Miracle-dz/UniFAR-FTUs huggingface dataset:
Implications of compromised zinc status on bone loss associated with chronic inflammation in C57BL/6 mice

Compromised zinc status and chronic inflammation are independent factors that can contribute to bone loss. However, zinc’s role in regulating lymphoid and myeloid cell populations, combined with the interplay between the immune and skeletal systems raises the question as to the extent to which a low-grade inflammatory challenge in the context of marginal zinc deficiency would exacerbate bone loss. To address this question, young adult C57BL/6 male mice (n=32) were used in a 2×2 factorial design with dietary zinc (adequate or 35 ppm vs inadequate or −Zn =5 ppm) and lipopolysaccharide (LPS, 0 or 0.1 mg/kg body weight). Mice were fed their respective diets for 10 weeks. On the 6th week, mice had a slow release pellet implanted to induce a low-grade inflammation for the final 4 weeks of the study. −Zn induced a decrease in total white cell counts and peripheral lymphocytes, whereas LPS increased blood monocytes. LPS significantly reduced spine bone mineral density and trabecular bone volume and number of the vertebral body compared with both zinc adequate and inadequate without LPS groups. Likewise, the most pronounced effects on bone strength occurred with LPS, however, −Zn also had negative effects on the bone von Mises stresses. LPS induced an increase in TNF-α and this response was further increased with −Zn. Although the marginal zinc deficiency altered immune function, bone loss was not exacerbated with low-grade chronic inflammation in marginally zinc-deficient young adult mice. These findings demonstrate that in young adult animals an immune challenge modestly increases the inflammatory response and worsens bone biomechanics in the context of a marginal zinc deficiency, but not to the extent that more severe adverse outcomes are observed on bone structural parameters.
Probabilistic Modeling of Hierarchical Music Analysis

Hierarchical music analysis, as exempliﬁed by Schenkerian analysis, describes the structure of a musical composition by a hierarchy among its notes. Each analysis deﬁnes a set of prolongations, where musical objects persist in time even though others are present. We present a formal model for representing hierarchical music analysis, probabilistic interpretations of that model, and an efﬁcient algorithm for computing the most probable analysis under these interpretations. We represent Schenkerian analyses as maximal out-erplanar graphs (MOPs). We use this representation to encode the largest known data set of computer-processable Schenkerian analyses, and we use these data to identify statistical regularities in the human-generated analyses. We show that a dynamic programming algorithm can be applied to these regularities to identify the maximum likelihood analysis for a given piece of music.
Switching in Heteroclinic Networks

We study the dynamics near heteroclinic networks for which all eigenvalues of the linearization at the equilibria are real. A common connection and an assumption on the geometry of its incoming and outgoing directions exclude even the weakest forms of switching (i.e. along this connection). The form of the global transition maps, and thus the type of the heteroclinic cycle, plays a crucial role in this. We look at two examples in $\mathbb{R}^5$, the House and Bowtie networks, to illustrate complex dynamics that may occur when either of these conditions is broken. For the House network, there is switching along the common connection, while for the Bowtie network we find switching along a cycle.
Framework for Evaluating Camera Opinions

Opinion mining plays a most important role in text mining applications in brand and product positioning, customer relationship management, consumer attitude detection and market research. The applications lead to new generation of companies/products meant for online market perception, online content monitoring and reputation management. Expansion of the web inspires users to contribute/express opinions via blogs, videos and social networking sites. Such platforms provide valuable information for analysis of sentiment pertaining a product or service. This study investigates the performance of various feature extraction methods and classification algorithm for opinion mining. Opinions expressed in Amazon website for cameras are collected and used for evaluation. Features are extracted from the opinions using Term Document Frequency and Inverse Document Frequency (TDF×IDF). Feature transformation is achieved through Principal Component Analysis (PCA) and kernel PCA. Naive Bayes, K Nearest Neighbor and Classification and Regression Trees (CART) classification algorithms classify the features extracted.
Workload dependent NBTI and PBTI analysis for a sub-45nm commercial microprocessor

This paper analyzes aging effects on various design hierarchies of a sub-45nm commercial processor running realistic applications. Dependencies of aging effects on switching-activity and power-state of workloads are quantified. This paper presents an “instance-based” simulation flow, which creates a standard-cell library for each use of the cell in the design, by aging each transistor individually. Implementation results show that processor timing degradation can vary from 2% to 11%, depending on workload. Lifetime computational power efficiency improvements of optimized self-tuning is demonstrated, relative to a one-time worst-case guardbanding approach.
Exploiting BICC Features for Classification of Advertisement Videos Using RIDOR Algorithm

