Fermion masses in noncommutative geometry

Recent indications of neutrino oscillations raise the question of the possibility of incorporating massive neutrinos in the formulation of the Standard Model (SM) within noncommutative geometry (NCG). We find that the NCG requirement of Poincare duality constrains the numbers of massless quarks and neutrinos to be unequal unless new fermions are introduced. Possible scenarios in which this constraint is satisfied are discussed.Comment: 4 pages, REVTeX; typos are corrected in (19), "Possible Solutions" and "Conclusion" are modified; additional calculational details are included; references are update

Investigation of vacuum polarization in t-channel radiative Bhabha scattering

We discuss the possibility of a precision measurement of vacuum polarization in t-channel radiative Bhabha scattering at a high luminosity collider. For illustration, the achievable precision is estimated for the BaBar experiment at PEP-II and for the OPAL experiment at LEP

Soil Degradation: Will Humankind Ever Learn?

Citation: Karlen, D. L., & Rice, C. W. (2015). Soil Degradation: Will Humankind Ever Learn? Sustainability, 7(9), 12490-12501. doi:10.3390/su70912490Soil degradation is a global problem caused by many factors including excessive tillage, inappropriate crop rotations, excessive grazing or crop residue removal, deforestation, mining, construction and urban sprawl. To meet the needs of an expanding global population, it is essential for humankind to recognize and understand that improving soil health by adopting sustainable agricultural and land management practices is the best solution for mitigating and reversing current soil degradation trends. This research editorial is intended to provide an overview for this Special Issue of Sustainability that examines the global problem of soil degradation through reviews and recent research studies addressing soil health in Africa, Australia, China, Europe, India, North and South America, and Russia. Two common factorssoil erosion and depletion of soil organic matter (SOM)emerge as consistent indicators of how the thin layer covering the planet that stands between us and starvation is being degraded. Soil degradation is not a new problem but failing to acknowledge, mitigate, and remediate the multiple factors leading to it is no longer a viable option for humankind. We optimistically conclude that the most promising strategies to mitigate soil degradation are to select appropriate land uses and improve soil management practices so that SOM is increased, soil biology is enhanced, and all forms of erosion are reduced. Collectively, these actions will enable humankind to take care of the soil so it can take care of us.Soil degradation is a global problem caused by many factors including excessive tillage, inappropriate crop rotations, excessive grazing or crop residue removal, deforestation, mining, construction and urban sprawl. To meet the needs of an expanding global population, it is essential for humankind to recognize and understand that improving soil health by adopting sustainable agricultural and land management practices is the best solution for mitigating and reversing current soil degradation trends. This research editorial is intended to provide an overview for this Special Issue of Sustainability that examines the global problem of soil degradation through reviews and recent research studies addressing soil health in Africa, Australia, China, Europe, India, North and South America, and Russia. Two common factors—soil erosion and depletion of soil organic matter (SOM)—emerge as consistent indicators of how “the thin layer covering the planet that stands between us and starvation” is being degraded. Soil degradation is not a new problem but failing to acknowledge, mitigate, and remediate the multiple factors leading to it is no longer a viable option for humankind. We optimistically conclude that the most promising strategies to mitigate soil degradation are to select appropriate land uses and improve soil management practices so that SOM is increased, soil biology is enhanced, and all forms of erosion are reduced. Collectively, these actions will enable humankind to “take care of the soil so it can take care of us”

Balancing Corn Yield Goals and N Fertilization Rates

Establishing realistic yield goals is essential for environmentally and economically sustainable crop production. It is also important because many of the variable inputs, including fertilizer N rates, are often based upon those goals. If yield goals are beyond what uncontrollable factors such as rainfall can support, many controllable inputs such as N fertilizer will probably be used at rates in excess of crop needs. This scenario will result in reduced nutrient recovery, decreased profitability or return on fertilizer investment, and an increased potential for N loss to groundwater resources. If yield goals are set too low, crop nutrient needs may be underestimated leading to loss of yield, quality, and profit

Reflexive obstacle avoidance for kinematically-redundant manipulators

Dexterous telerobots incorporating 17 or more degrees of freedom operating under coordinated, sensor-driven computer control will play important roles in future space operations. They will also be used on Earth in assignments like fire fighting, construction and battlefield support. A real time, reflexive obstacle avoidance system, seen as a functional requirement for such massively redundant manipulators, was developed using arm-mounted proximity sensors to control manipulator pose. The project involved a review and analysis of alternative proximity sensor technologies for space applications, the development of a general-purpose algorithm for synthesizing sensor inputs, and the implementation of a prototypical system for demonstration and testing. A 7 degree of freedom Robotics Research K-2107HR manipulator was outfitted with ultrasonic proximity sensors as a testbed, and Robotics Research's standard redundant motion control algorithm was modified such that an object detected by sensor arrays located at the elbow effectively applies a force to the manipulator elbow, normal to the axis. The arm is repelled by objects detected by the sensors, causing the robot to steer around objects in the workspace automatically while continuing to move its tool along the commanded path without interruption. The mathematical approach formulated for synthesizing sensor inputs can be employed for redundant robots of any kinematic configuration

