Miracle-dz/UniFAR-FTUs huggingface dataset:
Oncogenic Action of Secreted Phospholipase A2 in Prostate Cancer

Mortality from prostate cancer is associated with progression of tumors to androgen-independent growth and metastasis. Eicosanoid products of both the cyclooxygenase (COX) and lipoxygenase (LOX) pathways are important mediators of the proliferation of prostate cancer cells in culture and regulate tumor vascularization and metastasis in animal models. Pharmacologic agents that block either COX or LOX products effectively reduce the size of prostate cancer xenografts. Phospholipase A2 (PLA2) enzymes regulate the provision of arachidonic acid to both COX- and LOX-derived eicosanoids, and a secreted form of the enzyme (sPLA2-IIA) is elevated in prostate cancer tissues. Here, we show by immunohistochemistry, in patients receiving androgen ablation therapy, that sPLA2-IIA remains elevated in remaining cancer cells relative to benign glands after treatment. Furthermore, sPLA2-IIA expression seen in benign glands is substantially decreased after androgen depletion, whereas cytosolic PLA2-α (cPLA2-α) levels are unchanged. sPLA2-IIA mRNA expression is detectable and inducible by androgen (0.01–10 nmol/L) in the androgen-sensitive cell line LNCaP, and exogenous addition of sPLA2-IIA (1–100 nmol/L), but not an inactive sPLA2-IIA mutant (H48Q), results in a dose-dependent increase in cell numbers or the fraction of cells in G2-M phase, which is inhibited by sPLA2-IIA-selective inhibitors. The effect of exogenous sPLA2-IIA can also be blocked by inhibition of cPLA2-α, suggesting a role for cPLA2-α in mediating sPLA2-IIΑ action. sPLA2-IIA inhibitors suppressed basal proliferation in LNCaP cells and in the androgen-independent, sPLA2-positive cell line PC3 but not in the sPLA2-IIA-negative androgen-independent cell line DU145. Established PC3 xenograft tumors grew more slowly in mice treated with sPLA2-IIA inhibitors than those treated with saline only. The PLA2 enzymes, and sPLA2-IIA in particular, thus represent important targets for the treatment of sPLA2-IIA-positive androgen-independent prostate cancer.
Loving-Kindness Meditation to Target Affect in Mood Disorders: A Proof-of-Concept Study

Conventional treatments for mood disorders primarily focus on reducing negative affect, but little on enhancing positive affect. Loving-kindness meditation (LKM) is a traditional meditation practice directly oriented toward enhancing unconditional and positive emotional states of kindness towards oneself and others. We report here two independent and uncontrolled studies carried out at different centers, one in Boston, USA (n = 10), and one in Frankfurt, Germany (n = 8), to examine the potential therapeutic utility of a brief LKM group intervention for symptoms of dysthymia and depression. Results at both centers suggest that LKM was associated with large-sized effects on self-reported symptoms of depression (d = 3.33 and 1.90), negative affect (d = 1.98 and 0.92), and positive affect (d = 1.63 and 0.94). Large effects were also found for clinician-reported changes in depression, rumination and specific positive emotions, and moderate effects for changes in adaptive emotion regulation strategies. The qualitative data analyses provide additional support for the potential clinical utility of the intervention. This proof-of-concept evaluation of LKM as a clinical strategy warrants further investigation.
Community Dynamics of Ectomycorrhizal Fungi Following the Vision Fire

Many people that read this chapter may be aware of mammals, birds, and maybe even plant species that are common at Point Reyes, and may have witnessed or have been aware of the ways that these organisms responded to the Vision fi re of 1995. Few will be familiar with fungal species at Point Reyes, and even fewer may have noticed their response to the fi re. This is un for tu nate, be cause fungi play many critical roles in structuring and maintaining plant (and therefore also animal) communities at Point Reyes. It is un der stand able, however, because even those of us that study fungi for a living know less about them than plant or animal biologists typically know about their or gan isms. There are several reasons for our collective ignorance. Fungi can be diffi cult to identify, so reliable species records are rare. For most of their lives, fungi are microscopic and hidden in soil or plant parts; this makes it diffi cult to observe their basic life histories and ecology. Finally, relatively few people study fungi, especially when one considers that there are roughly six species of fungi for every plant species on the planet (Hawksworth 1990). The good news is that there is much to learn, and the Vision fi re provided an exceptional opportunity to do exactly that.
Experimental Study of Charge Neutralization at the Surface of Granular Layers of Insulating Materials

