criterion. Next, simulations are done for a wide range of particle properties to get
Analysis of Aggregation Characteristics of Streaming Media Traffic

The analysis of aggregation characteristics of streaming media traffic provides a scientific basis for the general plan of Next Generation Broadcasting network. Based on the method of simulation, the streaming media traffic characteristics, self-similarity and aggregation delay time are discussed with different load scales and source processing strategies. The result shows that delay time of the aggregation processing is improved, because of the source classification strategy. And with the increasing of the aggregation scale self-similarity of the traffic has been weakened.
Mixed Integer Optimization for Layout Arrangement

Arranging geometric entities in a two-dimensional layout is a common task for most information visualization applications, where existing algorithms typically rely on heuristics to position shapes such as boxes or discs in a visual space. Geometric entities are used as a visual resource to convey information contained in data such as textual documents or videos and the challenge is to place objects with similar content close to each other while still avoiding overlap. In this work we present a novel mechanism to arrange rectangular boxes in a two-dimensional layout which copes with the two properties above, that is, it keeps similar object close and prevents overlap. In contrast to heuristic techniques, our approach relies on mixed integer quadratic programming, resulting in well structured arrangements which can be easily be tuned to take different forms. We show the effectiveness of our methodology through a comprehensive set of comparisons against state-of-art methods. Moreover, we employ the proposed technique in video data visualization, attesting its usefulness in a practical application.
Source Side Information Can Increase the Joint Source-Channel Coding Error Exponent

We study the joint source-channel coding (JSCC) error exponent for discrete memoryless source-channel systems with side information which is correlated to the transmitted source. Two cases are considered: (1) the side information is available only at the decoder; (2) the side information is available at both the encoder and decoder. We employ the method of types to establish a lower bound for the JSCC error exponent for each case. As a consequence, a JSCC theorem on the reliable transmissibility of the source over the channel is obtained. It is noted that the same JSCC theorem applies for both cases. For binary sources and symmetric channels, we derive a sufficient condition for which the side information at the decoder can strictly improve the JSCC error exponent. Numerical results show that side information can enlarge the region for reliable transmissibility and increase the JSCC error exponent for a wide class of source-channel parameters.
A copula‐based mixed Poisson model for bivariate recurrent events under event‐dependent censoring

In many chronic disease processes subjects are at risk of two or more types of events. We describe a bivariate mixed Poisson model in which a copula function is used to model the association between two gamma distributed random effects. The resulting model is a bivariate negative binomial process in which each type of event arises from a negative binomial process. Methods for parameter estimation are described for parametric and semiparametric models based on an EM algorithm. We also consider the issue of event‐dependent censoring based on one type of event, which arises when one event is sufficiently serious that its occurence may influence the decision of whether to withdraw a patient from a study. The asymptotic biases of estimators of rate and mean functions from naive marginal analyses are discussed, as well as associated treatment effects. Because the joint model is fit based on a likelihood, consistent estimates are obtained. Simulation studies are carried out to evaluate the empirical performance of the proposed estimators with independent and event‐dependent censoring and applications to a trial of breast cancer patients with skeletal metastases and a study of patients with chronic obstructive pulmonary disease illustrate the approach. Copyright © 2010 John Wiley & Sons, Ltd.
Warming increases the risk of civil war in Africa

Armed conflict within nations has had disastrous humanitarian consequences throughout much of the world. Here we undertake the first comprehensive examination of the potential impact of global climate change on armed conflict in sub-Saharan Africa. We find strong historical linkages between civil war and temperature in Africa, with warmer years leading to significant increases in the likelihood of war. When combined with climate model projections of future temperature trends, this historical response to temperature suggests a roughly 54% increase in armed conflict incidence by 2030, or an additional 393,000 battle deaths if future wars are as deadly as recent wars. Our results suggest an urgent need to reform African governments' and foreign aid donors' policies to deal with rising temperatures.
Compact UWB bandpass filter with improved upper-stopband performance using multiple-mode resonator

