Systemic Development of Leadership: Action Research in an Indian Manufacturing Organization

This insider action research study differentiates between developing leaders and leadership, evolves a systemic leadership model, and intervenes on the human, social and processes dimensions for developing leadership. This is a real-time study and responds to the organizational reality of fast pace of change and its systemic nature. Consequently, the research too is fast to guide actions and influence positive changes in the organization. As the action research addresses a systemic reality, research and contributions are in multiple aspects, with new techniques having huge implications for theory building as well as improving practice. The study provides a structural solution to perceived lack of commitment in senior colleagues—a syndrome I acronym as HILE (High Intentions and Lukewarm Execution)–by re-designing organizational processes and making time available for its effective utilization in developing leadership. A new technique of triggering major changes in organizations termed “concept sublimation” distils concept from the statements of major stakeholder and sublimates it from lower to higher unit of analysis and to higher levels of positivity. Statistical simplification of a competency framework by applying concepts from Euclidian geometry and making it effective is yet a unique contribution of this action research study. The study adapts the competing values framework in developing a method of assessing cultural congruence of a candidate with the culture of the organization. The uniqueness of the study lies in bridging the gap in the literature by actually and systemically developing leadership in an organization and providing pragmatic insights on developing leadership while also creating knowledge for theory building.     

<Emphasis Type="Italic">Dictyostelium</Emphasis> dynamin B modulates cytoskeletal structures and membranous organelles

Dictyostelium discoideum cells produce five dynamin family proteins. Here, we show that dynamin B is the only member of this group of proteins that is initially produced as a preprotein and requires processing by mitochondrial proteases for formation of the mature protein. Our results show that dynamin B-depletion affects many aspects of cell motility, cell-cell and cell-surface adhesion, resistance to osmotic shock, and fatty acid metabolism. The mature form of dynamin B mediates a wide range and unique combination of functions. Dynamin B affects events at the plasma membrane, peroxisomes, the contractile vacuole system, components of the actin-based cytoskeleton, and cell adhesion sites. The modulating effect of dynamin B on the activity of the contractile vacuole system is unique for the Dictyostelium system. Other functions displayed by dynamin B are commonly associated with either classical dynamins or dynamin-related proteins.     

Ablation of LMO4 in glutamatergic neurons impairs leptin control of fat metabolism

The LIM domain only 4 (LMO4) protein is expressed in the hypothalamus, but its function there is not known. Using mice with LMO4 ablated in postnatal glutamatergic neurons, including most neurons of the paraventricular (PVN) and ventromedial (VMH) hypothalamic nuclei where LMO4 is expressed, we asked whether LMO4 is required for metabolic homeostasis. LMO4 mutant mice exhibited early onset adiposity. These mice had reduced energy expenditure and impaired thermogenesis together with reduced sympathetic outflow to adipose tissues. The peptide hormone leptin, produced from adipocytes, activates Jak/Stat3 signaling at the hypothalamus to control food intake, energy expenditure, and fat metabolism. Intracerebroventricular infusion of leptin suppressed feeding similarly in LMO4 mutant and control mice. However, leptin-induced fat loss was impaired and activation of Stat3 in the VMH was blunted in these mice. Thus, our study identifies LMO4 as a novel modulator of leptin function in selective hypothalamic nuclei to regulate fat metabolism.     

Cyclopentenones from lactones

Zusammenfassung Es wird eine verbesserte Anordnung zur Überführung von Lactonen in Cyclopectonen beschrieben.     

Oscillatory dependence of current-driven magnetic domain wall motion on current pulse length

Magnetic domain walls, in which the magnetization direction varies continuously from one direction to another, have long been objects of considerable interest. New concepts for devices based on such domain walls are made possible by the direct manipulation of the walls using spin-polarized electrical current through the phenomenon of spin momentum transfer. Most experiments to date have considered the current-driven motion of domain walls under quasi-static conditions, whereas for technological applications, the walls must be moved on much shorter timescales. Here we show that the motion of domain walls under nanosecond-long current pulses is surprisingly sensitive to the pulse length. In particular, we find that the probability of dislodging a domain wall, confined to a pinning site in a permalloy nanowire, oscillates with the length of the current pulse, with a period of just a few nanoseconds. Using an analytical model and micromagnetic simulations, we show that this behaviour is connected to a current-induced oscillatory motion of the domain wall. The period is determined by the wall's mass and the slope of the confining potential. When the current is turned off during phases of the domain wall motion when it has enough momentum, the domain wall is driven out of the confining potential in the opposite direction to the flow of spin angular momentum. This dynamic amplification effect could be exploited in magnetic nanodevices based on domain wall motion.     

FORECASTING AUTOMOBILE WARRANTY PERFORMANCE IN PRESENCE OF ‘MATURING DATA＇ PHENOMENA USING MULTILAYER PERCEPTRON NEURAL NETWORK

Automobile companies that spend billions of dollars annually towards warranty cost, give high priority to warranty reduction programs. Forecasting of automobile warranty performance plays an important role towards these efforts. The forecasting process involves prediction of not only the specific months-in-service (MIS) warranty performance at certain future time, but also at future MIS values. However, ‘maturing data‘ (also called warranty growth) phenomena that causes warranty performance at specific MIS values to change with time, makes such a forecasting task challenging. Although warranty forecasting methods such as log-log plots and dynamic linear models appear in literature, there is a need for applications addressing the well recognized issue of ‘maturing data‘. In this paper we use an artificial neural network for the forecasting of warranty performance in presence of ‘maturing data‘ phenomena. The network parameters are optimized by minimizing the training and testing errors using response surface methodology. This application shows the effectiveness of neural networks in the forecasting of automobile warranty performance in the presence of the ‘maturing data‘ phenomena.