The application of human resource management policies within the marketing organization: The impact on business and marketing strategy implementation

Characteristics of the marketing organization and their relationship with strategy implementation have been the focus of considerable research over the past three decades. These characteristics include the marketing organization's structure, culture, processes, influence and leadership, among others. However, little attention has been paid to human resource management policies for marketing personnel. These policies, when properly implemented, are among the strongest motivators for appropriate individual and organizational behavior. We demonstrate in this study that the application of HR policies for mid-level marketing managers (i.e., selection, training, appraisal, and compensation) vary significantly both between firms pursuing alternative business strategies (i.e., Prospectors, Analyzers, Low Cost Defenders and Differentiated Defenders) and within each of those business strategy types by the type of marketing strategy adopted (i.e., Aggressive Marketers, Mass Marketers, Marketing Minimizers, Value Marketers). Firms whose business and marketing strategies align (Fit) demonstrated significantly stronger overall firm performance scores than those whose business and marketing strategies do not align (Misfit)

A System for Accessible Artificial Intelligence

While artificial intelligence (AI) has become widespread, many commercial AI systems are not yet accessible to individual researchers nor the general public due to the deep knowledge of the systems required to use them. We believe that AI has matured to the point where it should be an accessible technology for everyone. We present an ongoing project whose ultimate goal is to deliver an open source, user-friendly AI system that is specialized for machine learning analysis of complex data in the biomedical and health care domains. We discuss how genetic programming can aid in this endeavor, and highlight specific examples where genetic programming has automated machine learning analyses in previous projects.Comment: 14 pages, 5 figures, submitted to Genetic Programming Theory and Practice 2017 worksho

Winter wheat roots grow twice as deep as spring wheat roots, is this important for N uptake and N leaching losses?

Cropping systems comprising winter catch crops followed by spring wheat could reduce N leaching risks compared to traditional winter wheat systems in humid climates. We studied the soil mineral N (Ninorg) and root growth of winter- and spring wheat to 2.5 m depth during three years. Root depth of winter wheat (2.2 m) was twice that of spring wheat, and this was related to much lower amounts of Ninorg in the 1 to 2.5 m layer after winter wheat (81 kg Ninorg ha-1 less). When growing winter catch crops before spring wheat, N content in the 1 to 2.5 m layer after spring wheat was not different from that after winter wheat. The results suggest that by virtue of its deep rooting, winter wheat may not lead to high levels of leaching as it is often assumed in humid climates. Deep soil and root measurements (below 1 m) in this experiment were essential to answer the questions we posed

Quantum biology on the edge of quantum chaos

We give a new explanation for why some biological systems can stay quantum coherent for long times at room temperatures, one of the fundamental puzzles of quantum biology. We show that systems with the right level of complexity between chaos and regularity can increase their coherence time by orders of magnitude. Systems near Critical Quantum Chaos or Metal-Insulator Transition (MIT) can have long coherence times and coherent transport at the same time. The new theory tested in a realistic light harvesting system model can reproduce the scaling of critical fluctuations reported in recent experiments. Scaling of return probability in the FMO light harvesting complex shows the signs of universal return probability decay observed at critical MIT. The results may open up new possibilities to design low loss energy and information transport systems in this Poised Realm hovering reversibly between quantum coherence and classicality

Dead or alive: animal sampling during Ebola hemorrhagic fever outbreaks in humans

There are currently no widely accepted animal surveillance guidelines for human Ebola hemorrhagic fever (EHF) outbreak investigations to identify potential sources of Ebolavirus (EBOV) spillover into humans and other animals. Animal field surveillance during and following an outbreak has several purposes, from helping identify the specific animal source of a human case to guiding control activities by describing the spatial and temporal distribution of wild circulating EBOV, informing public health efforts, and contributing to broader EHF research questions. Since 1976, researchers have sampled over 10,000 individual vertebrates from areas associated with human EHF outbreaks and tested for EBOV or antibodies. Using field surveillance data associated with EHF outbreaks, this review provides guidance on animal sampling for resource-limited outbreak situations, target species, and in some cases which diagnostics should be prioritized to rapidly assess the presence of EBOV in animal reservoirs. In brief, EBOV detection was 32.7% (18/55) for carcasses (animals found dead) and 0.2% (13/5309) for live captured animals. Our review indicates that for the purposes of identifying potential sources of transmission from animals to humans and isolating suspected virus in an animal in outbreak situations, (1) surveillance of free-ranging non-human primate mortality and morbidity should be a priority, (2) any wildlife morbidity or mortality events should be investigated and may hold the most promise for locating virus or viral genome sequences, (3) surveillance of some bat species is worthwhile to isolate and detect evidence of exposure, and (4) morbidity, mortality, and serology studies of domestic animals should prioritize dogs and pigs and include testing for virus and previous exposure

Blockade of insulin-like growth factors increases efficacy of paclitaxel in metastatic breast cancer.