In this paper, a novel ultra-wideband (UWB) bandpass filter (BPF) with compact size and improved upper-stopband performance has been studied and designed using multiple-mode resonator (MMR). The MMR is formed by attaching three pairs of ring open stubs in shunt to a high impedance microstrip line. By simply adjusting the radius of the circles of the ring stubs, the resonant modes of the MMR can be roughly allocated within the 3.1-10.6 GHz UWB band while suppressing the spurious harmonics in the upper-stopband. In order to enhance the coupling degree, two interdigital coupled-lines are used in the input and output sides. Thus, a predicted UWB passband is realized. Meanwhile, the insertion loss is higher than 20.0 dB in the upper-stopband from 11.7 to 33.5 GHz. The design is successfully realized in theory and verified by full-wave EM-simulation.
Global expression profiling of murine MEN1‐associated tumors reveals a regulatory role for menin in transcription, cell cycle and chromatin remodelling

Although the identification of menin‐interacting partners and other evidence support a role for menin, the multiple endocrine neoplasia type 1 gene (MEN1) product, in regulating gene expression, little is known about the cellular pathways dysregulated by menin loss during tumorigenesis. The mouse models of MEN1 accurately mimic the human syndrome and provide an opportunity to assess the transcriptional effects of Men1 deletion in different endocrine tumor types to identify common pathway aberrations underlying tumorigenesis in MEN1‐affected tissues. We compared the global gene expression profiles of pituitary adenomas and pancreatic islet tumors with control tissues from wild‐type littermates. Amongst the 551 differentially expressed genes was significant over‐representation of genes associated with chromatin remodelling, transcription and cell cycling, including some genes known to encode menin‐binding partners, e.g., Rhox5 and Mll1. Consistent with increased cell‐cycle transition from G1 to S phase was an elevation of Cdc7 expression in the tumors, which was confirmed by qRT‐PCR using independent samples. In support of previous findings in islet tumors, we found down‐regulation of the cell‐cycle regulator, p18, in both the pancreatic islet and pituitary adenomas, suggesting that reduced p18 levels may be important for Men1‐related tumorigenesis in multiple tissues. Surprisingly, we identified increased p16 transcript in pancreatic islet and pituitary tumors. This was accompanied by increased cytoplasmic localization p16 protein in tumor cells. The specific genes and general pathways we have found to be commonly dysregulated in MEN1 tumors, provide a platform for determining their roles in endocrine tumorigenesis. © 2007 Wiley‐Liss, Inc.
Dynamic management of resources and workloads for RDBMS in cloud: a control-theoretic approach

As cloud computing environments become explosively popular, dealing with unpredictable changes, uncertainties, and disturbances in both systems and environments turns out to be one of the major challenges facing the concurrent computing industry. My research goal is to dynamically manage resources and workloads for RDBMS in cloud computing environments in order to achieve ``better performance but lower cost", i.e., better service level compliance but lower consumption of virtualized computing resource(s). Nowadays, although control theory offers a principled way to deal with the challenge based on feedback mechanisms, a controller is typically designed based on the system designer's domain knowledge and intuition instead of the behavior of the system being controlled. My research approach is based on the essence of control theory but transcends state-of-the-art control-theoretic approaches by leveraging interdisciplinary areas, especially from machine learning. While machine learning is often viewed merely as a toolbox that can be deployed for many data-centric problems, my research makes efforts to incorporate machine learning as a full-fledged engineering discipline into control-theoretic approaches for realizing my research goal. My PhD thesis work implements two solid systems by leveraging machine learning techniques, namely, ActiveSLA and SmartSLA. ActiveSLA is an automatic controller featuring risk assessment admission control to obtain the most profitable service-level compliance. SmartSLA is an automatic controller featuring cost-sensitive adaptation to achieve the lowest total cost. The experimental results show that both of the two systems outperform the state-of-the-art methods.
Efficacy and Tolerability of Clozapine versus Quetiapine in Treatment-resistant Schizophrenia