The latest trend in the design of electronic embedded systems focuses on technology integration with a domestic utility concept. Automated classification of advertisement videos from the general program videos is emerging as an essential task that is expected to support the television (TV) viewers to have a seamless visual experience without being hampered by commercial advertisement videos (ADD). The demand for a solution is gaining momentum which will enable the viewers to skip the advertisements and move automatically to another channel. This can be achieved just by classifying the extracted frames of videos of advertisements and non-advertisements videos (NADD) which consist of more visual information. In this present work, the descriptive feature is derived through the block intensity comparison technique and applied on 8x8 block size of the frames. The best performing features are identified and selected by decision tree (J48) algorithm and these selected features are used for classification by the Ripple Down Rule Learner (RIDOR) algorithm. The experimental results demonstrate the performance evaluation of RIDOR algorithm, the importance of dimensionality reduction and the comparative study of various classifiers. Therefore, RIDOR achieved the best classification accuracy of 87.12% is reported for further study.
Distributed Security for Communications and Memories in a Multiprocessor Architecture

The need for security in embedded systems has strongly increased since several years. Nowadays, it is possible to integrate several processors in a single chip. The design of such multiprocessor systems-on-chip (MPSoC) must be done with a lot of care as the execution of applications may lead to potential vulnerabilities such as revelation of critical data and private information. Thus it becomes mandatory to deal with security issues all along the design cycle of the MPSoC in order to guarantee a global protection. Among the critical points, the protection of the communications is very sensible as most of the data are exchanged through the communication architecture of the system. This paper targets this point and proposes a solution with distributed enhancements to secure data exchanges and to monitor communications within a MPSoC. In order to validate our contribution, a case study based on a generic multiprocessor architecture is considered.
Mitochondrial Ultrastructure and Glucose Signaling Pathways Attributed to the Kv1.3 Ion Channel

Gene-targeted deletion of the potassium channel Kv1.3 (Kv1.3−∕−) results in “Super-smeller” mice with a sensory phenotype that includes an increased olfactory ability linked to changes in olfactory circuitry, increased abundance of olfactory cilia, and increased expression of odorant receptors and the G-protein, Golf. Kv1.3−∕− mice also have a metabolic phenotype including lower body weight and decreased adiposity, increased total energy expenditure (TEE), increased locomotor activity, and resistance to both diet- and genetic-induced obesity. We explored two cellular aspects to elucidate the mechanism by which loss of Kv1.3 channel in the olfactory bulb (OB) may enhance glucose utilization and metabolic rate. First, using in situ hybridization we find that Kv1.3 and the insulin-dependent glucose transporter type 4 (GLUT4) are co-localized to the mitral cell layer of the OB. Disruption of Kv1.3 conduction via construction of a pore mutation (W386F Kv1.3) was sufficient to independently translocate GLUT4 to the plasma membrane in HEK 293 cells. Because olfactory sensory perception and the maintenance of action potential (AP) firing frequency by mitral cells of the OB is highly energy demanding and Kv1.3 is also expressed in mitochondria, we next explored the structure of this organelle in mitral cells. We challenged wildtype (WT) and Kv1.3−∕− male mice with a moderately high-fat diet (MHF, 31.8 % kcal fat) for 4 months and then examined OB ultrastructure using transmission electron microscopy. In WT mice, mitochondria were significantly enlarged following diet-induced obesity (DIO) and there were fewer mitochondria, likely due to mitophagy. Interestingly, mitochondria were significantly smaller in Kv1.3−∕− mice compared with that of WT mice. Similar to their metabolic resistance to DIO, the Kv1.3−∕− mice had unchanged mitochondria in terms of cross sectional area and abundance following a challenge with modified diet. We are very interested to understand how targeted disruption of the Kv1.3 channel in the OB can modify TEE. Our study demonstrates that Kv1.3 regulates mitochondrial structure and alters glucose utilization; two important metabolic changes that could drive whole system changes in metabolism initiated at the OB.
What Do We Do before We Do Theory?

Against the background of a ‘diagnosis’ of present-day mainstream psychological enterprise, the author explores in which way the application of the method of logico-conceptual critique may enhance the development of theory in psychology. Logico-conceptual critique is described as an heuristic device aimed at the detection and explication of logical tensions/defects/fallacies in psychological theories. It is stressed that the method necessitates the employment of the conceptual schemes of common-sense in terms of which psychological ‘subjects’ or ‘testees’ comprehend their real-life contexts. To apply the method, the author selected a particular research area (concept formation) and concentrated on theoretical positions emanating from three psychological metaphors, namely, man: the behaving machine; man: the mediatory ‘agent’ in the machine; and man: the information processor. Various logico-conceptual weaknesses in each of these positions are pointed out. It is concluded that logico-conceptual critique is an activity that should precede all experimentation, data gathering and theory building. Various suggestions are made as to how the conceptual schemes of common sense may become part and parcel of theory development in psychology.
Dynamic changes in expression of glutamate transporter mRNAs in developing brain

