Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of soil and Trifolium repens (white clover) on the fate of estrogen

In this study, we investigated the behavior of estrogens in the rhizosphere of white clover (Trifolium repens, clover hereafter) with two different pot tests, using soil and agar as growth media. In a pot test using agar spiked with estrogen, the estrogen concentration in the agar with clover decreased to non-detectable levels within one month, while in the agar without clover, 60% of initially added estrogen remained after one month. The half-lives of estrone (E1) and 17β -estradiol (E2) in the agar with clover were 2.4–3.8 and 13.2 d, respectively. The dissipation of E1 followed first-order rate law, while that of E2 fitted a zero-order reaction, indicating that they had different mechanisms of dissipation from agar. In the soil pot test, the behavior of E1 and E2 was not influenced by clover. An initial rapid decrease in the amount of estrogen extracted by methanol/acetic acid was followed by persistence for 1–3 months, regardless of presence of clover. Moreover, in three weeks E1 and E2 were only partly degraded by microbes extracted from the soil used in the pot test. In this study, abiotic degradation of estrogens and sorption of estrogen to soil, rather than the effects of soil microbes and clover, contributed to the initial rapid dissipation of estrogens in the soil. However, the results of the agar pot test suggested that vegetation such as clover may significantly contribute to removal of estrogens when estrogens in aqueous phase are discharged with surface runoff and preferential flow after heavy rain in agricultural fields, or when present in soils with low estrogen sorptivity.
Three-dimensional Imaging of Paint Layers and Paint Substructures with Synchrotron Radiation Computed μ-laminography

Abstract Information on the creation of a painting lies usually hidden under the surface. A painting's substructure may include the underdrawing, underpainting, modifications to the initial setup (or pentimenti), and sometimes even abandoned compositions. Traditionally, the study of these characteristics relies on penetrative, two-dimensional imaging techniques (infrared reflectography, x-ray radiography) complemented with selected paint crosssections. The limitations of this approach are twofold. First, it can be difficult to combine data from cross sections with two-dimensional images, because of poor redundancy of both methods. Second, cross sections involve destructive sampling of the paint layer. This paper introduces synchrotron radiation computed micro-laminography in the study of paintings. The technique allows for three-dimensional imaging of the paint stratigraphy in a nondestructive manner, enabling the imaging of paint layers, their interfaces, the ground, and carrier. The technique is demonstrated on a test painting, and its interest to curators and conservators of painting collections is discussed.
Relational cost analysis

Establishing quantitative bounds on the execution cost of programs is essential in many areas of computer science such as complexity analysis, compiler optimizations, security and privacy. Techniques based on program analysis, type systems and abstract interpretation are well-studied, but methods for analyzing how the execution costs of two programs compare to each other have not received attention. Naively combining the worst and best case execution costs of the two programs does not work well in many cases because such analysis forgets the similarities between the programs or the inputs. In this work, we propose a relational cost analysis technique that is capable of establishing precise bounds on the difference in the execution cost of two programs by making use of relational properties of programs and inputs. We develop , a refinement type and effect system for a higher-order functional language with recursion and subtyping. The key novelty of our technique is the combination of relational refinements with two modes of typing-relational typing for reasoning about similar computations/inputs and unary typing for reasoning about unrelated computations/inputs. This combination allows us to analyze the execution cost difference of two programs more precisely than a naive non-relational approach. We prove our type system sound using a semantic model based on step-indexed unary and binary logical relations accounting for non-relational and relational reasoning principles with their respective costs. We demonstrate the precision and generality of our technique through examples.
Ornament size and colour as alternative strategies for effective communication in gliding lizards

Sexual ornamentation needs to be conspicuous to be effective in attracting potential mates and defending territories and indeed, a multitude of ways exists to achieve this. Two principal mechanisms for increasing conspicuousness are to increase the ornament's colour or brightness contrast against the background and to increase the size of the ornament. We assessed the relationship between the colour and size of the dewlap, a large extendible throat‐fan, across a range of species of gliding lizards (Agamidae; genus Draco) from Malaysia and the Philippines. We found a negative relationship across species between colour contrast against the background and dewlap size in males, but not in females, suggesting that males of different species use increasing colour contrast and dewlap size as alternative strategies for effective communication. Male dewlap size also increases with increasing sexual size dimorphism, and dewlap colour and brightness contrast increase with increasing sexual dichromatism in colour and brightness, respectively, suggesting that sexual selection may act on both dewlap size and colour. We further found evidence that relative predation intensity, as measured from predator attacks on models placed in the field, may play a role in the choice of strategy (high chromatic contrast or large dewlap area) a species employs. More broadly, these results highlight that each component in a signal (such as colour or size) may be influenced by different selection pressures and that by assessing components individually, we can gain a greater understanding of the evolution of signal diversity.
Decision Theory, the Situation Calculus and Conditional Plans

