Miracle-dz/UniFAR-FTUs huggingface dataset:
Antioxidative Role of Hatikana (Leea macrophylla Roxb.) Partially Improves the Hepatic Damage Induced by CCl4 in Wistar Albino Rats

This research investigated the protective role of Leea macrophylla extract on CCl4-induced acute liver injury in rats. Different fractions of Leea macrophylla (Roxb.) crude extract were subjected to analysis for antioxidative effects. Rats were randomly divided into four groups as normal control, hepatic control, and reference control (silymarin) group and treatment group. Evaluations were made for the effects of the fractions on serum enzymes and biochemical parameters of CCl4-induced albino rat. Histopathological screening was also performed to evaluate the changes of liver tissue before and after treatment. Different fractions of Leea macrophylla showed very potent 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging effect, FeCl3 reducing effect, superoxide scavenging effect, and iron chelating effect. Carbon tetrachloride induction increased the level of serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALP) and other biochemical parameters such as lipid profiles, total protein, and CK-MB. In contrast, treatment of Leea macrophylla reduced the serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALP) activities as well as biochemical parameters activities. L. macrophylla partially restored the lipid profiles, total protein, and CK-MB. Histopathology showed the treated liver towards restoration. Results evidenced that L. macrophylla can be prospective source of hepatic management in liver injury.
Sisters in arms: case study of the experiences of women warriors in the United States military

v Chapter 1 – Introduction . 1 Statement of the Problem . 5 Significance of the Study . 6 Purpose of the Study. 7 Questions Guiding the Inquiry . 8 Conceptual Assumptions . 9 Conceptual Framework . 11 Definitions of Major Terms . 13 Scope and Delimitation of the Study . 14 Narrative Outline of the Dissertation . 15 Chapter 2 – Literature Review . 16 Introduction . 16 Women in Combat . 16 Theoretical Framework . 21 Standpoint Epistemology . 21 Gender Role . 22 Androgyny . 27 Standpoint . 28 Gender Stereotypes . 29 Negative Stereotypes of Women Warriors . 29 Issues Affecting Women Warriors . 32 Chapter 3 – Design and Methodology . 37 Introduction . 37 Design of the Study . 38 Participants . 39 Instruments . 40 Interview . 42 Data Collection Procedure . 44 Research Design and Verification Procedure . 44 About the Researcher . 45 Peer Debriefing . 56 ii External Auditing . 56 Member Checking . 57 Data Analysis . 58 Chapter 4 Results . 60 Case Studies . 60 Amijah.61 Cassandra . 70 Janora . 83 Wilma . 95 Krista . 108 Alice . 121 Carolyn . 132 Jeanne . 156 Jackie.170 Chapter 5 Summary and Conclusions . 187 Summary . 188 Statement of the Problem . 188 Methodology . 189 Findings.190 Interview Observations . 204 Unexpected Outcomes . 209 Expected Outcomes . 211 Implications for Civilian Society . 213 Implications for Military . 214 Limitations . 214 Conclusions . 216 Recommendation for Future Research . 217 References . 219 Appendices . 226 Appendix A: Recruiting Letter for Study . 227 Appendix B: Selection Criteria for Study . 228 Appendix C: Letter to Participants . 229 Appendix D: Informed Consent to Participate in Study . 230 Appendix E: Auditor Background Information . 233 Appendix F: Letter of Attestation . 234 About the Author . End Page
Microsomal monooxygenase as a multienzyme system: the role of P450-P450 interactions

