Miracle-dz/UniFAR-FTUs huggingface dataset:
Association between cytotoxic T-lymphocyte associated protein 4 gene +49 A/G polymorphism and chronic infection with hepatitis B virus: A meta-analysis

Objective This meta-analysis determined the relationship between polymorphisms of the cytotoxic T-lymphocyte-associated protein 4 (CTLA4) gene and hepatitis B virus (HBV) clearance in chronic hepatitis B. Methods Published studies reporting associations between CTLA4 gene +49A/G polymorphisms and chronic HBV infection were reviewed. Odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the risk of persistent HBV according to genotype. Results Six studies, involving 1076 chronic HBV patients and 1294 controls, were included. The risk of persistent HBV in patients with a +49 GG/AG genotype decreased significantly compared with the AA genotype (OR 0.65; 95% CI 0.52, 0.82). The variant G allele was negatively associated with chronic HBV infection versus the A allele (OR 0.77; 95% CI 0.68, 0.88). When stratifying by type of study control, a significantly decreased risk was associated with CTLA4+49 variant genotypes (AG and GG) in both spontaneous recovery control group and healthy control group. Conclusions Findings of this meta-analysis suggest that A at position +49 of the CTLA4 gene may significantly increase the risk of persistent HBV infection, whereas G at position +49 may positively influence virus clearance.
Genetic diversity and population structure of an extremely endangered species: the world's largest Rhododendron

This is the first study of the genetic diversity and structure of the big tree rhododendron, Rhododendron protistum var. giganteum, which is a highly endangered species with only two known endemic populations in a small area in the southern part of Yunnan Province in China. We detected moderate to high genetic diversity at the species level, but low genetic differentiation between the two extant populations. These results suggest that some rare and endangered species are able to maintain high levels of genetic diversity even at small population sizes.
Status and Coordination in Organizations ∗ Wing

Firms can motivate workers by offering them social status. Much of the literature argues that a rise in status is a powerful work incentive while ignoring its impact on coordination. However, when workers need to collaborate while having individual vested interests, too large a difference in status distorts how workers coordinate, i.e., one worker compromises too much with respect to his most preferred choice and the other compromises too little. On the contrary, small status differentials can be profitable when status confers power and cost advantages.
Saving the world from bad beans: deployment-time confinement checking

The Enterprise JavaBeans (EJB) framework requires developers to preserve architectural integrity constraints when writing EJB components. Breaking these constraints allows components to violate the transaction protocol, bypass security mechanisms, disable object persistence, and be susceptible to malicious attacks from other EJBs. We present an object confinement discipline that allows static verification of components' integrity as they are deployed into an EJB server. The confinement rules are simple for developers to understand, require no annotation to the code of EJB components, and can be efficiently enforced in existing EJB servers.
REBEL and TDC: Two embedded test structures for on-chip measurements of within-die path delay variations

As feature printability becomes more challenging in advanced technology nodes, measuring and characterizing process variation effects on delay and power is becoming increasingly important. In this paper, we present two embedded test structures (ETS) for carrying out path delay measurement in actual product designs. Of the two structures proposed here, one is designed to be incorporated into a customer's scan structures, augmenting selected functional units with the ability to perform accurate path delay measurements. We refer to this ETS as REBEL (regional delay behavior). It is designed to leverage the existing scan chain as a means of reducing area overhead and performance impact. For cases in which very high resolution of delay measurements is required, a second standalone structure is proposed which we refer to as TDC for time-to-digital converter. Beyond characterizing process variations, these ETSs can also be used for design debug, detection of hardware Trojans and small delay defects and as physical unclonable functions.
Crosstalk via the NF-κ B Signaling System

The NF-κB family of transcription factors consists of fifteen possible dimers whose activity is controlled by a family of inhibitor proteins, known as IκBs. A variety of cellular stimuli, many of them transduced by members of the TNFR superfamily, induce degradation of IκBs to activate an overlapping subset of NF-κB dimers. However, generation and stimulus-responsive activation of NF-κB dimers are intimately linked via various cross-regulatory mechanisms that allow crosstalk between different signaling pathways through the NF-κB signaling system. In this review, we summarize these mechanisms and discuss physiological and pathological consequences of crosstalk between apparently distinct inflammatory and developmental signals. We argue that a systems approach will be valuable for understanding questions of specificity and emergent properties of highly networked cellular signaling systems.
The Vacuolar Manganese Transporter MTP8 Determines Tolerance to Iron Deficiency-Induced Chlorosis in Arabidopsis1[OPEN]