This paper shows how to combine decision theory and logical representations of actions in a manner that seems natural for both. In particular, we assume an axiomatization of the domain in the situationcalculus, using what is essentially Reiter’s solution to the frame problem, in terms of the completion of the axioms defining the state change. Uncertainty is handled using the independent choice logic, which allows for independent choices and a logic program that gives the consequences of the choices. The same framework handles both frame and ramification axioms. As part of the consequences are a specification of the utility of (final) states, and how sensors depend on the state. The logic is used to reason about agents; agents themselves evaluate conditional plans, similar to the GOLOG programming language. Within the logic, we can define the expected utility of a conditional plan, based on the axiomatization of the actions, the sensors and the utility. Sensors can be noisy and actions can be stochastic. The planning problem is to find the plan with the highest expected utility. This representation is related to recent structured representations for partially observable Markov decision processes (POMDPs); here we use stochastic situationcalculus rules to specify the state transition function and the reward/value function. We show that with stochastic frame axioms, action representations in probabilistic STRIPS are exponentially larger than using the representation proposed here.
Personal semantic and episodic autobiographical memories in Korsakoff syndrome: A comparison of interview methods.

OBJECTIVE The temporal gradient in patients with Korsakoff's syndrome has been of particular interest in the literature, as many studies have found evidence for a steep temporal gradient, but others have observed more uniform remote memory impairment across all past time periods. Inconsistencies might be the result of the nature of remote memory impairment under study (i.e., nonpersonal or autobiographical memory) and of methodological differences in the examination of remote memory loss. The aim of this study was to examine whether differences between autobiographical memory interview (AMI) and autobiographical interview (AI) procedures influence the presence of a temporal gradient in semantic and episodic autobiographical memory in Korsakoff patients. METHOD The procedure used in the present study combined the AMI and AI into one study session. We compared the performance of 20 patients with Korsakoff's syndrome and 27 healthy controls. First, participants were asked to recall knowledge from different life periods. Second, participants were asked to recall memories from five life periods. Thirdly, participants were asked to rate their subjective experience of each event recalled on a 5-point scale. Finally, we analyzed the findings in terms of all the memories recalled versus the first memory from each life-period only. RESULTS Both the AMI and the AI showed a temporally graded retrograde amnesia in the Korsakoff patients for personal semantic and episodic autobiographical memories. The pattern of amnesia in Korsakoff patients was not affected by examining only one event per life-period. Subjective ratings of recalled memories were largely comparable between the groups. CONCLUSIONS The findings were generally consistent across the AMI and AI. Varying the number of events did not affect the pattern of the gradient. Hence, the temporal gradient in Korsakoff patients is not an artefact of either the AMI or the AI method.
Transglutaminase 2 accelerates neuroinflammation in amyotrophic lateral sclerosis through interaction with misfolded superoxide dismutase 1

Although the aberrant assembly of mutant superoxide dismutase 1 (mSOD1) is implicated in the pathogenesis of familial amyotrophic lateral sclerosis (ALS), the molecular basis of superoxide dismutase 1 (SOD1) oligomerization remains undetermined. We investigated the roles of transglutaminase 2 (TG2), an endogenous cross‐linker in mSOD1‐linked ALS. TG2 interacted preferentially with mSOD1 and promoted its oligomerization in transfected cells. Purified TG2 directly oligomerized recombinant mutant SOD1 and the apo‐form of the wild‐type SOD1 proteins in a calcium‐dependent manner, indicating that misfolded SOD1 is a substrate of TG2. Moreover, the non‐cell‐autonomous effect of extracellular TG2 on the neuroinflammation was suggested, since the TG2‐mediated soluble SOD1 oligomers induced tumor necrosis factor‐α, interleukin‐1β, and nitric oxide in microglial BV2 cells. TG2 was up‐regulated in the spinal cord of pre‐symptomatic G93A SOD1 transgenic mice and in the hypoglossal nuclei of mice suffering nerve ligation. Furthermore, inhibition of spinal TG2 by cystamine significantly delayed the progression and reduced SOD1 oligomers and microglial activation. These results indicate a novel role of TG2 in SOD1 oligomer‐mediated neuroinflammation, as well as in the involvement in the intracellular aggregation of misfolded SOD1 in ALS.
A Robust Grouping Proof Protocol for RFID EPC C1G2 Tags

Several grouping proof protocols for RFID systems have been proposed over the years but they are either found to be vulnerable to certain attacks or do not comply with the EPC class-1 gen-2 (C1G2) standard because they use hash functions or other complex encryption schemes. Among other requirements, synchronization of keys, simultaneity, dependence, detecting illegitimate tags, eliminating unwanted tag processing, and denial-of-proof attacks have not been fully addressed by many. Our protocol addresses these important gaps by taking a holistic approach to grouping proofs and provides forward security, which is an open research issue. The protocol is based on simple (XOR) encryption and 128-bit pseudorandom number generators, operations that can be easily implemented on low-cost passive tags. Thus, our protocol enables large-scale implementations and achieves EPC C1G2 compliance while meeting the security requirements.
Health Promotion in Cervical Cancer Prevention among the Yakama Indian Women of the Wa’shat Longhouse