Introduction: There is increasing evidence of physical interactions (association) among cytochromes P450 in the membranes of the endoplasmic reticulum. Functional consequences of these interactions are often underestimated. Areas covered: This article provides a comprehensive overview of available experimental material regarding P450-P450 interactions. Special emphasis is given to the interactions between different P450 species and to the functional consequences of homo- and heterooligomerization. Expert opinion: Recent advances provide conclusive evidence for a substantial degree of P450 oligomerization in membranes. Interactions between different P450 species resulting in the formation of mixed oligomers with altered activity and substrate specificity have been demonstrated clearly. There are important indications that oligomerization impedes electron flow to a fraction of the P450 population, which renders some P450 species nonfunctional. Functional consequences of P450-P450 interactions make the integrated properties of the microsomal monooxygenase remarkably different from a simple summation of the properties of the individual P450 species. This complexity compromises the predictive power of the current in vitro models of drug metabolism and warrants an urgent need for development of new model systems that consider the interactions of multiple P450 species.
A dynamic voltage scaled microprocessor system

A microprocessor system is presented in which the supply voltage and clock frequency can be dynamically varied so that the system can deliver high throughput when required while significantly extending battery life during the low speed periods. The system consists of a dc-dc switching regulator, an ARM V4 microprocessor with a 16-kB cache, a bank of 64-kB SRAM ICs, and an I/O interface IC. The four custom chips were fabricated in a standard 0.6-/spl mu/m 3-metal CMOS process. The system can dynamically vary the supply voltage from 1.2 to 3.8 V in less than 70 /spl mu/s. This provides a throughput range of 6-85 MIPS with an energy consumption of 0.54-5.6 mW/MIP yielding an effective energy efficiency as high as 26200 MIPS/W.
Numerical Analysis/Partial Differential Equations Solving Maxwell equations in 3D prismatic domains

In this Note, we introduce the Fourier Singular Complement Method, for solving Maxwell equations in a 3D prismatic domain. The numerical implementation of this method provides a continuous approximation of the electromagnetic field. It can be applied to the computation of propagating and evanescent modes in prismatic stub filters, thus generalizing 2D approaches.
The Long Noncoding RNA MEG3 Is Downregulated and Inversely Associated with VEGF Levels in Osteoarthritis

Osteoarthritis (OA) is becoming a major public health problem in China, especially considering the increase in average life expectancy of the population. Thus, enhanced understanding of the molecular changes associated with OA is urgently needed to develop more effective strategies for the diagnosis and treatment of this debilitating disease. LncRNAs play an important role in the processes of bone and cartilage development. Maternally expressed gene 3 (MEG3) is a maternally expressed lncRNA and may function as a tumor suppressor by inhibiting angiogenesis. OA is closely associated with angiogenesis and the inhibition of angiogenesis presents a novel therapeutic approach to reduce inflammation and pain in OA. In this study, we detected the mRNA expression of MEG3 and VEGF in articular cartilage samples from 20 OA patients and 10 healthy volunteers by real-time RT-PCR. VEGF protein is detected by ELISA in cartilage samples. The results show that human MEG3 is significantly downregulated in OA patients compared to normal cartilage samples. However, higher levels of VEGF mRNA and protein are found in OA compared to the control. Moreover, MEG3 levels are inversely associated with VEGF levels, suggesting that MEG3 may be involved in OA development through the regulation of angiogenesis.
Evidence for a pervasive ‘idling-mode’ activity template in flying and pedestrian insects

Understanding the complex movement patterns of animals in natural environments is a key objective of ‘movement ecology’. Complexity results from behavioural responses to external stimuli but can also arise spontaneously in their absence. Drawing on theoretical arguments about decision-making circuitry, we predict that the spontaneous patterns will be scale-free and universal, being independent of taxon and mode of locomotion. To test this hypothesis, we examined the activity patterns of the European honeybee, and multiple species of noctuid moth, tethered to flight mills and exposed to minimal external cues. We also reanalysed pre-existing data for Drosophila flies walking in featureless environments. Across these species, we found evidence of common scale-invariant properties in their movement patterns; pause and movement durations were typically power law distributed over a range of scales and characterized by exponents close to 3/2. Our analyses are suggestive of the presence of a pervasive scale-invariant template for locomotion which, when acted on by environmental cues, produces the movements with characteristic scales observed in nature. Our results indicate that scale-finite complexity as embodied, for instance, in correlated random walk models, may be the result of environmental cues overriding innate behaviour, and that scale-free movements may be intrinsic and not limited to ‘blind’ foragers as previously thought.
Real-Time Monitoring of Multicast Group Information

