Behavioral inhibition and behavioral activation in college students: The effects of aversive control

Negative reinforcement is utilized in many contexts in our society but its differential effects in relation to individual differences are rarely studied. It is very similar in form to punishment in that they are both forms of aversive control, and only differs in the sense that negative reinforcement is a technique utilized to increase rather than reduce a behavior. Researchers, starting with Gray, have shown that individuals higher in inhibition and anxiety are more responsive to punishment, while individuals who are more impulsive are more sensitive to rewards. The positive relation between anxiety and sensitivity to punishment suggests that individuals higher in inhibition and anxiety might also be more responsive to negative reinforcement. Consistent findings have been established for how individuals who are more impulsive respond on tasks utilized to measure inhibition and approach, while results for anxious individuals are inconsistent. On go/no-go tasks specifically, impulsive individuals are less likely to inhibit responses that could result in loss than individuals who are less impulsive. No empirical explanations have been established for why individuals higher in anxiety do not respond in a consistent manner on these tasks. Gray\u27s theory of behavioral inhibition would assume that individuals higher in anxiety would be more likely to inhibit responses and even avoid opportunities for reward that may result in aversive consequences. The current research aimed to study the relation between level of inhibition and anxiety, and how individuals respond to negative reinforcement using a computerized go/no-go task. Despite inconsistent findings on previous go/no-go tasks, individuals higher in anxiety might alter responding more consistently to an increase in negative reinforcement. The current study did not identify any individual differences in how individuals responded to negative reinforcement, but does offer a paradigm to further research in the area of negative reinforcement. This study outlines the methods used and offers suggestions for improving the methods in the future

A constitutive material model for nonlinear finite element structural analysis using an iterative matrix approach

A unified numerical method for the integration of stiff time dependent constitutive equations is presented. The solution process is directly applied to a constitutive model proposed by Bodner. The theory confronts time dependent inelastic behavior coupled with both isotropic hardening and directional hardening behaviors. Predicted stress-strain responses from this model are compared to experimental data from cyclic tests on uniaxial specimens. An algorithm is developed for the efficient integration of the Bodner flow equation. A comparison is made with the Euler integration method. An analysis of computational time is presented for the three algorithms

Factors Affecting Care Quality in South Dakota Nursing Homes

Research has shown that current healthcare infrastructure is unsuited to fulfill the needs of the quickly growing population of retired Americans, a large portion of whom will require some form of long term service or support. With this in mind, the purpose of this study is to determine how certain factors such as; the incidence of use of various classes of drugs, staffing measures and education of staff, local population, and facility size relate to the overall quality of care in South Dakota nursing homes. Population data was collected from the 2010 U.S. Census and specific nursing home data was retrieved from the Nursing Home Compare Tool, part of the Medicare.gov website. Data analysis was performed using regression analysis, which utilizes a method of least squares to determine the relationship between two factors based on the scatter of data points. The results were significant in some areas and unremarkable in others; the most intriguing subject was local population. There is a significant, inverse relationship between local population and nursing home care quality, which may be explained by the size of the facility in terms of the number of certified beds

Instrument Bias Correction With Machine Learning Algorithms: Application to Field-Portable Mass Spectrometry

In situ sensors for environmental chemistry promise more thorough observations, which are necessary for high confidence predictions in earth systems science. However, these can be a challenge to interpret because the sensors are strongly influenced by temperature, humidity, pressure, or other secondary environmental conditions that are not of direct interest. We present a comparison of two statistical learning methods—a generalized additive model and a long short-term memory neural network model for bias correction of in situ sensor data. We discuss their performance and tradeoffs when the two bias correction methods are applied to data from submersible and shipboard mass spectrometers. Both instruments measure the most abundant gases dissolved in water and can be used to reconstruct biochemical metabolisms, including those that regulate atmospheric carbon dioxide. Both models demonstrate a high degree of skill at correcting for instrument bias using correlated environmental measurements; the difference in their respective performance is less than 1% in terms of root mean squared error. Overall, the long short-term memory bias correction produced an error of 5% for O2 and 8.5% for CO2 when compared against independent membrane DO and laser spectrometer instruments. This represents a predictive accuracy of 92–95% for both gases. It is apparent that the most important factor in a skillful bias correction is the measurement of the secondary environmental conditions that are likely to correlate with the instrument bias. These statistical learning methods are extremely flexible and permit the inclusion of nearly an infinite number of correlates in finding the best bias correction solution

Rapid identification of mutations in GJC2 in primary lymphoedema using whole exome sequencing combined with linkage analysis with delineation of the phenotype.

