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Psychological Capital as Mediator between Transformational Leadership and Adaptive Performance
(2013)
Quantum systems are typically subject to various environmental noise sources. Treating these environmental disturbances with a system-bath approach beyond weak coupling, one must refer to numerical methods as, for example, the numerically exact quasi-adiabatic path integral approach. This approach, however, cannot treat baths which couple to the system via operators, which do not commute. We extend the quasi-adiabatic path integral approach by determining the time discrete influence functional for such non-commuting fluctuations and by modifying the propagation scheme accordingly. We test the extended quasi-adiabatic path integral approach by determining the time evolution of a quantum two-level system coupled to two independent baths via non-commuting operators. We show that the convergent results can be obtained and agreement with the analytical weak coupling results is achieved in the respective limits.
The development of deep learning-based optical chemical structure recognition (OCSR) systems has led to a need for datasets of chemical structure depictions. The diversity of the features in the training data is an important factor for the generation of deep learning systems that generalise well and are not overfit to a specific type of input. In the case of chemical structure depictions, these features are defined by the depiction parameters such as bond length, line thickness, label font style and many others. Here we present RanDepict, a toolkit for the creation of diverse sets of chemical structure depictions. The diversity of the image features is generated by making use of all available depiction parameters in the depiction functionalities of the CDK, RDKit, and Indigo. Furthermore, there is the option to enhance and augment the image with features such as curved arrows, chemical labels around the structure, or other kinds of distortions. Using depiction feature fingerprints, RanDepict ensures diversely picked image features. Here, the depiction and augmentation features are summarised in binary vectors and the MaxMin algorithm is used to pick diverse samples out of all valid options. By making all resources described herein publicly available, we hope to contribute to the development of deep learning-based OCSR systems.
The development of deep learning-based optical chemical structure recognition (OCSR) systems has led to a need for datasets of chemical structure depictions. The diversity of the features in the training data is an important factor for the generation of deep learning systems that generalise well and are not overfit to a specific type of input. In the case of chemical structure depictions, these features are defined by the depiction parameters such as bond length, line thickness, label font style and many others. Here we present RanDepict, a toolkit for the creation of diverse sets of chemical structure depictions. The diversity of the image features is generated by making use of all available depiction parameters in the depiction functionalities of the CDK, RDKit, and Indigo. Furthermore, there is the option to enhance and augment the image with features such as curved arrows, chemical labels around the structure, or other kinds of distortions. Using depiction feature fingerprints, RanDepict ensures diversely picked image features. Here, the depiction and augmentation features are summarised in binary vectors and the MaxMin algorithm is used to pick diverse samples out of all valid options. By making all resources described herein publicly available, we hope to contribute to the development of deep learning-based OCSR systems.
Recommendations for the Development of a Robotic Drinking and Eating Aid - An Ethnographic Study
(2021)
Being able to live independently and self-determined in one’s own home is a crucial factor or human dignity and preservation of self-worth. For people with severe physical impairments who cannot use their limbs for every day tasks, living in their own home is only possible with assistance from others. The inability to move arms and hands makes it hard to take care of oneself, e.g. drinking and eating independently. In this paper, we investigate how 15 participants with disabilities consume food and drinks. We report on interviews, participatory observations, and analyzed the aids they currently use. Based on our findings, we derive a set of recommendations that supports researchers and practitioners in designing future robotic drinking and eating aids for people with disabilities.
In the realm of digital situational awareness during disaster situations, accurate digital representations,
like 3D models, play an indispensable role. To ensure the
safety of rescue teams, robotic platforms are often deployed
to generate these models. In this paper, we introduce an
innovative approach that synergizes the capabilities of compact Unmaned Arial Vehicles (UAVs), smaller than 30 cm, equipped with 360° cameras and the advances of Neural Radiance Fields (NeRFs). A NeRF, a specialized neural network, can deduce a 3D representation of any scene using 2D images and then synthesize it from various angles upon request. This method is especially tailored for urban environments which have experienced significant destruction, where the structural integrity of buildings is compromised to the point of barring entry—commonly observed post-earthquakes and after severe fires. We have tested our approach through recent post-fire scenario, underlining the efficacy of NeRFs even in challenging outdoor environments characterized by water, snow, varying light conditions, and reflective surfaces.