SUMMARY This paper presents a method to monitor information of a large-sized multicast group that can follow the group’s dynamics in realtime while avoiding feedback implosion by using probabilistic polling. In particular, this paper improves the probabilistic-polling-based approach by deriving a reference mean value as the reference control value for the number of expected feedback from the properties of a binomial estimation model. As a result, our method adaptively changes its estimation parameters depending on the feedback from receivers in order to achieve a fast estimate time with high accuracy, while preventing the possible occurrence of feedback implosion. Our experimental implementation and evaluation on PlanetLab showed that the proposed method effectively controls the number of feedback and accurately estimates the size of a dynamic multicast
Named Entity Recognition in Chinese News Comments on the Web

News comment is a new text genre in the Web 2.0 era. Many people often write comments to express their opinions about recent news events or topics after they read news articles. Because news comments are freely written without checking, they are very different from formal news texts. In particular, named entities in news comments are usually composed of some wrongly written words, informal abbreviations or aliases, which brings great difficulties for machine detection and understanding. This paper addresses the task of named entity recognition in Chinese news comments on the Web. We propose to leverage the entity information in the referred news article to improve named entity recognition in the news comments. Three different schemes are investigated to find useful entities in the news article for new feature generation in the CRFs model. Finally, a dictionary-based correction step is employed to further improve the results. We manually labelled a benchmark dataset with 60 pieces of news and 6000 comments downloaded from a popular Chinese news portal – www.sina. com.cn. The experimental results on the dataset show that our method is effective for this special task.
DHT Extension of m-Cloud -- Scalable and Distributed Privacy Preserving Statistical Computation on Public Cloud

In the age of IoT (Internet of Things), tens of billions sensors or devices will be connected to cloud services. Although cloud environment is suitable for incredibly growing IoT services because of elasticity, scalability and efficiency for collecting and analyzing such data, protecting privacy on public cloud is a big issue. We proposed m-cloud, a distributed computation mechanism on multiple and independent public cloud environment. The mechanism enables to calculate various statistical indices from a large number of sensor data while it reduces the risk of revealing privacy information. We also propose an extension of the m-cloud computation mechanism so that it provides high scalability for infinitely increasing number of IoT devices by applying DHT (Distributed Hash Table) technique.
The effect of altruistic tendency on fairness in third-party punishment

Third-party punishment, as an altruistic behavior, was found to relate to inequity aversion in previous research. Previous researchers have found that altruistic tendencies, as an individual difference, can affect resource division. Here, using the event-related potential (ERP) technique and a third-party punishment of dictator game paradigm, we explored third-party punishments in high and low altruists and recorded their EEG data. Behavioral results showed high altruists (vs. low altruists) were more likely to punish the dictators in unfair offers. ERP results revealed that patterns of medial frontal negativity (MFN) were modulated by unfairness. For high altruists, high unfair offers (90:10) elicited a larger MFN than medium unfair offers (70:30) and fair offers (50:50). By contrast, for low altruists, fair offers elicited larger MFN while high unfair offers caused the minimal MFN. It is suggested that the altruistic tendency effect influences fairness consideration in the early stage of evaluation. Moreover, the results provide further neuroscience evidence for inequity aversion.
Error-prone DnaE2 Balances the Genome Mutation Rates in Myxococcus xanthus DK1622