Background: Primary lymphoedema describes a chronic, frequently progressive, failure of lymphatic drainage. This disorder is frequently genetic in origin, and a multigenerational family in which eight individuals developed postnatal lymphoedema of all four limbs was ascertained from the joint Lymphoedema/Genetic clinic at St George's Hospital. Methods: Linkage analysis was used to determine a locus, and exome sequencing was employed to look for causative variants. Results: Linkage analysis revealed cosegregation of a 16.1 Mb haplotype on chromosome 1q42 that contained 173 known or predicted genes. Whole exome sequencing in a single affected individual was undertaken, and the search for the causative variant was focused to within the linkage interval. This approach revealed two novel non-synonymous single nucleotide substitutions within the chromosome 1 locus, in NVL and GJC2. NVL and GJC2 were sequenced in an additional cohort of individuals with a similar phenotype and non-synonymous variants were found in GJC2 in four additional families. Conclusion: This report demonstrates the power of exome sequencing efficiently applied to a traditional positional cloning pipeline in disease gene discovery, and suggests that the phenotype produced by GJC2 mutations is predominantly one of 4 limb lymphoedema

What Kigali’s open‑air markets reveal about achieving food and nutrition security: the role of African indigenous crops

Background: Household dietary diversity in Rwanda remains low and significantly contributes to the double burden of malnutrition. Rwanda has one of the highest under five stunting rates globally, and malnutrition remains one of the most pressing public health issues; therefore, factors that shape food and nutrition security are of utmost concern. Globally, the variety of foods available in open-air markets has been shown to affect dietary diversity. Furthermore, the consumption of indigenous foods can contribute to a diverse diet and improve nutrition status. At present, there are limited data on foods available for purchase in open-air markets in Africa. Therefore, this study was designed to provide data on food availability in the largest open-air markets of Rwanda’s most populated city, Kigali, and to highlight which foods indigenous to Africa can be purchased. Methods: All consumables were inventoried between October and December of 2020 in three open-air markets of Kigali, the capital city of Rwanda. Consumables were organized by the site of domestication and the nutritional contents of some African indigenous crops were compared to similar non-indigenous items. Results: A variety of raw and processed consumables was available in the open-air markets inventoried; however, only 25.8% of available species are indigenous to Africa. All Rwanda’s staples, including sweet potatoes, plantains, beans, maize, banana, and cassava, are endemic to other continents. Indigenous plant species, which are often drought-resistant and more nutritious, for example, Africa’s pineapple fruits (Myrianthus holstii), could not be purchased in Kigali’s open-air markets. Pineapple fruits are richer in iron, vitamin C, protein, and vitamin A than banana, which is the most consumed fruit in Rwanda. Conclusions: Given rapid population growth, limited arable land, and erratic climate patterns, policies to conserve and promote indigenous species, especially those already adapted to harsh environmental conditions, should be enacted in Rwanda. The cultivation of native vegetables and fruits in home gardens, and the conservation of edible wild species, can improve dietary diversity and enhance food and nutrition security across the entire country

Gravitational Lensing as Signal and Noise in Lyman-alpha Forest Measurements

In Lyman-alpha forest measurements it is generally assumed that quasars are mere background light sources which are uncorrelated with the forest. Gravitational lensing of the quasars violates this assumption. This effect leads to a measurement bias, but more interestingly it provides a valuable signal. The lensing signal can be extracted by correlating quasar magnitudes with the flux power spectrum and with the flux decrement. These correlations will be challenging to measure but their detection provides a direct measure of how features in the Lyman-alpha forest trace the underlying mass density field. Observing them will test the fundamental hypothesis that fluctuations in the forest are predominantly driven by fluctuations in mass, rather than in the ionizing background, helium reionization or winds. We discuss ways to disentangle the lensing signal from other sources of such correlations, including dust, continuum and background residuals. The lensing-induced measurement bias arises from sample selection: one preferentially collects spectra of magnified quasars which are behind overdense regions. This measurement bias is ~0.1-1% for the flux power spectrum, optical depth and the flux probability distribution. Since the effect is systematic, quantities such as the amplitude of the flux power spectrum averaged across scales should be interpreted with care.Comment: 22 pages, 8 figures; v2: references added, discussion expanded, matches PRD accepted versio

Loss of aboveground forest biomass and landscape biomass variability in Missouri, US

Disturbance regimes and forests have changed over time in the eastern United States. We examined effects of historical disturbance (circa 1813 to 1850) compared to current disturbance (circa 2004 to 2008) on aboveground, live tree biomass (for trees with diameters \u3e/= 13 cm) and landscape variation of biomass in forests of the Ozarks and Plains landscapes in Missouri, USA. We simulated 10,000 one-hectare plots using random diameters generated from parameters of diameter distributions limited to diameters \u3e/= 13 cm and random densities generated from density estimates. Area-weighted mean biomass density (Mg/ha) for historical forests averaged 116 Mg/ha, ranging from 54 Mg/ha to 357 Mg/ha by small scale ecological subsections within Missouri landscapes. Area-weighted mean biomass density for current forests averaged 82 Mg/ha, ranging from 66 Mg/ha to 144 Mg/ha by ecological subsection for currently forested land. Biomass density of current forest was greater than historical biomass density for only 2 of 23 ecological subsections. Current carbon sequestration of 292 TgC on 7 million ha of forested land is less than half of the estimated historical total carbon sequestration of 693 TgC on 12 million ha. Cumulative tree cutting disturbances over time have produced forests that have less aboveground tree biomass and are uniform in biomass compared to estimates of historical biomass, which varied across Missouri landscapes. With continued relatively low rates of forest disturbance, current biomass per ha will likely increase to historical levels as the most competitive trees become larger in size and mean number of trees per ha decreases due to competition and self-thinning. Restoration of large diameter structure and forested extent of upland woodlands and floodplain forests could fulfill multiple conservation objectives, including carbon sequestration