Swine in Confinement - Feeding

It\u27s no news that hog feeding has moved out of the slopping stage. With the movement from pasture to houses and the shift from a small number of slop-fed hogs to larger scale production, swine producers soon learned that when swine are confined without vegetation, more care had to be taken with rations. And, with feed costs accounting for two-thirds to nearly nine-tenths of the total production cost, no wonder so much attention has been paid to rations, feeds, and feeding

Limit on the fermion masses in technicolor models

Recently it has been pointed out that no limits can be put on the scale of fermion mass generation $(M)$ in technicolor models, because the relation between the fermion masses $(m_f)$ and $M$ depends on the dimensionality of the interaction responsible for generating the fermion mass. Depending on this dimensionality it may happens that $m_f$ does not depend on $M$ at all. We show that exactly in this case $m_f$ may reach its largest value, which is almost saturated by the top quark mass. We make few comments on the question of how large can be a dynamically generated fermion mass.Comment: 5 pages, 1 figure, RevTeX

Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data

Despite the remarkable advances in cancer diagnosis, treatment, and management that have occurred over the past decade, malignant tumors remain a major public health problem. Further progress in combating cancer may be enabled by personalizing the delivery of therapies according to the predicted response for each individual patient. The design of personalized therapies requires patient-specific information integrated into an appropriate mathematical model of tumor response. A fundamental barrier to realizing this paradigm is the current lack of a rigorous, yet practical, mathematical theory of tumor initiation, development, invasion, and response to therapy. In this review, we begin by providing an overview of different approaches to modeling tumor growth and treatment, including mechanistic as well as data-driven models based on ``big data" and artificial intelligence. Next, we present illustrative examples of mathematical models manifesting their utility and discussing the limitations of stand-alone mechanistic and data-driven models. We further discuss the potential of mechanistic models for not only predicting, but also optimizing response to therapy on a patient-specific basis. We then discuss current efforts and future possibilities to integrate mechanistic and data-driven models. We conclude by proposing five fundamental challenges that must be addressed to fully realize personalized care for cancer patients driven by computational models

United States Relations with the Association of Southeast Asian Nations (ASEAN)

This report provides an overview of U.S. interests towards the Association of Southeast Asian Nations (ASEAN). The report discusses the U.S. policy developments toward the region and policy issues

Fundamental constructs in food parenting practices: a content map to guide future research

Although research shows that “food parenting practices” can impact children’s diet and eating habits, current understanding of the impact of specific practices has been limited by inconsistencies in terminology and definitions. This article represents a critical appraisal of food parenting practices, including clear terminology and definitions, by a working group of content experts. The result of this effort was the development of a content map for future research that presents 3 overarching, higher-order food parenting constructs – coercive control, structure, and autonomy support – as well as specific practice subconstructs. Coercive control includes restriction, pressure to eat, threats and bribes, and using food to control negative emotions. Structure includes rules and limits, limited/guided choices, monitoring, meal- and snacktime routines, modeling, food availability and accessibility, food preparation, and unstructured practices. Autonomy support includes nutrition education, child involvement, encouragement, praise, reasoning, and negotiation. Literature on each construct is reviewed, and directions for future research are offered. Clear terminology and definitions should facilitate cross-study comparisons and minimize conflicting findings resulting from previous discrepancies in construct operationalization

Symptoms associated with victimization in patients with schizophrenia and related disorders

Background: Patients with psychoses have an increased risk of becoming victims of violence. Previous studies have suggested that higher symptom levels are associated with a raised risk of becoming a victim of physical violence. There has been, however, no evidence on the type of symptoms that are linked with an increased risk of recent victimization. Methods: Data was taken from two studies on involuntarily admitted patients, one national study in England and an international one in six other European countries. In the week following admission, trained interviewers asked patients whether they had been victims of physical violence in the year prior to admission, and assessed symptoms on the Brief Psychiatric Rating Scale (BPRS). Only patients with a diagnosis of schizophrenia or related disorders (ICD-10 F20–29) were included in the analysis which was conducted separately for the two samples. Symptom levels assessed on the BPRS subscales were tested as predictors of victimization. Univariable and multivariable logistic regression models were fitted to estimate adjusted odds ratios. Results: Data from 383 patients in the English sample and 543 patients in the European sample was analysed. Rates of victimization were 37.8% and 28.0% respectively. In multivariable models, the BPRS manic subscale was significantly associated with victimization in both samples. Conclusions: Higher levels of manic symptoms indicate a raised risk of being a victim of violence in involuntary patients with schizophrenia and related disorders. This might be explained by higher activity levels, impaired judgement or poorer self-control in patients with manic symptoms. Such symptoms should be specifically considered in risk assessments

Characterization of Sleep Stages by Correlations of Heartbeat Increments

We study correlation properties of the magnitude and the sign of the increments in the time intervals between successive heartbeats during light sleep, deep sleep, and REM sleep using the detrended fluctuation analysis method. We find short-range anticorrelations in the sign time series, which are strong during deep sleep, weaker during light sleep and even weaker during REM sleep. In contrast, we find long-range positive correlations in the magnitude time series, which are strong during REM sleep and weaker during light sleep. We observe uncorrelated behavior for the magnitude during deep sleep. Since the magnitude series relates to the nonlinear properties of the original time series, while the signs series relates to the linear properties, our findings suggest that the nonlinear properties of the heartbeat dynamics are more pronounced during REM sleep. Thus, the sign and the magnitude series provide information which is useful in distinguishing between the sleep stages.Comment: 7 pages, 4 figures, revte

Decision Tree Algorithms Predict the Diagnosis and Outcome of Dengue Fever in the Early Phase of Illness

Dengue illness appears similar to other febrile illness, particularly in the early stages of disease. Consequently, diagnosis is often delayed or confused with other illnesses, reducing the effectiveness of using clinical diagnosis for patient care and disease surveillance. To address this shortcoming, we have studied 1,200 patients who presented within 72 hours from onset of fever; 30.3% of these had dengue infection, while the remaining 69.7% had other causes of fever. Using body temperature and the results of simple laboratory tests on blood samples of these patients, we have constructed a decision algorithm that is able to distinguish patients with dengue illness from those with other causes of fever with an accuracy of 84.7%. Another decision algorithm is able to predict which of the dengue patients would go on to develop severe disease, as indicated by an eventual drop in the platelet count to 50,000/mm3 blood or below. Our study shows a proof-of-concept that simple decision algorithms can predict dengue diagnosis and the likelihood of developing severe disease, a finding that could prove useful in the management of dengue patients and to public health efforts in preventing virus transmission