The purpose of this 3-year study was to gain a greater understanding of the importance of the Wa’Shat Longhouse religion to the design of a culturally appropriate health promotion (cervical cancer prevention) program with the Yakama Indian people of eastern Washington. This descriptive study involved interviews with 10 Wa’Shat members, observations, and participant observations of 30 community ceremonial activities. The framework of health promotion planning guided the investigation. We found that (a) program goals needed to be holistic and wellness oriented, (b) teaching methods needed to include circular symbols, and (c) intervention strategies needed to be linked to the natural patterns of communication of the Wa’Shat Longhouse and to involve elders. Storytelling, talking circles, and use of role models were all found to be important teaching methods. We confirm previous perspectives on the importance of religion, provide greater depth in this understanding and outline implications for transcultural nursing practice.
Detection of enterotoxigenic Staphylococcus aureus isolates in domestic dairy products

Background and objectives Staphylococcus aureusis a one of THE most frequent causes of food poisoning (FP) in dairy products. The main etiologic agents of FP are staphylococcal enterotoxins (SE). There are different types of SE; types A (SEA) and B (SEB) are the most clinically important enterotoxins. Traditional dairy products are still produced in small batches and sold by some vendors without a permit from the Ministry of Health. This study focuses on the molecular and serological detection of enterotoxigenic Staphylococcus aureus SEA and SEB genes and its products, respectively from samples of such traditional products. Materials and Methods 100 samples from dairy products were produced under sterile conditions via traditional methods and were transported to the laboratory. The samples were cultured and identified by routine bacteriological methods. The isolated bacteria were evaluated by PCR tests for detection of the genes encoding SEA and SEB. Subsequently, the ability of these strains to produce enterotoxin was examined by Sac's culture method and was confirmed by Sigel Radial Immounodiffussion (SRID). Results The results indicated that 32% of the dairy products were contaminated by S. aureus (cream 18%, cheese 10%, milk 4%). The PCR results showed that 15.6% of the S. aureus isolates possessed the SEA gene, 9.3% had the SEB gene, and 6.2% possessed both genes. The evaluation of enterotoxin production indicated that 80% of SEA and 33% of SEB genes were expressed. Conclusion Enterotoxins SEA and SEB are heat stable and consequently; heating has no effect on dairy products contaminated by entertoxins. Subsequently, gastritis may occur within several hours after consumption. Our findings suggest that PCR is a rapid, sensitive, specific, and inexpensive method for detecting SE and can replace the traditional assays.
Multi-source Transfer Learning with Convolutional Neural Networks for Lung Pattern Analysis

Early diagnosis of interstitial lung diseases is crucial for their treatment, but even experienced physicians find it difficult, as their clinical manifestations are similar. In order to assist with the diagnosis, computer-aided diagnosis (CAD) systems have been developed. These commonly rely on a fixed scale classifier that scans CT images, recognizes textural lung patterns and generates a map of pathologies. In a previous study, we proposed a method for classifying lung tissue patterns using a deep convolutional neural network (CNN), with an architecture designed for the specific problem. In this study, we present an improved method for training the proposed network by transferring knowledge from the similar domain of general texture classification. Six publicly available texture databases are used to pretrain networks with the proposed architecture, which are then fine-tuned on the lung tissue data. The resulting CNNs are combined in an ensemble and their fused knowledge is compressed back to a network with the original architecture. The proposed approach resulted in an absolute increase of about 2% in the performance of the proposed CNN. The results demonstrate the potential of transfer learning in the field of medical image analysis, indicate the textural nature of the problem and show that the method used for training a network can be as important as designing its architecture.
SAMBO and SAMBOdtf Results for the Ontology Alignment Evaluation Initiative 2008

This article describes a base system for ontology alignment, SAMBO, and an extension, SAMBOdtf. We present their results for the benchmark, anatomy and FAO tasks in the 2008 Ontology Alignment Evaluation Initiative. For the benchmark and FAO tasks SAMBO uses a strategy based on string matching as well as the use of a thesaurus. It obtains good results in many cases. For the anatomy task SAMBO uses a combination of string matching and the use of domain knowledge. This combination performed well in former evaluations using other anatomy ontologies. SAMBOdtf uses the same strategies but, in addition, uses an advanced filtering technique that augments recall while maintaining a high precision.
The Centre for Market and Public Organisation Why Economics Is Good for Your Health. 2004 Royal Economic Society Public Lecture Why Economics Is Good for Your Health. 2004 Royal Economic Society Public Lecture