Developmental changes in gene expression for three glutamate transporter subtypes in the mouse brain were analysed by in situ hybridization. During embryonic stages, GluT-1 and GLT-1 mRNAs were expressed at high levels in the ventricular zone, whereas EAAC1 mRNA was not detected in the zone. In the mantle zone, transcription levels of three transporter mRNAs were low during embryonic stages, and these levels, especially those of the GluT-1 and GLT-1 mRNAs, displayed remarkable increases postnatally to reach maximal levels at 14 days of age. These dynamic developmental regulations suggest that the glutamate transporter not only regulates the excitatory synaptic transmission at mature stages, but might also be intimately involved in the brain development.
An algebra for data flow anomaly detection

An algebra A is developed that is specialized for the detection of data flow anomalies by interpreting the regular expression for the paths in a program as an A expression. Two methods are subsequently presented that use A but do not require the explicit computation of the regular expression for the paths. One method is based on the prime program decomposition. The other is based upon the iterative algorithms of global data flow analysis. In addition the use of the algebra to get better warning messages than just the detection of anomalies is presented.
Students’ Affective Learning in a Technologically Mediated Writing and Speaking Course

Situated learning theory postulates that the environment in which learning occurs is foundational to understanding the outcomes of that learning. Taking classes in a nontraditional classroom, therefore, might have a noticeable effect on learning outcomes. This study examines three structures of the same general education course to understand the potential impact of mediated learning on students’ public speaking and writing apprehension and self-efficacy. Although situated learning theory suggests that the three structures (face-to-face, partially face-to-face, and fully online) should demonstrate differences, the results of this study are mixed, suggesting a complicated picture for situated learning’s ability to speak to differences based on technology use while highlighting the differences in how such technology might affect oral skills versus written skills. The application of situated learning principles to technologically mediated courses demonstrates the need to consider the interplay between environment and content.
Using Heuristics for Supportability Analysis of Adaptive Weapon Systems in Combat

Abstract : The new U.S. Army vision contends that heuristics are practical tools for achieving innovation. Overcoming complex terrain and adaptive hybrid threats in Syria, Iraq, and Afghanistan requires technological innovation. Supportability issues result from modifying deployed weapon systems with new technology for countering these types of threats. Collecting detailed data on deployed weapon systems is constrained in combat zones. A solution for modeling supportability requirements of adaptive weapon systems in a constrained data environment involves heuristics. This modeling effort is achieved by modifying a decision matrix to include heuristics as an alternative field data source.
Estimate of the Cutoff Errors in the Ewald Summation for Dipolar Systems

Theoretical estimates for the cutoff errors in the Ewald summation method for dipolar systems are derived. Absolute errors in the total energy, forces and torques, both for the real and reciprocal space parts, are considered. The applicability of the estimates is tested and confirmed in several numerical examples. We demonstrate that these estimates can be used easily in determining the optimal parameters of the dipolar Ewald summation in the sense that they minimize the computation time for a predefined, user set, accuracy.
A Cross-Cutting Calm How Social Sorting Drives Affective Polarization

Although anecdotal stories of political anger and enthusiasm appear to be provoked largely by issues such as gay marriage or healthcare reform, social sorting is capable of playing a powerful role in driving anger and enthusiasm, undercutting the perception that only practical disagreements are driving higher levels of political rancor. Because a highly aligned set of social identities increases an individual’s perceived differences between groups, the emotions that result from group conflict are likely to be heightened among well-sorted partisans. An experimental design in a national online survey manipulates political threats and reassurances, including a threat to a party and a threat to distinct policy goals. Issue positions are found to drive anger and enthusiasm in the presence of issue-based messages, but not all party-based messages. Partisan identity drives anger and enthusiasm in the presence of party-based threats and reassurances, but not all issue-based messages. Social sorting, however, drives anger and enthusiasm in response to all threats and reassurances, suggesting that well-sorted partisans are more reliably emotionally reactive to political messages. Finally, these results are driven not by the most-sorted partisans, but by the emotional dampening effect that occurs among those with the most cross-cutting identities. As social sorting increases in the American electorate, the cooler heads inspired by cross-cutting identities are likely to be taking up a smaller portion of the electorate.
The role of space in reducing predator-prey cycles