The cation diffusion facilitator MTP8 transports manganese into root vacuoles of iron-deficient plants and thereby prevents the inhibition of iron deficiency-induced ferric chelate reductase by manganese. Iron (Fe) deficiency is a widespread nutritional disorder on calcareous soils. To identify genes involved in the Fe deficiency response, Arabidopsis (Arabidopsis thaliana) transfer DNA insertion lines were screened on a high-pH medium with low Fe availability. This approach identified METAL TOLERANCE PROTEIN8 (MTP8), a member of the Cation Diffusion Facilitator family, as a critical determinant for the tolerance to Fe deficiency-induced chlorosis, also on soil substrate. Subcellular localization to the tonoplast, complementation of a manganese (Mn)-sensitive Saccharomyces cerevisiae yeast strain, and Mn sensitivity of mtp8 knockout mutants characterized the protein as a vacuolar Mn transporter suitable to prevent plant cells from Mn toxicity. MTP8 expression was strongly induced on low-Fe as well as high-Mn medium, which were both strictly dependent on the transcription factor FIT, indicating that high-Mn stress induces Fe deficiency. mtp8 mutants were only hypersensitive to Fe deficiency when Mn was present in the medium, which further suggested an Mn-specific role of MTP8 during Fe limitation. Under those conditions, mtp8 mutants not only translocated more Mn to the shoot than did wild-type plants but suffered in particular from critically low Fe concentrations and, hence, Fe chlorosis, although the transcriptional Fe deficiency response was up-regulated more strongly in mtp8. The diminished uptake of Fe from Mn-containing low-Fe medium by mtp8 mutants was caused by an impaired ability to boost the ferric chelate reductase activity, which is an essential process in Fe acquisition. These findings provide a mechanistic explanation for the long-known interference of Mn in Fe nutrition and define the molecular processes by which plants alleviate this antagonism.
Exploring Objective Causal Inference in Case-Noncase Studies under the Rubin Causal Model

investigated via simulation, and compared to those of logistic and probit regression. Chapter 3 focuses on the re-analysis of a subset of data from a published article, Karkouti et al. (2006). We investigate whether PrepDA and logistic regression, when applied to case-noncase data, can generate estimates that are concordant with those from the causal analysis of prospectively collected data. We introduce tools for covariate balance assessment across multiple imputed datasets. We explore the potential for analyst bias with logistic regression, when said method is used to analyze case-noncase data. In Chapter 4 we discuss our technology’s advantages over, and drawbacks as compared to, traditional approaches. iv
Antidiabetic Effects of Chamomile Flowers Extract in Obese Mice through Transcriptional Stimulation of Nutrient Sensors of the Peroxisome Proliferator-Activated Receptor (PPAR) Family

Given the significant increases in the incidence of metabolic diseases, efficient strategies for preventing and treating of these common disorders are urgently needed. This includes the development of phytopharmaceutical products or functional foods to prevent or cure metabolic diseases. Plant extracts from edible biomaterial provide a potential resource of structurally diverse molecules that can synergistically interfere with complex disorders. In this study we describe the safe application of ethanolic chamomile (Matricaria recutita) flowers extract (CFE) for the treatment and prevention of type 2 diabetes and associated disorders. We show in vitro that this extract activates in particular nuclear receptor peroxisome proliferator-activated receptor gamma (PPARγ) and its isotypes. In a cellular context, in human primary adipocytes CFE administration (300 µg/ml) led to specific expression of target genes of PPARγ, whereas in human hepatocytes CFE-induced we detected expression changes of genes that were regulated by PPARα. In vivo treatment of insulin-resistant high-fat diet (HFD)-fed C57BL/6 mice with CFE (200 mg/kg/d) for 6 weeks considerably reduced insulin resistance, glucose intolerance, plasma triacylglycerol, non-esterified fatty acids (NEFA) and LDL/VLDL cholesterol. Co-feeding of lean C57BL/6 mice a HFD with 200 mg/kg/d CFE for 20 weeks showed effective prevention of fatty liver formation and hepatic inflammation, indicating additionally hepatoprotective effects of the extract. Moreover, CFE treatment did not reveal side effects, which have otherwise been associated with strong synthetic PPAR-targeting molecules, such as weight gain, liver disorders, hemodilution or bone cell turnover. Taken together, modulation of PPARs and other factors by chamomile flowers extract has the potential to prevent or treat type 2 diabetes and related disorders.
P1I-9 Passive 2.45 GHz TDMA based Multi-Sensor Wireless Temperature Monitoring System: Results and Design Considerations

This paper presents a TDMA (time division multiple access) based wireless temperature monitoring system using 2.45 GHz passive surface acoustic wave (SAW) delay line sensors. A three-step resolution refinement scheme using a combined delay and phase evaluation is proposed. Using a transmission power of 2 dBm (1.59 mW) a temperature accuracy of 0.19 K and 0.1 K(6sigma), were achieved for an interrogation distance of 1.4 m, and 1.3 m, respectively. The sensor design is discussed using experimental results concerning the relationship between the SNR (signal to noise ratio) of the sensors and the accuracy in time delay or phase measurement. Also, the direct electron beam writing on chemically-reduced (black) LiNbO3 is described
C21. Single image motion deblurring using Genetic Algorithms