Objectives: To compare the efficacy and tolerability of clozapine and quetiapine in patients with treatment-resistant schizophrenia (TRS). Patients and Methods: In this prospective, randomized, open label study of 14 weeks, 53 patients with schizophrenia diagnosed as per ICD-10 and fulfilling the modified version of Conley and Kelly's criteria of TRS were randomly assigned to receive clozapine or quetiapine as per a computer-generated random table. After 2-weeks of dose-titration phase, doses were fixed at minimum therapeutic dose and subsequently adjusted according to the clinical improvement. All patients received dosage of respective drug in therapeutic range. 13 patients were lost to follow up. Treatment efficacy and side effects were evaluated with standardized rating scales. Results: Clozapine group (reduction in total score: mean=14.45, SD=10.39) had significantly greater reductions (P=0.004; CI=3.541-17.059) in the Positive and Negative Syndrome Scale (PANSS) total score, PANSS positive subscale and PANSS general psychopathology subscale at 14 weeks in comparison to the quetiapine group (reduction in total score: mean=4.15, SD=10.71). Significant reduction in PANSS negative subscale was seen with both drugs but no significant difference was present between the two drugs. At 14 weeks, 30% patients in clozapine group and 15% patients in quetiapine group showed response. Clozapine led to significantly greater side effects (P< 0.001, CI=2.241-6.059) on Glassgow Antipsychotic Side-effect Scale (GASS) than quetiapine. Conclusions: Clozapine was found to be more efficacious than quetiapine in patients with TRS but was associated with greater side effects. Both the drugs were found to be equally effective in reducing the negative symptoms.
Electron-vibration coupling constants in positively charged fullerene

Abstract Recent experiments have shown that C60 can be positively field doped. In that state, fullerene exhibits a higher resistivity and a higher superconducting temperature than the corresponding negatively doped state. A strong intramolecular hole–phonon coupling, connected with the Jahn–Teller effect of the isolated positive ion, is expected to be important for both properties, but the actual coupling strengths are so far unknown. Based on density functional calculations, we determine the linear couplings of the two ag six gg and eight hg vibrational modes to the Hu highest occupied molecular orbital level of the C60 molecule. The couplings predict a D5 distortion, and an Hu vibronic ground state for C60 +. They are also used to generate the dimensionless coupling constant λ which controls the superconductivity and the phonon contribution to the electrical resistivity in the crystalline phase. We find that λ is 1.4 times larger in positively charged C60 than in the negatively doped case. These results are discussed in the context of the available transport data and superconducting temperatures. The role of higher orbital degeneracy in superconductivity is also addressed.
An application of fuzzy DL-based semantic perception to soil container classification

Semantic perception and object labeling are key requirements for robots interacting with objects on a higher level. Symbolic annotation of objects allows the usage of planning algorithms for object interaction, for instance in a typical fetchand-carry scenario. In current research, perception is usually based on 3D scene reconstruction and geometric model matching, where trained features are matched with a 3D sample point cloud. In this work we propose a semantic perception method which is based on spatio-semantic features. These features are defined in a natural, symbolic way, such as geometry and spatial relation. In contrast to point-based model matching methods, a spatial ontology is used where objects are rather described how they "look like", similar to how a human would described unknown objects to another person. A fuzzy based reasoning approach matches perceivable features with a spatial ontology of the objects. The approach provides a method which is able to deal with senor noise and occlusions. Another advantage is that no training phase is needed in order to learn object features. The use-case of the proposed method is the detection of soil sample containers in an outdoor environment which have to be collected by a mobile robot. The approach is verified using real world experiments.
The LIA-Thales summarization system at DUC-2006

The LIA-Thales system is made of five different sentence selection systems and a fusion module. Among the five sentence selection systems used, two were originally developed for the Question-Answering task (QA) and three specifically built for DUC-2006. The outputs of the five systems are combined in a weighted graph where the cost functions integrate the votes given by the different systems to the sentences. The best path in this graph corresponds to the summary given by our system. Our experiments have shown that the fusion of the five systems always scores better on ROUGE and BE than each system alone. In the DUC-2006 evaluation, the LIA-Thales fusion system obtained very good results in the automatic evaluations and achieved good performance in human evaluations.
Comparison of dynamic susceptibility-weighted contrast-enhanced MR methods: recommendations for measuring relative cerebral blood volume in brain tumors.