Throughout the history of ecology, the interaction between predators and their prey has received attention from ecologists. Some of the longest and most well-known data series in ecology are from predator and prey populations, and predator–prey models are among the oldest in the field. Despite these efforts, a discrepancy exists between the behavior of most models and that of natural predator and prey populations. Most predator–prey models predict lasting periodic oscillations in population densities. Oscillations have been observed in nature, but they do not seem nearly as common or as pronounced as models predict. Several explanations have been suggested for the qualitative difference between the behavior of the models and reality. Most of these involve additional mechanisms, such as invulnerable life stages of the prey or optimal foraging behavior of the predator. However, experimental studies show that the equations used in classical models do indeed give a reasonable qualitative description of the behavior of predator and prey populations (Gause et al. 1936; Maly 1969; Harrison 1995). All these studies compare model predictions with laboratory-scale experiments in which the densities often exhibit oscillations that can lead to population extinction (Huffaker 1958; Gause 1969; Luckinbill 1974). The models thus seem to describe the interaction between predators and their prey in laboratory experiments reasonably well, but fail to capture the properties of natural populations. Because there is no reason to believe that laboratory and natural populations are fundamentally different, the spatial scale at which the predator–prey system exists must play a crucial role in preventing population oscillations in the field.
Genocide and frontier violence in Australia

ABSTRACT Did frontier conflict in Australia amount to genocide? Answers to this question have revolved around topics such as contemporary understandings of the conflict, intent, the applicability of the term to Australian history and considerations of Indigenous agency. In this historiographical article, we argue that ‘genocide’ is a useful framework with which to understand the frontier experience in the Australian colonies. From that perspective, we provide a critical review of the literature up to the present.
Inter-STOP symbol distances for the identification of coding regions

Summary In this study we explore the potential of inter-STOP symbol distances for finding coding regions in DNA sequences. We use the distance between STOP symbols in the DNA sequence and a chi-square statistic to evaluate the nonhomogeneity of the three possible reading frames and the occurrence of one long distance in one of the frames. The results of this exploratory study suggest that inter-STOP symbol distances have strong ability to discriminate coding regions in prokaryotes and simple eukaryotes.
Association of the Ala54-Thr polymorphism in the intestinal fatty acid-binding protein with 2-h postchallenge insulin levels in the Framingham Offspring Study.

OBJECTIVE To investigate the association of variants of the intestinal fatty acid-binding protein gene (FABP2) with fasting and postchallenge glucose and insulin levels, HbA(1c), and prevalence of type 2 diabetes in a separate sample of men and women. RESEARCH DESIGN AND METHODS Subjects were participants in the Framingham Offspring Study, a long-term community-based prospective observational study of risk factors for cardiovascular disease. The study sample consisted of 762 men and 922 women. RESULTS In women, carriers of the Thr54 allele had significantly higher 2-h postchallenge insulin levels than noncarriers (104.4 +/- 73.0 vs. 93.4 +/- 61.5 microU/ml; P = 0.0139). This relationship remained significant after adjustment for familial relationship, age, BMI, triglycerides, APOE genotype, smoking, alcohol intake, the use of beta-blockers, menopausal status, and estrogen therapy. No such significant association was observed in men. In both men and women, there were no statistical associations between the FABP2 polymorphism and BMI, fasting glucose, fasting insulin, 2-h postchallenge glucose levels, HbA(1c), and prevalence of type 2 diabetes. CONCLUSIONS These results suggest that the FABP2 Thr54 allele may have a minor contribution to the insulin resistance syndrome in a white general population.
Associations of knee extensor strength and standing balance with physical function in knee osteoarthritis

Knee extensor strength is an important correlate of physical function in patients with knee osteoarthritis; however, it remains unclear whether standing balance is also a correlate. The purpose of this study was to evaluate the cross‐sectional associations of knee extensor strength, standing balance, and their interaction with physical function.
The School That Refused to Die: Continuity and Change at Thomas Jefferson High School

ilies, especially in cities, to forego income from their children, and allow them to remain in school. By 1930 only one in twenty children worked, and in 1940 the figure sank to one in one hundred. But by the 1970s and 1980s, the trend had reversed itself. In 1990 between half and two-thirds of all high school juniors held part-time jobs. The revival of teen participation in the work force was not caused by necessity-the overwhelming majority of working teenagers came from middle-class families-but by the desire of the young to purchase the increasingly expensive consumer wares of the youth culture market. Material from the other categories selected by West is equally compelling. There is an evocative re-creation of a turn-of-the-century educational experience in a rural schoolhouse, and a comprehensive description of the revolution in eating habits during the 1920s. The book is a treasure house of information and guidelines for research on the history of the child during the twentieth century. This valuable guide's major shortcoming is conceptual: there is no overview, in an introduction or conclusion, about what it all means. West states that Americans have made this the "century of the child," and he ably traces the enormous changes (most of them positive) in the condition of children over the course of the century. But he fails to discuss why children and the idea of childhood have such a central place within American culture. For example, it is clear that most Americans are implacably child-centered and, in fact, unabashedly sentimental about childhood. It is not clear why this is the case, especially since most Americans are remarkably unsentimental about what happens to the individual once he or she leaves the paradise of childhood and enters the fallen state of adulthood-note the commitment to ruthless do-or-die economic competition, the lack of help for victims of corporate "downsizing," or the general disdain for those on welfare. This extremely useful book would have profited from a conceptual overview.