dnaE is an alpha subunit of the tripartite protein complex of DNA polymerase III that is responsible for the replication of bacterial genome. The dnaE gene is often duplicated in many bacteria, and the duplicated dnaE gene was reported dispensable for cell survivals and error-prone in DNA replication in a mystery. In this study, we found that all sequenced myxobacterial genomes possessed two dnaE genes. The duplicate dnaE genes were both highly conserved but evolved divergently, suggesting their importance in myxobacteria. Using Myxococcus xanthus DK1622 as a model, we confirmed that dnaE1 (MXAN_5844) was essential for cell survival, while dnaE2 (MXAN_3982) was dispensable and encoded an error-prone enzyme for replication. The deletion of dnaE2 had small effects on cellular growth and social motility, but significantly decreased the development and sporulation abilities, which could be recovered by the complementation of dnaE2. The expression of dnaE1 was always greatly higher than that of dnaE2 in either the growth or developmental stage. However, overexpression of dnaE2 could not make dnaE1 deletable, probably due to their protein structural and functional divergences. The dnaE2 overexpression not only improved the growth, development and sporulation abilities, but also raised the genome mutation rate of M. xanthus. We argued that the low-expressed error-prone DnaE2 played as a balancer for the genome mutation rates, ensuring low mutation rates for cell adaptation in new environments but avoiding damages from high mutation rates to cells.
A STUDY OF FUEL TEMPERATURE DYNAMIC CHARACTERISTICS FOR DIESEL ENGINE COMBINATION ELECTRONIC UNIT PUMP SYSTEM

The combination electronic unit pump (CEUP) is a type of electronic unit pump fuel injection system specially designed for meeting the requirements on emission and fuel efficiency of diesel engines. It is a fairly complex product which is assembled together by mechanical, hydraulic and electrical magnetic systems. The fuel temperature dynamic characteristics of CEUP which reflects heat load characteristics of the whole system are investigated both by bench test in the laboratory and numerical simulations. The research on dynamic characteristics of highpressure fuel injection temperature (FIT) reveals the effects of fuel tank temperature and injection pulse width on FIT. The results show that FIT goes up with the increase of fuel injection pulse width when the cam rotational speed is kept constant. A maximum FIT of 118C is recorded at 10CaA pulse width, 1400 rpm cam rotational speed and 50C fuel tank temperature. It is concluded from research that increasing the pulse width by 4-6CaA and 6-10CaA results in FIT variation rate of 0-4C/ CaA and 4-5C/CaA respectively. The research on the lowpressure fuel supply temperature (FST) dynamic characteristic illustrates that the increase of FST in low-pressure system is the result of thermal transmittance of the fuel flowing back from the high-pressure system to the low-pressure system after the end of fuel injection. Moreover, FST in the low-pressure system tends to climb up with the increase of cam rotational speed and injection pulse width. In addition, the deviation between entrance fuel temperature and exit fuel temperature in low-pressure system ranges between -0.7C and 3.4C, and the same tendency has been observed when the numbers of unit pumps in CEUP are increased. It is also concluded that the variation of FST in high/ low pressure system is due to the transient coupling process of the fuel.
Incorporating Topic Priors into Distributed Word Representations

Representing words as continuous vectors enables the quantification of semantic relationships of words by vector operations, thereby has attracted much attention recently. This paper proposes an approach to combine continuous word representation and topic modeling, by encoding words based on their topic distributions in the hierarchical softmax, so as to introduce the prior semantic relevance information into the neural networks. The word vectors generated by our model are evaluated with respect to word relevance and the document relevance. Experimental results show that our approach is promising for further improving the quality of word vectors.
Substance use in children of parents with chronic pain – the HUNT study

Purpose The aim of the present study was to investigate possible associations between parental chronic pain and smoking, alcohol, and drug use in adolescent offspring. Methods Cross-sectional data from Nord-Trøndelag Health Study (HUNT 3), a Norwegian population-based health survey conducted in the period 2006–2008 was utilized. The present sample consisted of adolescents aged 13–18 years (n=3,227) for whom information was available on maternal and paternal health statuses. Results Results from multivariable ordinal and binary logistic regression analyses, adjusting for potential confounding factors (child age, parental age, education, and organ specific illness) indicated that the estimated odds ratios (OR) for smoking (OR =1.72, 95% confidence interval [CI] [1.00, 3.05], P=0.049) and alcohol intoxication (drunkenness) (OR =1.56, 95% CI [1.05, 2.33], P=0.029) were higher for boys whose mother and father had chronic pain, compared with boys for whom neither parent had chronic pain. These associations were slightly attenuated by additional adjustment for pain-related factors, such as parental smoking and symptoms of anxiety and depression. Parental chronic pain was not significantly associated with girls’ levels of substance use. There were significant interaction effects between parental chronic pain and child sex on offspring’s alcohol intoxication and smoking. Conclusion The present study expands on existing knowledge and provides groundwork for preventive and specific measures targeting substance use in families burdened with parental chronic pain.
The MARIE Autonomous Mobile Robot

