Towards a Variety of Family Models: Economic Contributions of Spouses and Family Power

In Western societies the increase in female employment (especially among married women) is seen as having brought about the crisis of the traditional model of the family, reinforcing the position of the "modern" model - the egalitarian family with two working spouses and a "dual-career" family. In contrast, the transitional situation in the post-communist countries during the 1990s is producing a crisis of the family with two working spouses (the basic type of the communist period) and leading to new power relations within the family. While the growth of dual-earner households in this century has implied modification of family models towards greater symmetry of responsibility for breadwinning and homemaking, there is considerable evidence that women's increased employment does not necessarily lead to a more egalitarian approach to gender roles within the family. The group set out to investigate the economic situation of families and economic power within the fame as a crucial factor in the transformation of families with two working spouses in order to reveal the specific patterns of gender contracts and power relations within the family that are emerging in response to the current political and economic transformation. They opted for a comparative approach, selecting the Czech Republic as a country where the very similar tendencies of a few years ago (almost 100% of women employed and the family as a realm of considerable private freedom where both women's and men's gender identities and the traditional distribution of family responsibilities were largely preserved) are combined with a very different experience in terms of economic inequalities during the 1990s to that of Russia. In the first stage of the study they surveyed 300 married couples (150 in each country) on the question of breadwinning. They then carried out in-depth interviews with 10 couples from each country (selected from among the educated layers of the population), focusing on the process of the social construction of gender, using breadwinning and homemaking as gender boundaries which distinguish men from women. By analysing changes in social position and the type of interpersonal interaction of spouses they distinguished two main types of family contracts: the neo-traditional "communal sharing" (with male breadwinner, traditional distribution of family chores and negotiated family power) and the modern one based on negotiated agreement. The most important pre-conditions of husband-wife agreement about breadwinning seemed to imply their overall gender ideology rather than the economic and/or family circumstances. In general, wives were more likely to express egalitarian views, supporting the blurring or even elimination of many gender boundaries. Husbands, on the other hand, more often gave responses calling for the continued maintenance of gender boundaries. The analysis showed that breadwinning is still an important gender boundary in these cultures, one that is assumed unless it is explicitly questioned and that is seen as part of what makes a man a "real man". The majority of respondents seemed to be committed to egalitarian ideology on gender roles and the distribution of family tasks, including decision making, but this is contradicted by the persistent idea of the husband as the breadwinner. This contradiction is more characteristic of the Russian situation than of the Czech. The quantitative study showed a difference in prevailing family models between the two countries, with a clearer shift towards the traditional family contract in the Russian case. The Czechs were more likely to consider their partnerships as based on negotiated agreement, while the Russians saw theirs as based on egalitarian contract, in both cases seeing this as the norm. The majority of couples said they felt satisfied with their marriage, although in both countries wives seemed to be less satisfied. There was however a difference in the issues that aroused dissatisfaction, with Czech women being more sensitive to issues such as self-realisation, personal independence, understanding and recognition in the family, and Russians to issues of love, understanding and recognition. The most disputed area for the majority of families was chores in the home, presumably because in many families both husband and wife were working hard outside the home and because a number of partners had differing views as to the ideal distribution of chores within the family. The distribution of power in the family seems to be linked to the level of well being. The analysis showed that in the dominant democratic model there is still an inverse connection between family leadership and well being: the more prominent the wife's position as head of the family is, the lower the level of family income. This may reflect both the husband's refusal to play the leading role in the family and even his rejection of any involvement in family issues in such a family. The qualitative research revealed that both men and women see the breadwinning role to be an essential part of masculine identity, a role which the female partner would take on temporarily to assist the male but not permanently since this would threaten the gender boundaries and the man's identity. At the same time, few breadwinners expressed a sense of job satisfaction and all considered their choice as imposed on them by the circumstances (i.e. having a family in difficult times). The group feel that family orientation and some loss of personal involvement in their profession is partly reflected in the fact that many of the men felt more comfortable and self-confident at home than at work. Women's work, on the other hand, was largely seen as a source of personal and self-realisation and social life. Eight out of ten of the Russian women interviewed were employed, although only two on a full-time basis, but none saw their jobs as adding substantially to the family budget. Both partners see the most important factor as the wife's wish to work or stay at home, and do not think it wise for the wife to work at the expense of her part of the "family contract", although husbands from the "egalitarian" relationships expressed more willingness to compromise. The analysis showed clearly that wives and husbands did not construct gender boundaries in isolation, with the interviews providing clear evidence of negotiation. At the same time, husbands' interpretations of their wives' employment were less susceptible to the influence of negotiation than were their gender attitudes and norms about breadwinning. One of the most interesting aspects of the spouses' negotiations was the extent to which they disagreed about what they seemed to have agreed upon. Most disagreements about the breadwinning boundaries, however, were over norms and were settled by changes in norms rather than in behavioural interpretation. Changes in norms were often a form of peace offering or were in response in changes in circumstances. The study did show, however, that many of the efforts at cooperation and compensation were more symbolic than real and the group found the plasticity of expressed gender ideology to be one of the most striking findings of their work. They conclude that the shift towards more traditional gednder distributions of incomes and domestic chores does not automatically mean the reestablishment of a patriarchal model of family power. On the contrary, it seems to be a compromise formation, relatively unstable, temporary and containing self-defeating forces as the split between the personal and professional value of work and its social value expressed in a money equivalent cannot be maintained for generations.