Neutralization of the residual electric charge is often a prerequisite for the optimal processing of insulating granules, thin films, or textile media. The aim of this paper is to evaluate the factors that might affect the ability of ac corona discharge to eliminate the charge at the surface of polyethylene granular materials. The effectiveness of the neutralization is evaluated from the measurement of surface potential distribution before and after exposing the samples to a flux of bipolar ions. The corona discharge was generated by energizing at various high-voltage (HV) levels (16, 20, and 25 kV) and frequencies (1, 20, 50, 100, 200, and 400 Hz) a wire-type corona electrode suspended at 30 mm above the granular layer disposed at the surface of a grounded plate. The results show that the neutralization efficiency can be improved by increasing the frequency of the HV. An optimal value voltage can be experimentally determined for the case of practical interest when the frequency of the power supply is 50 Hz. In the same case, successive exposures to the ac corona discharge may enhance the efficiency of the neutralization.
Phylogenetic dependency networks: inferring patterns of adaptation in hiv

Populations adapt to their environment through a process of natural selection. By studying this process, one can gain insight into the specific functions of adaptive traits that provide an advantage in certain environments. HIV has proven to be remarkably adept at adaptation. So much so that the virus quickly adapts to each individual who is infected, effectively nullifying the immune response of most patients. By identifying the specific adaptations HIV employs against the immune system, it may be possible to identify vaccine targets that reduce HIV's capacity to successfully adapt. This dissertation introduces the Phylogenetic Dependency Network (PDN) for the identification of adaptive traits and the environments in which they arise. The PDN is a directed graphical model in which nodes represent measurable traits of the population and the environment and arcs represent probabilistic dependencies among traits. The probability component of the PDN consists of a model of adaptive evolution in which each population trait adapts to a set of predictors, traits to which it is connected in the PDN. The structure of the PDN is identified through a model selection approach and can be interpreted as an estimate of which traits directly interact. We introduce a class of probabilistic adaptive evolution models called conditional adaptation models. These models assume that each trait has evolved independent of all other traits in the PDN until it reached the current environment, at which point the predictors act to influence adaptation of the trait. One of the key benefits of this approach over traditional methods is the ability to simultaneously model multiple interactions. Existing approaches are typically constrained to consider the evolutionary interaction of two traits at a time. In complex environments in which each trait interacts with many other traits, this constrained view of adaptation blurs the distinction of which traits are truly interacting and which are only indirectly correlated. By modeling these interactions using conditional adaptation models, we are able to accurately capture dense networks of interactions. We apply our PDN approach to study adaptation of HIV to the human cellular immune response, identifying a large set of HIV adaptations that consistently arise in patients with similar immune genetics. These adaptations often take the form of multiple mutations spanning large regions of HIV proteins and indicate the presence of preferred patterns of adaptation. Although these adaptation networks are quite complex, the presence of these preferred adaptation patterns suggest weak points in viral adaptation that may be exploited by future vaccines.
Including students with disabilities in Education for All: lessons from Ethiopia

ABSTRACT This article addresses the inclusion of students with disabilities into the Education for All and Sustainable Development Goals agenda through a case study of Ethiopia, a country aiming to promote inclusive education amidst rapidly rising school enrolments. The article begins with a review of debates concerning inclusive education in the Global South and the strategy taken by Ethiopia. It then examines how inclusive education is currently being implemented drawing on recent fieldwork at rural and urban schools in Tigray province. Through interviews, participant observation, and focus groups, we found that teachers and school administrators are generally in favour of mainstreaming children with disabilities into ‘normal’ schools. However, insufficient training of teachers and itinerant teachers along with shortages of teaching materials and resources present major challenges to addressing special education needs.
Interactive Extraction and Re-Design of Sweep Geometries

We introduce two interactive extraction mod- ules that can t the parameters of generalized sweeps to large, unstructured meshes for immediate, high-level, detail-preserving modication. These modules represent two extremes in a spectrum of parameterized shapes: rotational sweeps dened by a few global parameters, and progressive sweeps forming generalized cylinders with many slowly varying local parameters. Both mod- ules are initialized and controlled by the user draw- ing a few strokes onto the displayed original model. We demonstrate the system on various shapes, rang- ing from clean, mechanical geometries to organic forms with intricate surface details.
Swimming patterns and the activity of identified equilibrium interneurones in the shore crab, Carcinus maenas