One of the key problems of restoring a degraded image from motion blur is the estimation of the unknown blur filter from a single input blurred image. Many blind deconvolution methods typically assume frequency-domain constraints on images, simplified parametric forms for the motion path during camera shake or use multiple input images. The paper proposes an algorithm for removing motion blur from a single input blurred image using Genetic Algorithms. Genetic Algorithms are applied in science and engineering as adaptive algorithms for optimizing practical problems. Also recent research in natural image statistics is exploited, which shows that photographs of natural scenes typically obey heavy-tailed distribution. Both linear and non-linear motion blur are handled. Experiments on a wide data set of standard images degraded with different kernels of different sizes demonstrate the efficiency of the proposed approach especially in small blur lengths.
Super learning for anomaly detection in cellular networks

The ever-growing population of smartphone» connected to mobile networks is changing the cellular traffic ecosystem. The traffic volumes and patterns generated by smartphone apps pose complex challenges to cellular network operators, particularly in terms of detection and diagnosis of network anomalies caused by specific apps. The high-dimensionality of network data provided by current network monitoring systems opens the door to the application of machine learning approaches to improve the detection and classification of network anomalies, but this higher dimensionality comes with an extra data processing overhead. In addition, critical network monitoring applications such as the detection of anomalies require fast mechanisms for on-line analysis of thousands of events per second, as well as efficient techniques for off-line analysis of massive historical data. In this paper we explore the application of big data analytics and big data platforms to the automatic detection of anomalies in mobile networks. We consider ensemble, multi-combined machine learning models to enhance anomaly detection, following a particularly promising model known as Super Learning. Super-learning is an ensemble learning approach which performs asymptotically as well as the best possible weighted combination of multiple learning algorithms, providing a very powerful detection approach. We implement and test different super-learning models on top of Big-DAMA, a big data analytics framework for network monitoring. We test the proposed solution on the detection of traffic anomalies in operational cellular networks, and compare it to other traditional ensemble learning approaches such as bagging and boosting. Results indicate that our approach outperforms traditional ones.
MODELLING AND CONTROL STRATEGY OF ROBOTIC YO-YO

In the paper we address a problem of controlling an oscillating motion with a robot. As the object we have selected a yo-yo. Yo-yo is a toy made of two discs connected with a short thin axle, which can be moved up and down by moving a string tied to the axle. Although it is very easy to play with yo-yo for a human, designing a control system for a robot is quite a challenge. We present a simplified model of a yo-yo which is intended for control analysis and design. Our model has one degree-of-freedom and the behaviour at the end of the string is modelled as an impact. Next we discuss the control strategy and present a control method which allows playing the yo-yo at selected top height.
From synaptically localized to volume transmission by nitric oxide

Nitric oxide (NO) functions widely as a transmitter/diffusible second messenger in the central nervous system, exerting physiological effects in target cells by binding to specialized guanylyl cyclase‐coupled receptors, resulting in cGMP generation. Despite having many context‐dependent physiological roles and being implicated in numerous disease states, there has been a lack of clarity about the ways that NO operates at the cellular and subcellular levels. Recently, several approaches have been used to try to gain a more concrete, quantitative understanding of this unique signalling pathway. These approaches have included analysing the kinetics of NO receptor function, real‐time imaging of cellular NO signal transduction in target cells, and the use of ultrasensitive detector cells to record NO as it is being generated from native sources in brain tissue. The current picture is that, when formed in a synapse, NO is likely to act only very locally, probably mostly within the confines of that synapse, and to exist only in picomolar concentrations. Nevertheless, closely neighbouring synapses may also be within reach, raising the possibility of synaptic crosstalk. By engaging its enzyme‐coupled receptors, the low NO concentrations are able to stimulate physiological (submicromolar) increases in cGMP concentration in an activity‐dependent manner. When many NO‐emitting neurones or synapses are active simultaneously in a tissue region, NO can act more like a volume transmitter to influence, and perhaps coordinate, the behaviour of cells within that region, irrespective of their identity and anatomical connectivity.
Uplink/downlink duality in massive MIMO systems with hardware impairments