Power and Robustness of Linkage Tests for Quantitative Traits in General Pedigrees

There are numerous statistical methods for quantitative trait linkage analysis in human studies. An ideal such method would have high power to detect genetic loci contributing to the trait, would be robust to non-normality in the phenotype distribution, would be appropriate for general pedigrees, would allow the incorporation of environmental covariates, and would be appropriate in the presence of selective sampling. We recently described a general framework for quantitative trait linkage analysis, based on generalized estimating equations, for which many current methods are special cases. This procedure is appropriate for general pedigrees and easily accommodates environmental covariates. In this paper, we use computer simulations to investigate the power robustness of a variety of linkage test statistics built upon our general framework. We also propose two novel test statistics that take account of higher moments of the phenotype distribution, in order to accommodate non-normality. These new linkage tests are shown to have high power and to be robust to non-normality. While we have not yet examined the performance of our procedures in the context of selective sampling via computer simulations, the proposed tests satisfy all of the other qualities of an ideal quantitative trait linkage analysis method.

Three dimensional finite element simulation of polymer melting and flow in a single-screw extruder : optimization of screw channel geometry

Single-screw extrusion is one of the widely used processing methods in plastics industry, which was the third largest manufacturing industry in the United States in 2007 [5]. In order to optimize the single-screw extrusion process, tremendous efforts have been devoted for development of accurate models in the last fifty years, especially for polymer melting in screw extruders. This has led to a good qualitative understanding of the melting process; however, quantitative predictions of melting from various models often have a large error in comparison to the experimental data. Thus, even nowadays, process parameters and the geometry of the extruder channel for the single-screw extrusion are determined by trial and error. Since new polymers are developed frequently, finding the optimum parameters to extrude these polymers by trial and error is costly and time consuming. In order to reduce the time and experimental work required for optimizing the process parameters and the geometry of the extruder channel for a given polymer, the main goal of this research was to perform a coordinated experimental and numerical investigation of melting in screw extrusion. In this work, a full three-dimensional finite element simulation of the two-phase flow in the melting and metering zones of a single-screw extruder was performed by solving the conservation equations for mass, momentum, and energy. The only attempt for such a three-dimensional simulation of melting in screw extruder was more than twenty years back. However, that work had only a limited success because of the capability of computers and mathematical algorithms available at that time. The dramatic improvement of computational power and mathematical knowledge now make it possible to run full 3-D simulations of two-phase flow in single-screw extruders on a desktop PC. In order to verify the numerical predictions from the full 3-D simulations of two-phase flow in single-screw extruders, a detailed experimental study was performed. This experimental study included Maddock screw-freezing experiments, Screw Simulator experiments and material characterization experiments. Maddock screw-freezing experiments were performed in order to visualize the melting profile along the single-screw extruder channel with different screw geometry configurations. These melting profiles were compared with the simulation results. Screw Simulator experiments were performed to collect the shear stress and melting flux data for various polymers. Cone and plate viscometer experiments were performed to obtain the shear viscosity data which is needed in the simulations. An optimization code was developed to optimize two screw geometry parameters, namely, screw lead (pitch) and depth in the metering section of a single-screw extruder, such that the output rate of the extruder was maximized without exceeding the maximum temperature value specified at the exit of the extruder. This optimization code used a mesh partitioning technique in order to obtain the flow domain. The simulations in this flow domain was performed using the code developed to simulate the two-phase flow in single-screw extruders.

