Effects of Rotational Energy Relaxation in a Modular Particle-Continuum Method

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90623/1/AIAA-50720-713.pd

Effect of Energy Source Prior to Parturitian and During Lactation on Tissue Lipid, Liver Glycogen and Plasma Levels of Some Metabolytes in the Newborn Pig

Two experiments were conducted to determine the effect of energy source (carbohydrate or fat), fed to sows prior to parturition and during lactation, on energy storage and some metabolite levels in the neonatal pig which may exert an influence on rate of survival

Effect of Energy Source Prior to Parturitian and During Lactation on Tissue Lipid, Liver Glycogen and Plasma Levels of Some Metabolytes in the Newborn Pig

Two experiments were conducted to determine the effect of energy source (carbohydrate or fat), fed to sows prior to parturition and during lactation, on energy storage and some metabolite levels in the neonatal pig which may exert an influence on rate of survival

The impact of “super-dosing” phytase in pig diets on growth performance during the nursery and grow-out periods

Previous research indicates that “super-dosing” phytase may improve pig growth performance by improved nutrient use, although the benefits appear to be more consistent in nursery than in grow-out pigs. Therefore, two experiments were conducted to determine if performance could be improved by feeding phytase at super-dosed levels, and whether this response would be different if energy and amino acid (AA) were limiting. Experiment 1 involved 440 weaned pigs (6.27 ± 0.01 kg) in a factorial arrangement of treatments comparing the main effects of diet (positive control [PC] balanced for all nutrients vs. a negative control [NC]: 10% lower standardized ileal digestible (SID) lysine with relative reduction of all other essential AA and 1% reduced fat) and phytase levels (0 vs. 2,500 FTU Quantum Blue 5G phytase/kg). Pigs were assigned to pen according to a randomized complete block design based on body weight (BW). Feed and water were provided ad libitum across four dietary phases: 3 × 1 wk plus 1 × 2 wk. The average daily gain (ADG) and gain to feed ratio (G:F) were improved in the PC relative to the NC (P \u3c 0.05) indicating success in formulating a diet limiting in energy and/or AA. Phytase improved ADG and G:F, regardless of diet composition (P \u3c 0.05). Thus, super-dosing phytase improved nursery pig growth performance, irrespective of diet nutrient adequacy or deficit. Experiment 2 involved 2,200 growing pigs (36.6 ± 0.30 kg) allotted to five treatments: a balanced PC (250 FTU Quantum Blue 5G phytase/kg), an NC (PC with 15% less SID lysine and 1.5% lower net energy [NE]), and three super-dosing phytase treatments applied to the NC totaling 1,000, 1,750, and 2,500 FTU phytase/kg. Feed and water were available ad libitum. At trial completion (approximately 122 kg), the PC pigs were heavier and more efficient than the NC pigs (P \u3c 0.05) indicating success in formulating an NC treatment. Super-dosing phytase had no effect on whole body ADG or average daily feed intake (P \u3e 0.10) but tended to improve G:F and feed energy efficiency (P \u3c 0.10). Super-dosing phytase improved carcass-based feed and feed energy efficiency (P \u3c 0.05) and tended to improve ADG (P \u3c 0.10). Supplying phytase at “super-dosed” levels—above that required to meet the phosphorus requirement—improved growth performance in nursery pigs (6 to 22 kg BW) and provided smaller benefits in grow-finish pigs (37 to 122 kg BW). The improvement during the nursery period was independent of energy and AA levels in the diet

Effect of Ad libitum Feeding of Gilt Developer Diets Differing in Standard Ileal Digestive Lysine Concentrations on Growth Traits

An experiment was conducted to determine the optimum dietary lysine concentration for optimum growth rate of replacement gilts during the growing-finishing period. A total of 2,960 gilts (Large White x Landrace), 42.3±7.0 kg average BW were allotted to randomized completely block design (RCBD). Three grower and finisher diets were formulated to contain low lysine (0.68 and 0.52% standard ileal digestible (SID) lysine), medium lysine (0.79 and 0.60% SID lysine), and high lysine (0.90 and 0.68 % SID lysine) at data recording day (142, 160 and 200 d of age). Covariate of body weight at 100 days was included in the models and it had significant influence on growth traits (P \u3c 0.05). Gilts fed the high lysine treatment had increased body weight (BW), flank-to-flank, backfat thickness, loin depth, fat-free-lean, and average daily gain (ADG) (P \u3c 0.05) when compared to gilts fed the medium and low lysine treatments. The results indicated that gilts require higher dietary lysine concentrations to maximize growth rate and high lysine diet may useful to impact growth traits when fed to developing gilt from 142 to 200 kg BW

Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning

The development of cluster computing frameworks has allowed practitioners to scale out various statistical estimation and machine learning algorithms with minimal programming effort. This is especially true for machine learning problems whose objective function is nicely separable across individual data points, such as classification and regression. In contrast, statistical learning tasks involving pairs (or more generally tuples) of data points - such as metric learning, clustering or ranking do not lend themselves as easily to data-parallelism and in-memory computing. In this paper, we investigate how to balance between statistical performance and computational efficiency in such distributed tuplewise statistical problems. We first propose a simple strategy based on occasionally repartitioning data across workers between parallel computation stages, where the number of repartitioning steps rules the trade-off between accuracy and runtime. We then present some theoretical results highlighting the benefits brought by the proposed method in terms of variance reduction, and extend our results to design distributed stochastic gradient descent algorithms for tuplewise empirical risk minimization. Our results are supported by numerical experiments in pairwise statistical estimation and learning on synthetic and real-world datasets.Comment: 23 pages, 6 figures, ECML 201

Transcription factors that mediate epithelial–mesenchymal transition lead to multidrug resistance by upregulating ABC transporters

Development of multidrug resistance (MDR) is a major deterrent in the effective treatment of metastatic cancers by chemotherapy. Even though MDR and cancer invasiveness have been correlated, the molecular basis of this link remains obscure. We show here that treatment with chemotherapeutic drugs increases the expression of several ATP binding cassette transporters (ABC transporters) associated with MDR, as well as epithelial–mesenchymal transition (EMT) markers, selectively in invasive breast cancer cells, but not in immortalized or non-invasive cells. Interestingly, the mere induction of an EMT in immortalized and non-invasive cell lines increased their expression of ABC transporters, migration, invasion, and drug resistance. Conversely, reversal of EMT in invasive cells by downregulating EMT-inducing transcription factors reduced their expression of ABC transporters, invasion, and rendered them more chemosensitive. Mechanistically, we demonstrate that the promoters of ABC transporters carry several binding sites for EMT-inducing transcription factors, and overexpression of Twist, Snail, and FOXC2 increases the promoter activity of ABC transporters. Furthermore, chromatin immunoprecipitation studies revealed that Twist binds directly to the E-box elements of ABC transporters. Thus, our study identifies EMT inducers as novel regulators of ABC transporters, thereby providing molecular insights into the long-standing association between invasiveness and MDR. Targeting EMT transcription factors could hence serve as novel strategies to curb both metastasis and the associated drug resistance

The computational therapeutic: exploring Weizenbaum's ELIZA as a history of the present

This paper explores the history of ELIZA, a computer programme approximating a Rogerian therapist, developed by Jospeh Weizenbaum at MIT in the 1970s, as an early AI experiment. ELIZA’s reception provoked Weizenbaum to re-appraise the relationship between ‘computer power and human reason’ and to attack the ‘powerful delusional thinking’ about computers and their intelligence that he understood to be widespread in the general public and also amongst experts. The root issue for Weizenbaum was whether human thought could be ‘entirely computable’ (reducible to logical formalism). This also provoked him to re-consider the nature of machine intelligence and to question the instantiation of its logics in the social world, which would come to operate, he said, as a ‘slow acting poison’. Exploring Weizenbaum’s 20th Century apostasy, in the light of ELIZA, illustrates ways in which contemporary anxieties and debates over machine smartness connect to earlier formations. In particular, this article argues that it is in its designation as a computational therapist that ELIZA is most significant today. ELIZA points towards a form of human–machine relationship now pervasive, a precursor of the ‘machinic therapeutic’ condition we find ourselves in, and thus speaks very directly to questions concerning modulation, autonomy, and the new behaviorism that are currently arising

The thing about pain: The remaking of illness narratives in chronic pain expressions on social media

In this article, we analyse chronic pain narratives on Flickr and Tumblr. We focus on how, by incorporating visual and multimodal elements, chronic pain expressions in social media significantly extend and challenge the logic, function and effects of traditional ‘illness narratives’. We examine a sample of images and blogs related to chronic pain and formulate a typology of chronic pain expressions on these sites. Flickr brings a form of narrative immediacy, making the pain experience visible, eliciting empathy and marking chronicity. Tumblr lends itself to more networked forms of interaction through the circulation of multimodal memes, and support communities are built through humour and social criticism. We argue that new forms of mediation and social media dynamics transform pain narratives. This has implications for our understandings of the forms and formats of pain communication and offers new possibilities for communicating pain within and beyond clinical contexts