The principal aim of the CMPO is to develop understanding of the design of activities within the public sector, on the boundary of the state and within recently privatised entities with the objective of developing research in, and assessing and informing policy toward, these activities. Abstract In this paper, I examine the contribution that economics can make to our understanding of key issues in health and health care. In the first part of the paper, I argue that economics can bring valuable insights into the world of over-eating and present recent economic theories that argue that the root cause of the increase in obesity lies in technological change. Technological change, in terms of the kind of work we do, the agricultural production revolution and the major cost reductions in food processing and distribution have all contributed to weight gain. This hypothesis is illustrated by data from the USA. In the second part, I argue that understanding incentives is the key to understanding the behaviour of suppliers of health care, explaining for example, why health staff 'fiddle the figures' to meet government targets and why doctors will respond to financial payments.
Pioglitazone Enhances Mitochondrial Biogenesis and Ribosomal Protein Biosynthesis in Skeletal Muscle in Polycystic Ovary Syndrome

Insulin resistance is a common metabolic abnormality in women with PCOS and leads to an elevated risk of type 2 diabetes. Studies have shown that thiazolidinediones (TZDs) improve metabolic disturbances in PCOS patients. We hypothesized that the effect of TZDs in PCOS is, in part, mediated by changes in the transcriptional profile of muscle favoring insulin sensitivity. Using Affymetrix microarrays, we examined the effect of pioglitazone (30 mg/day for 16 weeks) on gene expression in skeletal muscle of 10 obese women with PCOS metabolically characterized by a euglycemic-hyperinsulinemic clamp. Moreover, we explored gene expression changes between these PCOS patients before treatment and 13 healthy women. Treatment with pioglitazone improved insulin-stimulated glucose metabolism and plasma adiponectin, and reduced fasting serum insulin (all P<0.05). Global pathway analysis using Gene Map Annotator and Pathway Profiler (GenMAPP 2.1) and Gene Set Enrichment Analysis (GSEA 2.0.1) revealed a significant upregulation of genes representing mitochondrial oxidative phosphorylation (OXPHOS), ribosomal proteins, mRNA processing reactome, translation factors, and proteasome degradation in PCOS after pioglitazone therapy. Quantitative real-time PCR suggested that upregulation of OXPHOS genes was mediated by an increase in PGC-1α expression (P<0.05). Pretreatment expression of genes representing OXPHOS and ribosomal proteins was down-regulated in PCOS patients compared to healthy women. These data indicate that pioglitazone therapy restores insulin sensitivity, in part, by a coordinated upregulation of genes involved in mitochondrial OXPHOS and ribosomal protein biosynthesis in muscle in PCOS. These transcriptional effects of pioglitazone may contribute to prevent the onset of type 2 diabetes in these women.
Considering spatial and temporal scale in landscape‐genetic studies of gene flow

Landscape features exist at multiple spatial and temporal scales, and these naturally affect spatial genetic structure and our ability to make inferences about gene flow. This article discusses how decisions about sampling of genotypes (including choices about analytical methods and genetic markers) should be driven by the scale of spatial genetic structure, the time frame that landscape features have existed in their current state, and all aspects of a species’ life history. Researchers should use caution when making inferences about gene flow, especially when the spatial extent of the study area is limited. The scale of sampling of the landscape introduces different features that may affect gene flow. Sampling grain should be smaller than the average home‐range size or dispersal distance of the study organism and, for raster data, existing research suggests that simplifying the thematic resolution into discrete classes may result in low power to detect effects on gene flow. Therefore, the methods used to characterize the landscape between sampling sites may be a primary determinant for the spatial scale at which analytical results are applicable, and the use of only one sampling scale for a particular statistical method may lead researchers to overlook important factors affecting gene flow. The particular analytical technique used to correlate landscape data and genetic data may also influence results; common landscape‐genetic methods may not be suitable for all study systems, particularly when the rate of landscape change is faster than can be resolved by common molecular markers.
Learning Universal Computations with Spikes

Providing the neurobiological basis of information processing in higher animals, spiking neural networks must be able to learn a variety of complicated computations, including the generation of appropriate, possibly delayed reactions to inputs and the self-sustained generation of complex activity patterns, e.g. for locomotion. Many such computations require previous building of intrinsic world models. Here we show how spiking neural networks may solve these different tasks. Firstly, we derive constraints under which classes of spiking neural networks lend themselves to substrates of powerful general purpose computing. The networks contain dendritic or synaptic nonlinearities and have a constrained connectivity. We then combine such networks with learning rules for outputs or recurrent connections. We show that this allows to learn even difficult benchmark tasks such as the self-sustained generation of desired low-dimensional chaotic dynamics or memory-dependent computations. Furthermore, we show how spiking networks can build models of external world systems and use the acquired knowledge to control them.