Micro combined heat and power laboratory development

Micro Combined Heat and Power (Micro-CHP) system produces both electricity and heat required for residential or small business applications. Use of Micro-CHP in a residential application not only creates energy and economic savings but also reduces the carbon foot print of the house or small business. Additionally, micro-CHP can subsidize its cost of operation by selling excess electricity produced back to the grid. Even though Micro-CHP remains attractive on paper, high initial cost and optimization issues in residential scale heat and electrical requirement has kept this technology from becoming a success. To understand and overcome all disadvantages posed my Micro-CHP system, a laboratory is developed to test different scenarios of Micro-CHP applications so that we can learn and improve the current technology. This report focuses on the development of this Micro-CHP laboratory including installation of Ecopower micro-CHP unit, developing fuel line and exhaust line for Ecopower unit, design of electrical and thermal loop, installing all the instrumentation required for data collection on the Ecopower unit and developing controls for heat load simulation using thermal loop. Also a simulation of Micro-CHP running on Syngas is done in Matlab. This work was supported through the donation of ‘Ecopower’ a Micro-CHP unit by Marathon Engine and through the support of Michigan Tech REF-IF grand.

Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

Optimal game theoretic distributed control methodologies in small scale power systems

This dissertation presents the competitive control methodologies for small-scale power system (SSPS). A SSPS is a collection of sources and loads that shares a common network which can be isolated during terrestrial disturbances. Micro-grids, naval ship electric power systems (NSEPS), aircraft power systems and telecommunication system power systems are typical examples of SSPS. The analysis and development of control systems for small-scale power systems (SSPS) lacks a defined slack bus. In addition, a change of a load or source will influence the real time system parameters of the system. Therefore, the control system should provide the required flexibility, to ensure operation as a single aggregated system. In most of the cases of a SSPS the sources and loads must be equipped with power electronic interfaces which can be modeled as a dynamic controllable quantity. The mathematical formulation of the micro-grid is carried out with the help of game theory, optimal control and fundamental theory of electrical power systems. Then the micro-grid can be viewed as a dynamical multi-objective optimization problem with nonlinear objectives and variables. Basically detailed analysis was done with optimal solutions with regards to start up transient modeling, bus selection modeling and level of communication within the micro-grids. In each approach a detail mathematical model is formed to observe the system response. The differential game theoretic approach was also used for modeling and optimization of startup transients. The startup transient controller was implemented with open loop, PI and feedback control methodologies. Then the hardware implementation was carried out to validate the theoretical results. The proposed game theoretic controller shows higher performances over traditional the PI controller during startup. In addition, the optimal transient surface is necessary while implementing the feedback controller for startup transient. Further, the experimental results are in agreement with the theoretical simulation. The bus selection and team communication was modeled with discrete and continuous game theory models. Although players have multiple choices, this controller is capable of choosing the optimum bus. Next the team communication structures are able to optimize the players’ Nash equilibrium point. All mathematical models are based on the local information of the load or source. As a result, these models are the keys to developing accurate distributed controllers.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