Swimming behaviour in crabs is electromyographically described in relation to the involvement of the discharge of the equilibrium interneurones. In intact crabs or crabs with only the fifth legs remaining, swimming consists of cyclic out-of-phase sculling movements of the last pair of pereiopods (P5). In these legs, all muscles are involved within a single swimming cycle; antagonistic muscles burst alternately, as do bilateral pairs of muscles. Bursting in the four proximal muscles ensures the appendage rotation while distal muscles set the scull in the best propulsive position. Swimming evoked by tilt in the sagittal plane starts with symmetrical remotor activity before alternate bursting begins. Tilt in the plane of a statocyst vertical canal leads to asymmetrical onset of remotor bursting, starting with the muscle contralateral to the stimulated statocyst. Tilt in defined vertical planes elicits the discharge of identified equilibrium interneurones. Of these, interneurones C and D are active before and during swimming. Sensory inputs from the statocysts and/or the leg proprioceptors to these interneurones are both adequate to drive swimming. Moreover, our experiments suggest that cell C activity is strongly involved in the onset and the maintenance of swimming behaviour. Swimming can be altered by autotomy of legs on one side performed a few days in advance, and leads to the same turning tendency as does contralateral cutting of a connective. This may be due to modification in the strength of the remaining central connections to compensate for those lost. Note: To whom reprint requests should be addressed.
The Oxygen Abundance in the Inner H II Regions of M101: Implications for the Calibration of Strong-Line Metallicity Indicators

I present deep spectroscopy of four H II regions in the inner, metal-rich zone of the spiral galaxy M101 obtained with the LRIS spectrograph at the Keck telescope. From the analysis of the collisionally excited lines in two of the target H II regions, H1013 and H493, I have obtained oxygen abundances 12 + log(O/H) = 8.52 and 12 + log(O/H) = 8.74, respectively. These measurements extend the determination of the oxygen abundance gradient of M101 via the direct method to only 3 kpc from the center. The intensity of the C II λ4267 line in H1013 leads to a carbon abundance 12 + log(C/H) = 8.66, corresponding to nearly twice the solar value. From a comparison of the continuum temperature derived from the Balmer discontinuity, T(Bac) = 5000 K, and the line temperature derived from [O III] λ4363/λ5007, T[O III] = 7700 K, an average temperature T0 = 5500 K and a mean square temperature fluctuation t2 = 0.06 have been derived. Accounting for the spatial inhomogeneity in temperature raises the oxygen abundance obtained from the oxygen auroral lines to 12 + log(O/H) = 8.93. These findings are discussed in the context of the calibration of strong-line metallicity indicators, in particular of the upper branch of R23. There is no evidence for the strong abundance biases arising from temperature gradients predicted theoretically for metal-rich H II regions.
Volume-Based Cut-and-Paste Editing for Early Design Phases

Since product concepts are frequently changed in the early stage of design, the creation of its rough models is useful for communication among the design team. In this paper, we propose modeling operations based on a volume-based cut-and-paste method for generating rough 3D models using existing 3D models. Cut-and-paste editing extracts a characteristic feature from a source model and copies it to a target model. Our method allows pasting a wide variety of features that may have overhangs and handles, while most existing methods cannot manage such shapes. To realize such a volume-based cut-and-paste technique, this paper introduces a new method that consists of mesh segmentation and surface/volume fitting. In our method, a feature region and its surrounding area are separated from the user-specified area, and they are used for generating a parametric volume that involves the feature region. In feature pasting, parametric volumes are deformed and pasted to the target model and then features inside the volume are adaptively deformed and pasted to the target. On the basis of this cut-and-paste method, we propose modeling operations that enable feature registration, feature removal, feature pasting, and texture pasting. These operations were implemented and demonstrated using example models. The result shows our operations can effectively generate new models by removing and reusing partial shapes in existing models.Copyright © 2004 by ASME
Practical affine types

Alms is a general-purpose programming language that supports practical affine types. To offer the expressiveness of Girard's linear logic while keeping the type system light and convenient, Alms uses expressive kinds that minimize notation while maximizing polymorphism between affine and unlimited types. A key feature of Alms is the ability to introduce abstract affine types via ML-style signature ascription. In Alms, an interface can impose stiffer resource usage restrictions than the principal usage restrictions of its implementation. This form of sealing allows the type system to naturally and directly express a variety of resource management protocols from special-purpose type systems. We present two pieces of evidence to demonstrate the validity of our design goals. First, we introduce a prototype implementation of Alms and discuss our experience programming in the language. Second, we establish the soundness of the core language. We also use the core model to prove a principal kinding theorem.
Ontology and automatic code generation on modeling and simulation

In this paper we present a new approach for using semantic web technologies in modeling and simulation. In recent years ontologies have been used popularly in many fields to represent and structure their concepts. This work is an attempt to create a specific ontology for the process oriented discrete event simulation domain. The ontology instances represent the model instances. This instance described in XML format and then transformed to another form that is used to generate the simulation code via XSLT rules. The code is generated according to the open source library Japrosim. The objective of this work is to enhance interoperability and automation of the transition from the ontology to the code execution.
Extending SRT for parallel applications in tiled-CMP architectures