PURPOSE To investigate whether estimates of relative cerebral blood volume (rCBV) in brain tumors, obtained by using dynamic susceptibility-weighted contrast material-enhanced magnetic resonance (MR) imaging vary with choice of data acquisition and postprocessing methods. MATERIALS AND METHODS Four acquisition methods were used to collect data in 22 high-grade glioma patients, with informed written consent under HIPAA-compliant guidelines approved by the institutional review board. During bolus administration of a standard single dose of gadolinium-based contrast agent (0.1 mmol per kilogram of body weight), one of three acquisition methods was used: gradient-echo (GRE) echo-planar imaging (echo time [TE], 30 msec; flip angle, 90 degrees ; n = 10), small-flip-angle GRE echo-planar imaging (TE, 54 msec; flip angle, 35 degrees ; n = 7), or dual-echo GRE spiral-out imaging (TE, 3.3 and 30 msec; flip angle, 72 degrees ; n = 5). Next, GRE echo-planar imaging (TE, 30 msec; flip angle, 90 degrees ; n = 22) was used to collect data during administration of a second dose of contrast agent (0.2 mmol/kg). Subsequently, six methods of analysis were used to calculate rCBV. Mean rCBV values from whole tumor, tumor hot spots, and contralateral brain were normalized to mean rCBV in normal-appearing white matter. RESULTS Friedman two-way analysis of variance and Kruskal-Wallis one-way analysis of variance results indicated that qualitative rCBV values were dependent on acquisition and postprocessing methods for both tumor and contralateral brain. By using the nonparametric Mann-Whitney test, a consistently positive (greater than zero) tumor-contralateral brain rCBV ratio resulted when either the preload-postprocessing correction approach or dual-echo acquisition approach (P < .008 for both methods) was used. CONCLUSION The dependence of tumor rCBV on the choice of acquisition and postprocessing methods is caused by their varying sensitivities to T1 and T2 and/or T2* leakage effects. The preload-correction approach and dual-echo acquisition approach are the most robust choices for the evaluation of brain tumors when the possibility of contrast agent extravasation exists.
Genome Sequence of Streptococcus phocae subsp. salmonis Strain C-4T, Isolated from Atlantic Salmon (Salmo salar)

ABSTRACT Streptococcus phocae subsp. salmonis is a fish pathogen that has an important impact on the Chilean salmon industry. Here, we report the genome sequence of the type strain C-4T isolated from Atlantic salmon (Salmo salar), showing a number of interesting features and genes related to its possible virulence factors.
Hopelessness, depression and social support with end of life Turkish cancer patients.

BACKGROUND This study was performed to evaluate relationships between different demographic variables and hopelessness and depression in end of life Turkish cancer patients. This study was a descriptive survey with repeated measures conducted a university hospital in the city of Erzurum, in the eastern part of Turkey. The study enrolled 216 patients undergoing palliative treatment at the hospital. MATERIALS AND METHODS Data were collected using questionnaires (demographic questionnaire, Beck Hopelessness Scale (BHS), Beck Depression Scale (BDS) and analyzed for demographic and disease-related variable effects on hopelessness and depression. RESULTS Th hopelessness score was significantly high in female, illiterate, married, and living in rural areas cancer patients. Both hopelessness and depression scores were significantly higher with longer disease duration, receiving radiotherapy treatment, and having metastatic disease. CONCLUSIONS These findings demonstrate the coexistence of the physical, psychological, and cognitive problems faced by patients with cancer. Nurses can conduct brief screening assessments to identify patients with probable distress and and psychosocial support, as well as referrals to support services.
Animal Models of Diabetic Macrovascular Complications: Key Players in the Development of New Therapeutic Approaches

Diabetes mellitus is a lifelong, incapacitating metabolic disease associated with chronic macrovascular complications (coronary heart disease, stroke, and peripheral vascular disease) and microvascular disorders leading to damage of the kidneys (nephropathy) and eyes (retinopathy). Based on the current trends, the rising prevalence of diabetes worldwide will lead to increased cardiovascular morbidity and mortality. Therefore, novel means to prevent and treat these complications are needed. Under the auspices of the IMI (Innovative Medicines Initiative), the SUMMIT (SUrrogate markers for Micro- and Macrovascular hard end points for Innovative diabetes Tools) consortium is working on the development of novel animal models that better replicate vascular complications of diabetes and on the characterization of the available models. In the past years, with the high level of genomic information available and more advanced molecular tools, a very large number of models has been created. Selecting the right model for a specific study is not a trivial task and will have an impact on the study results and their interpretation. This review gathers information on the available experimental animal models of diabetic macrovascular complications and evaluates their pros and cons for research purposes as well as for drug development.