Cyberostracism and Social Monitoring: Social Anxiety\u27s Effects on Reactions to Exclusion and Inclusion Online

Previous research has shown that ostracism –the equivalence of exclusion in a social situation –improves social monitoring abilities – a natural practice by which individuals gather information through social cues about what is happening in their social worlds (Pickett, Gardner, & Knowles, 2004). Current knowledge on social anxiety, defined as a chronic fear of social situations that put one in the position of evaluation by others, describes hypersensitivity in those individuals in cases of social monitoring others (Barlow, 2002; Craske, 1999). The current study investigated how those two constructs interacted in a cyberostracism paradigm. After measuring their social anxiety levels, participants were placed in either an exclusion or inclusion situation modeled on the social networking website Facebook, a medium through which rejection is not only easily but also commonly executed. Following the manipulation, participants were tested on their social monitoring abilities, their mood, and their feelings of satisfaction in regards to Williams’ four fundamental needs – self-esteem, control, belonging, and meaningful existence. We hypothesized that individuals in the exclusion situation, in contrast to those in the inclusion situation, would show higher levels of social monitoring ability, lower mood, and fewer feelings of satisfaction in relation to Williams’ needs. We also predicted that individuals who were higher in social anxiety would show lower levels of social monitoring ability. Finally, we hypothesized that individuals both high in social anxiety and placed into the exclusion situation would show the lowest levels of social monitoring ability. Results showed that while participants with higher levels of social anxiety had stronger psychological reactions to be ostracized, they did not then show decreased social monitoring abilities. However, participants who were high in social anxiety and also in the exclusion situation made different kinds of social monitoring errors based on the affect and intensity of the social cue

SMAF: A Soil Health Assessment Tool

The Soil Management Assessment Framework (SMAF) was developed to help quantify soil quality/health effects of tillage, crop rotation, and other soil management practices. Our objective was to determine if the SMAF could detect soil health differences after growing a single winter triticale (X Triticosecale Wittmack) crop. Soil samples were collected from 0 to 7.5- and 7.5 to 15- cm depth increments during the 2003 – 2004 and 2004 – 2005 growing seasons near Ames and Lewis, IA, and analyzed for several potential soil quality indicators. The SMAF analysis showed higher soil quality ratings for surface than subsurface samples. It also showed that a single winter grain crop can significantly improve soil quality after either corn (Zea mays L.) or soybean (Glycine max [L.] Merr.). Finally, in response to increasing interest in soil health assessments, a detailed appendix is attached to provide guidance for future soil health assessments

Empirical analysis and prediction of nitrate loading and crop yield for corn–soybean rotations

Nitrate nitrogen losses through subsurface drainage and crop yield are determined by multiple climatic and management variables. The combined and interactive effects of these variables, however, are poorly understood. Our objective is to predict crop yield, nitrate concentration, drainage volume, and nitrate loss in subsurface drainage from a corn (Zea mays L.) and soybean (Glycine max (L.) Merr.) rotation as a function of rainfall amount, soybean yield for the year before the corn–soybean sequence being evaluated, N source, N rate, and timing of N application in northeastern Iowa, U.S.A. Ten years of data (1994–2003) from a long-term study near Nashua, Iowa were used to develop multivariate polynomial regression equations describing these variables. The regression equations described over 87, 85, 94, 76, and 95% of variation in soybean yield, corn yield, subsurface drainage, nitrate concentration, and nitrate loss in subsurface drainage, respectively. A two-year rotation under average soil, average climatic conditions, and 125 kg N/ha application was predicted to loose 29, 37, 36, and 30 kg N/ha in subsurface drainage for early-spring swine manure, fall-applied swine manure, early-spring UAN fertilizer, and late-spring split UAN fertilizer (urea ammonium nitrate), respectively. Predicted corn yields were 10.0 and 9.7 Mg/ha for the swine manure and UAN sources applied at 125 kg N/ha. Timing of application (i.e., fall or spring) did not significantly affect corn yield. These results confirm other research suggesting that manure application can result in less nitrate leaching than UAN (e.g., 29 vs. 36 kg N/ha), and that spring application reduces nitrate leaching compared to fall application (e.g., 29 vs. 37 kg N/ha). The regression equations improve our understanding of nitrate leaching; offer a simple method to quantify potential N losses from Midwestern corn–soybean rotations under the climate, soil, and management conditions of the Nashua field experiment; and are a step toward development of easy to use N management tools