Breast cancer remains the leading cause of cancer death in women owing to metastasis and the development of resistance to established therapies. Macrophages are the most abundant immune cells in the breast tumor microenvironment and can both inhibit and support cancer progression. Thus, gaining a better understanding of how macrophages support cancer could lead to the development of more effective therapies. In this study, we find that breast cancer-associated macrophages express high levels of insulin-like growth factors 1 and 2 (IGFs) and are the main source of IGFs within both primary and metastatic tumors. In total, 75% of breast cancer patients show activation of insulin/IGF-1 receptor signaling and this correlates with increased macrophage infiltration and advanced tumor stage. In patients with invasive breast cancer, activation of Insulin/IGF-1 receptors increased to 87%. Blocking IGF in combination with paclitaxel, a chemotherapeutic agent commonly used to treat breast cancer, showed a significant reduction in tumor cell proliferation and lung metastasis in pre-clinical breast cancer models compared to paclitaxel monotherapy. Our findings provide the rationale for further developing the combination of paclitaxel with IGF blockers for the treatment of invasive breast cancer, and Insulin/IGF1R activation and IGF+ stroma cells as potential biomarker candidates for further evaluation

Estimating the workload associated with symptoms-based ovarian cancer screening in primary care: an audit of electronic medical records

BACKGROUND: Ovarian cancer is the most lethal gynaecological malignancy in the United Kingdom (UK). Studies have found that many women with ovarian cancer have symptoms for several months before diagnosis. Using a symptoms-based tool to diagnose ovarian cancer (OC) earlier is appealing, but may increase general practitioner (GP) workload because the symptoms are typically vague and non-specific. This study aimed to provide estimates of the GP workload associated with offering symptoms-based ovarian cancer screening. METHODS: A cross-sectional analysis of electronic records from four general practices in England, UK. We downloaded anonymous data on women aged 45–74 who consulted over one week to estimate the proportion who would be offered ‘screening’ according to the UK National Institute for Health and Care Excellence (NICE) guidelines and a symptoms index (Index 2) over one year. We used previous consultations (censoring women with no prior symptom at the date of their last recorded consultation) to estimate the proportion of women presenting with a new (not recorded in previous 12 months) NICE symptom each year. RESULTS: Data were obtained from 19,558 women. The proportion presenting over one week varied between practices (5%-14%), however, the proportion with an OC symptom was similar (17% overall). Over one year, an estimated 51.8% (95% CI 44.0%-59.7%) would present with an OC symptom, 26.6% (95% CI 19.3%-35.1%) with a NICE symptom and 20.3% (95% CI 13.7%-28.5%) with an Index 2 symptom. Each year, an estimated 11.9% (95% CI 5.0%-18.3%) of women would present with a new NICE symptom. CONCLUSION: One in two women aged 45–74 present to primary care at least once a year with an OC symptom, 11.9% with a new NICE symptom. This would be comparable to 2 to 8 yearly screening (depending on what symptoms triggered testing)

Infant difficult behaviors in the context of perinatal biomedical conditions and early child environment

<p>Abstract</p> <p>Background</p> <p>Problems experienced within the first year of an infant's life can be precursors of later mental health conditions. The purpose of this study was to examine the frequency and continuity of difficult behaviors in infants at 3 and 6 months of age and the associations of these difficulties with biomedical and psychosocial factors.</p> <p>Methods</p> <p>This study was a part of an ongoing prospective birth-cohort study. Study participants were 189 uniparous mothers and their full-term newborns. The index of infant difficult behavior was constructed. This index was then associated with the following factors: delivery mode, newborn function after birth, maternal emotional well-being, risk behavior, subjective evaluation of the quality of the relationship of the couple, and attitudes toward infant-rearing.</p> <p>Results</p> <p>Common difficult behaviors, including crying, sleeping and eating problems, were characteristic for 30.2% of 3 month old and for 22.2% of 6 month old full-term infants. The expression of infant difficult behaviors at the age of 3 months increased the likelihood of the expression of these difficulties at 6 months by more than 5 times. Factors including younger maternal age, poor prenatal and postnatal emotional well-being, prenatal alcohol consumption, low satisfaction with the couple's relationship before pregnancy, and deficiency of infant-centered maternal attitudes towards infant-rearing increased the likelihood of difficult behaviors in infants at the age of 3 months. Low maternal satisfaction with the relationship of the couple before pregnancy, negative emotional reactions of both parents toward pregnancy (as reported by the mother) and the deficiency of an infant-centered maternal attitude towards infant-rearing increased the likelihood of infant difficult behaviors continuing between the ages of 3 to 6 months. Perinatal biomedical conditions were not related to the difficult behaviors in infants.</p> <p>Conclusions</p> <p>Our study suggests that early onset of difficult behavior highly increases the risk for the continuation of difficult behavior during infancy. In general, the impact of prenatal psychosocial environment on infant behavior decreases from the ages of 3 to 6 months; however, some prenatal and preconceptional psychosocial factors have direct associations with the continuity of difficult behaviors through the first half-year of an infant's life.</p