In this paper an experimental platform developed for the ESPRIT project MARIE is described. The vehicle has an automobile-like kinematics and is fitted with a control computer and ultra-sonic sensors. The control software has a layered, modular structure and standardized interfaces, suitable for an experimental platform. The principal software modules and the experiments performed to test the integrated system are described.
Big Data Analyses in Health and Opportunities for Research in Radiology

Abstract This article reviews examples of big data analyses in health care with a focus on radiology. We review the defining characteristics of big data, the use of natural language processing, traditional and novel data sources, and large clinical data repositories available for research. This article aims to invoke novel research ideas through a combination of examples of analyses and domain knowledge.
Topical Sequence Profiling

This paper introduces the problem of topical sequence profiling. Given a sequence of text collections such as the annual proceedings of a conference, the topical sequence profile is the most diverse explicit topic embedding for that text collection sequence that is both representative and minimal. Topic embeddings represent a text collection sequence as numerical topic vectors by storing the relevance of each text collection for each topic. Topic embeddings are called explicit if human readable labels are provided for the topics. A topic embedding is representative for a sequence, if for each text collection the percentage of documents that address at least one of the topics exceeds a predefined threshold. If no topic can be removed from the embedding without loosing representativeness, the embedding is minimal. From the set of all minimal representative embeddings, the one with the highest mean topic variance is sought and termed as the topical sequence profile. Topical sequence profiling can be used to highlight significant topical developments, such as raise, decline, or oscillation. The computation of topical sequence profiles is made up of two steps, topic acquisition and topic selection. In the first step, the sequence's text collections are mined for representative candidate topics. As a source for semantically meaningful topic labels, we propose the use of Wikipedia article titles, whereas the respective articles are used to build a classifier for the assignment of topics to documents. Within the second step the subset of candidate topics that constitutes the topical sequence profile is determined, for which we present an efficient greedy selection strategy. We demonstrate the potential of topical sequence profiling as an effective data science technology with a case study on a sequence of conference proceedings.
Dynamic Self-Organization and Early Lexical Development in Children

In this study we present a self-organizing connectionist model of early lexical development. We call this model DevLex-II, based on the earlier DevLex model. DevLex-II can simulate a variety of empirical patterns in children's acquisition of words. These include a clear vocabulary spurt, effects of word frequency and length on age of acquisition, and individual differences as a function of phonological short-term memory and associative capacity. Further results from lesioned models indicate developmental plasticity in the network's recovery from damage, in a non-monotonic fashion. We attribute the network's abilities in accounting for lexical development to interactive dynamics in the learning process. In particular, variations displayed by the model in the rate and size of early vocabulary development are modulated by (a) input characteristics, such as word frequency and word length, (b) consolidation of lexical-semantic representation, meaning-form association, and phonological short-term memory, and (c) delayed processes due to interactions among timing, severity, and recoverability of lesion. Together, DevLex and DevLex-II provide an accurate computational account of early lexical development.
Bayesian Word Alignment for Statistical Machine Translation

In this work, we compare the translation performance of word alignments obtained via Bayesian inference to those obtained via expectation-maximization (EM). We propose a Gibbs sampler for fully Bayesian inference in IBM Model 1, integrating over all possible parameter values in finding the alignment distribution. We show that Bayesian inference outperforms EM in all of the tested language pairs, domains and data set sizes, by up to 2.99 BLEU points. We also show that the proposed method effectively addresses the well-known rare word problem in EM-estimated models; and at the same time induces a much smaller dictionary of bilingual word-pairs.