DISTRIBUTED APPROACH FOR SOLVING OPTIMAL POWER FLOW PROBLEMS IN THREE-PHASE UNBALANCED DISTRIBUTION NETWORK

The objective of this report is to study distributed (decentralized) three phase optimal power flow (OPF) problem in unbalanced power distribution networks. A full three phase representation of the distribution networks is considered to account for the highly unbalance state of the distribution networks. All distribution network’s series/shunt components, and load types/combinations had been modeled on commercial version of General Algebraic Modeling System (GAMS), the high-level modeling system for mathematical programming and optimization. The OPF problem has been successfully implemented and solved in a centralized approach and distributed approach, where the objective is to minimize the active power losses in the entire system. The study was implemented on the IEEE-37 Node Test Feeder. A detailed discussion of all problem sides and aspects starting from the basics has been provided in this study. Full simulation results have been provided at the end of the report.

DESIGN AND IMPLEMENT DYNAMIC PROGRAMMING BASED DISCRETE POWER LEVEL SMART HOME SCHEDULING USING FPGA

With the development and capabilities of the Smart Home system, people today are entering an era in which household appliances are no longer just controlled by people, but also operated by a Smart System. This results in a more efficient, convenient, comfortable, and environmentally friendly living environment. A critical part of the Smart Home system is Home Automation, which means that there is a Micro-Controller Unit (MCU) to control all the household appliances and schedule their operating times. This reduces electricity bills by shifting amounts of power consumption from the on-peak hour consumption to the off-peak hour consumption, in terms of different “hour price”. In this paper, we propose an algorithm for scheduling multi-user power consumption and implement it on an FPGA board, using it as the MCU. This algorithm for discrete power level tasks scheduling is based on dynamic programming, which could find a scheduling solution close to the optimal one. We chose FPGA as our system’s controller because FPGA has low complexity, parallel processing capability, a large amount of I/O interface for further development and is programmable on both software and hardware. In conclusion, it costs little time running on FPGA board and the solution obtained is good enough for the consumers.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.

A COMPARATIVE STUDY OF HEURISTIC OPTIMIZATION ALGORITHMS

Heuristic optimization algorithms are of great importance for reaching solutions to various real world problems. These algorithms have a wide range of applications such as cost reduction, artificial intelligence, and medicine. By the term cost, one could imply that that cost is associated with, for instance, the value of a function of several independent variables. Often, when dealing with engineering problems, we want to minimize the value of a function in order to achieve an optimum, or to maximize another parameter which increases with a decrease in the cost (the value of this function). The heuristic cost reduction algorithms work by finding the optimum values of the independent variables for which the value of the function (the “cost”) is the minimum. There is an abundance of heuristic cost reduction algorithms to choose from. We will start with a discussion of various optimization algorithms such as Memetic algorithms, force-directed placement, and evolution-based algorithms. Following this initial discussion, we will take up the working of three algorithms and implement the same in MATLAB. The focus of this report is to provide detailed information on the working of three different heuristic optimization algorithms, and conclude with a comparative study on the performance of these algorithms when implemented in MATLAB. In this report, the three algorithms we will take in to consideration will be the non-adaptive simulated annealing algorithm, the adaptive simulated annealing algorithm, and random restart hill climbing algorithm. The algorithms are heuristic in nature, that is, the solution these achieve may not be the best of all the solutions but provide a means to reach a quick solution that may be a reasonably good solution without taking an indefinite time to implement.

Improvement of cardiac function with device-based diaphragmatic stimulation in chronic heart failure patients: the randomized, open-label, crossover Epiphrenic II Pilot Trial.