In this paper, we provide a new framework for the uplink/downlink duality in single-cell massive multiple-input multiple-output (MIMO) systems suffering from residual hardware impairments (HWIs) at the base station and the user terminals. Using the proposed duality, complex downlink optimization problems can be converted to equivalent dual uplink problems, which are easier to solve. As an example, we apply the proposed uplink/downlink duality to derive an HWI aware minimum mean square error (HWIA-MMSE) precoder, which minimizes the sum mean square error under a sum power constraint in a single-cell massive MIMO system with residual HWIs. Thereby, we use results from random matrix theory to derive an asymptotic expression for the downlink power allocation for large numbers of antennas, which only depends on the channel statistics and not on the individual channel realizations. Analytical results for the asymptotic achievable sum rate of the proposed HWIA-MMSE precoder for a large number of BS antennas are also provided. Our simulation and analytical results show that the proposed HWIA-MMSE precoder achieves a higher sum rate than the conventional regularized zero-forcing precoder for moderately large numbers of base station antennas.
Lebenszielinterventionen in der Neurorehabilitation

Erworbene Hirnschadigungen konnen neben akuten Beeintrachtigungen durch eine Fulle von langwierigen Krankheitsfolgen gekennzeichnet sein. Diese sind interindividuell sehr verschieden und stehen in einem engen Bezug zu klinischen Variablen, zum pramorbiden Status der Betroffenen und zur Unterstutzung nach dem Schadigungseintritt. Einschrankungen in der Erreichbarkeit wichtiger Lebensziele stellen ein hochideographisches Abbild solcher Krankheitsfolgen dar. Zum anderen bieten sie sich aber auch als ein geeigneter Rahmen und zugleich auch als Erfolgsmasstab einer individuell zugeschnittenen neuropsychologischen Rehabilitation an. Auf der Basis empirischer Befunde, die querschnittlich bei neurologischen Patienten erhoben wurden und zweier zentraler Modelle aus unterschiedlichen Forschungsrichtungen werden in dieser Arbeit Vorschlage fur Lebenszielinterventionen gemacht. Diese sollen klassisch neuropsychologische Therapieansatze nicht ersetzen sondern individualisieren und so deren subjektive Sinnhaftigkeit un.
Average Drift Analysis and Population Scalability

This paper aims to study how the population size affects the computation time of evolutionary algorithms (EAs) in a rigorous way. The computation time of EAs can be measured by either the number of generations (hitting time) or the number of fitness evaluations (running time) to find an optimal solution. Population scalability is the ratio of the expected hitting time between a benchmark algorithm and an algorithm using a larger population size. Average drift analysis is introduced to compare the expected hitting time of two algorithms and to estimate lower and upper bounds on the population scalability. Several intuitive beliefs are rigorously analyzed. It is proven that: 1) using a population sometimes increases rather than decreases the expected hitting time; 2) using a population cannot shorten the expected running time of any elitist EA on any unimodal function on the time-fitness landscape, however, this statement is not true in terms of the distance-based fitness landscape; and 3) using a population cannot always reduce the expected running time on deceptive functions, which depends on whether the benchmark algorithm uses elitist selection or random selection.
Growth of the Stress-Bearing and Shape-Maintaining Murein Sacculus of Escherichia coli

SUMMARY To withstand the high intracellular pressure, the cell wall of most bacteria is stabilized by a unique cross-linked biopolymer called murein or peptidoglycan. It is made of glycan strands [poly-(GlcNAc-MurNAc)], which are linked by short peptides to form a covalently closed net. Completely surrounding the cell, the murein represents a kind of bacterial exoskeleton known as the murein sacculus. Not only does the sacculus endow bacteria with mechanical stability, but in addition it maintains the specific shape of the cell. Enlargement and division of the murein sacculus is a prerequisite for growth of the bacterium. Two groups of enzymes, hydrolases and synthases, have to cooperate to allow the insertion of new subunits into the murein net. The action of these enzymes must be well coordinated to guarantee growth of the stress-bearing sacculus without risking bacteriolysis. Protein-protein interaction studies suggest that this is accomplished by the formation of a multienzyme complex, a murein-synthesizing machinery combining murein hydrolases and synthases. Enlargement of both the multilayered murein of gram-positive and the thin, single-layered murein of gram-negative bacteria seems to follow an inside-to-outside growth strategy. New material is hooked in a relaxed state underneath the stress-bearing sacculus before it becomes inserted upon cleavage of covalent bonds in the layer(s) under tension. A model is presented that postulates that maintenance of bacterial shape is achieved by the enzyme complex copying the preexisting murein sacculus that plays the role of a template.
Semantic feedback for hybrid recommendations in Recommendz

In this paper we discuss the Recommendz recommender system. This domain-independent system combines the advantages of collaborative and content-based filtering in a novel way. By allowing users to provide feedback not only about an item as a whole, but also properties of an item that motivated their opinion, increased performance seems to be achieved. The features used to describe items are specified by the users of the system rather than predetermined using manual knowledge-engineering. We describe a method for combining descriptive features and simple ratings, and provide a performance analysis.