Reliability has become a first-class consideration issue for architects along with performance and energy-efficiency. The increasing scaling technology and subsequent supply voltage reductions are increasing the susceptibility of architectures to soft errors. However, mechanisms to achieve full coverage to errors usually degrade performance in an unacceptable way for the majority of common users. Simultaneous and Redundantly Threaded (SRT) [13] is a fault tolerant architecture in which pairs of threads in a SMT core redundantly execute the same program instructions. In this paper, we study the under-explored architectural support of SRT to reliably execute shared-memory applications. We show how atomic operations induce a serialization point between master and slave threads. This bottleneck has an impact of 34% in execution speed for several parallel scientific benchmarks. We propose an alternative mechanism in which the L1 cache is updated by master's stores before verification reducing the overhead up to 21%. Our approach also outperforms other recent proposals such as DCC with a decrease of 8% in execution speed.
VisBricks: Multiform Visualization of Large, Inhomogeneous Data

Large volumes of real-world data often exhibit inhomogeneities: vertically in the form of correlated or independent dimensions and horizontally in the form of clustered or scattered data items. In essence, these inhomogeneities form the patterns in the data that researchers are trying to find and understand. Sophisticated statistical methods are available to reveal these patterns, however, the visualization of their outcomes is mostly still performed in a one-view-fits-all manner, In contrast, our novel visualization approach, VisBricks, acknowledges the inhomogeneity of the data and the need for different visualizations that suit the individual characteristics of the different data subsets. The overall visualization of the entire data set is patched together from smaller visualizations, there is one VisBrick for each cluster in each group of interdependent dimensions. Whereas the total impression of all VisBricks together gives a comprehensive high-level overview of the different groups of data, each VisBrick independently shows the details of the group of data it represents, State-of-the-art brushing and visual linking between all VisBricks furthermore allows the comparison of the groupings and the distribution of data items among them. In this paper, we introduce the VisBricks visualization concept, discuss its design rationale and implementation, and demonstrate its usefulness by applying it to a use case from the field of biomedicine.
A Hybrid Genetic Algorithm for Multi-Depot and Periodic Vehicle Routing Problems

We propose an algorithmic framework that successfully addresses three vehicle routing problems: the multi-depot VRP, the periodic VRP, and the multi-depot periodic VRP with heterogeneous capacitated vehicles and constrained route duration. The meta-heuristic combines the exploration breadth of population-based evolutionary search, the aggressive-improvement capabilities of neighborhood-based meta-heuristics, and advanced population-diversity management schemes. Extensive computational experiments show that, the method performs impressively, in terms of both solution quality and computational efficiency. It particular, it either identifies the best known solutions, including the optimal ones, or identifies new best solutions for all currently available benchmark instances for the three problem classes.
Macular pigment, visual function, and macular disease among subjects with Alzheimer's disease: an exploratory study.

BACKGROUND The macula (central retina) contains a yellow pigment, comprising the dietary carotenoids lutein (L), zeaxanthin (Z), and meso-zeaxanthin, known as macular pigment (MP). The concentrations of MP's constituent carotenoids in retina and brain tissue correlate, and there is a biologically-plausible rationale, supported by emerging evidence, that MP's constituent carotenoids are also important for cognitive function. OBJECTIVE To investigate if patients with Alzheimer's disease (AD) are comparable to controls in terms of MP and visual function. METHODS 36 patients with moderate AD and 33 controls with the same age range participated. MP was measured using dual-wavelength autofluorescence (Heidelberg Spectralis®); cognitive function was assessed using a battery of cognition tests (including Cambridge Neuropsychological Test Automated Battery). Visual function was recorded by measuring best corrected visual acuity (BCVA) and contrast sensitivity (CS). Serum L and Z concentrations (by HPLC) and age-related macular degeneration (AMD, by retinal examination) status were also assessed. RESULTS In the AD group, central MP (i.e., at 0.23°) and MP volume were significantly lower than the control group (p < 0.001 for both), as were measures of BCVA, CS, and serum L and Z concentrations (p < 0.05, for all). CONCLUSION AD patients were observed to exhibit significantly less MP, lower serum concentrations of L and Z, poorer vision, and a higher occurrence of AMD when compared to control subjects. A clinical trial in AD patients designed to investigate the impact of macular carotenoid supplementation with respect to MP, visual function, and cognitive function is merited.
Partially-Forgetful Memories : Relaxing Memory Guard-bands for Approximate Computing

While the memory subsystem is already a major contributor to energy consumption of computing platforms, the guard banding required for masking the effects of ever increasing manufacturing variations in memories imposes even more energy overhead. In this paper, we explore how PartiallyForgetful Memories can be used by exploiting the intrinsic tolerance of a vast class of applications to some level of error for relaxing this guard-banding in memories. We discuss the challenges to be addressed and introduce Relaxed Cache as an exemplar to address these challenges for partiallyforgetful SRAM caches. Preliminary results show how adapting guard-bands to application characteristics can help th e system save significant amount of cache leakage energy (up to 74%) while still generating acceptable quality results.