AIMS Device-based pacing-induced diaphragmatic stimulation (PIDS) may have therapeutic potential for chronic heart failure (HF) patients. We studied the effects of PIDS on cardiac function and functional outcomes. METHODS AND RESULTS In 24 chronic HF patients with CRT, an additional electrode was attached to the left diaphragm. Randomized into two groups, patients received the following PIDS modes for 3 weeks in a different sequence: (i) PIDS off (control group); (ii) PIDS 0 ms mode (PIDS simultaneously with ventricular CRT pulse); or (iii) PIDS optimized mode (PIDS with optimized delay to ventricular CRT pulse). For PIDS optimization, acoustic cardiography was used. Effects of each PIDS mode on dyspnoea, power during exercise testing, and LVEF were assessed. Dyspnoea improved with the PIDS 0 ms mode (P = 0.057) and the PIDS optimized mode (P = 0.034) as compared with the control group. Maximal power increased from median 100.5 W in the control group to 104.0 W in the PIDS 0 ms mode (P = 0.092) and 109.5 W in the PIDS optimized mode (P = 0.022). Median LVEF was 33.5% in the control group, 33.0% in the PIDS 0 ms mode, and 37.0% in the PIDS optimized mode (P = 0.763 and P = 0.009 as compared with the control group, respectively). PIDS was asymptomatic in all patients. CONCLUSION PIDS improves dyspnoea, working capacity, and LVEF in chronic HF patients over a 3 week period in addition to CRT. This pilot study demonstrates proof of principle of an innovative technology which should be confirmed in a larger sample. TRIAL REGISTRATION NCT00769678.

Towards End-User Driven Power Saving Control in Android devices

Abstract. During the last decade mobile communications increasingly became part of people's daily routine. Such usage raises new challenges regarding devices' battery lifetime management when using most popular wireless access technologies, such as IEEE 802.11. This paper investigates the energy/delay trade-off of using an end-user driven power saving approach, when compared with the standard IEEE 802.11 power saving algorithms. The assessment was conducted in a real testbed using an Android mobile phone and high-precision energy measurement hardware. The results show clear energy benefits of employing user-driven power saving techniques, when compared with other standard approaches.

Compact low-power cortical recording architecture for compressive multichannel data acquisition

This paper introduces an area- and power-efficient approach for compressive recording of cortical signals used in an implantable system prior to transmission. Recent research on compressive sensing has shown promising results for sub-Nyquist sampling of sparse biological signals. Still, any large-scale implementation of this technique faces critical issues caused by the increased hardware intensity. The cost of implementing compressive sensing in a multichannel system in terms of area usage can be significantly higher than a conventional data acquisition system without compression. To tackle this issue, a new multichannel compressive sensing scheme which exploits the spatial sparsity of the signals recorded from the electrodes of the sensor array is proposed. The analysis shows that using this method, the power efficiency is preserved to a great extent while the area overhead is significantly reduced resulting in an improved power-area product. The proposed circuit architecture is implemented in a UMC 0.18 [Formula: see text]m CMOS technology. Extensive performance analysis and design optimization has been done resulting in a low-noise, compact and power-efficient implementation. The results of simulations and subsequent reconstructions show the possibility of recovering fourfold compressed intracranial EEG signals with an SNR as high as 21.8 dB, while consuming 10.5 [Formula: see text]W of power within an effective area of 250 [Formula: see text]m × 250 [Formula: see text]m per channel.

Regulating a Benzodifuran Single Molecule Redox Switch via Electrochemical Gating and Optimization of Molecule/Electrode Coupling

We report a novel strategy for the regulation of charge transport through single molecule junctions via the combination of external stimuli of electrode potential, internal modulation of molecular structures, and optimization of anchoring groups. We have designed redox-active benzodifuran (BDF) compounds as functional electronic units to fabricate metal–molecule–metal (m–M–m) junction devices by scanning tunneling microscopy (STM) and mechanically controllable break junctions (MCBJ). The conductance of thiol-terminated BDF can be tuned by changing the electrode potentials showing clearly an off/on/off single molecule redox switching effect. To optimize the response, a BDF molecule tailored with carbodithioate (−CS2–) anchoring groups was synthesized. Our studies show that replacement of thiol by carbodithioate not only enhances the junction conductance but also substantially improves the switching effect by enhancing the on/off ratio from 2.5 to 8.