Cone-Beam computed tomography (CBCT) has become the most important component of modern radiotherapy for positioning tumor patients directly before treatment. In this work we investigate alternations to standard acquisition protocol, called preset, for patients with a tumor in the thoracic region. The effects of the changed acquisition parameters on the image quality are evaluated using the Catphan Phantom and the image analysis software Smári. The weighted CT dose index (CTDIW) is determined in each case and the effects of the different acquisition protocols on the patient dose are classified accordingly. Additionally, the clinical suitability of alternative presets is tested by investigating correctness of image registration using the CIRS thorax phantom. The results show that a significant dose reduction can be achieved. It can be reduced by 51% for a full rotation by adjusting the gantry speed.
The purpose of the paper is to contribute to the inner workings of transformational leadership in the context of organizational change. According to the organizational role theory, role conflict is proposed as a mediator between transformational leadership and affective commitment to change and irritation. Cross-sectional data were collected in a German company in the textiles sector, undergoing a pervasive IT-related change. Confirmatory factor analysis and structural equation modeling was performed for validity and hypothesis testing. The findings suggest that role conflict acts as a full mediator in the relationship between transformational leadership and affective commitment to change, as well as irritation. Transformational leadership is often discussed in terms of change-oriented leadership. Surprisingly, only a few studies have examined the specific impact of transformational leadership on attitudinal outcomes during change processes, yet. Consequently, research on the underlying psychological mechanisms of the relationship is scarce, too.
The concept of molecular scaffolds as defining core structures of organic molecules is utilised in many areas of chemistry and cheminformatics, e.g. drug design, chemical classification, or the analysis of high-throughput screening data. Here, we present Scaffold Generator, a comprehensive open library for the generation, handling, and display of molecular scaffolds, scaffold trees and networks. The new library is based on the Chemistry Development Kit (CDK) and highly customisable through multiple settings, e.g. five different structural framework definitions are available. For display of scaffold hierarchies, the open GraphStream Java library is utilised. Performance snapshots with natural products (NP) from the COCONUT database and drug molecules from DrugBank are reported. The generation of a scaffold network from more than 450,000 NP can be achieved within a single day.
The concept of molecular scaffolds as defining core structures of organic molecules is utilised in many areas of chemistry and cheminformatics, e.g. drug design, chemical classification, or the analysis of high-throughput screening data. Here, we present Scaffold Generator, a comprehensive open library for the generation, handling, and display of molecular scaffolds, scaffold trees and networks. The new library is based on the Chemistry Development Kit (CDK) and highly customisable through multiple settings, e.g. five different structural framework definitions are available. For display of scaffold hierarchies, the open GraphStream Java library is utilised. Performance snapshots with natural products (NP) from the COCONUT (COlleCtion of Open Natural prodUcTs) database and drug molecules from DrugBank are reported. The generation of a scaffold network from more than 450,000 NP can be achieved within a single day.
Segmentation of radio-angiographic images using morphological filters, thinning and region growing
(1997)
As vaccination campaigns are in progress in most countries, hopes to win back more normality are rising. However, the exact path from a pandemic to an endemic virus remains uncertain. While in the pre-vaccination phase many critical indoor situations were avoided by strict control measures, for the transition phase a certain mitigation of the effect of indoor situations seems advisable.
To better understand the mechanisms of indoor airborne transmissions, we present a new time-discrete model to calculate the level of exposure towards infectious SARS-CoV-2 aerosol and carry out a sensitivity analysis for the level of SARS-CoV-2 aerosol exposure in indoor settings. Time limitations and the use of any kind of masks were found to be strong mitigation measures, while how far the effort for a strict use of professional face pieces instead of simple masks can be justified by the additional reduction of the exposure dose remains unclear. Very good ventilation of indoor spaces is mandatory. The definition of sufficient ventilation in regard to airborne SARS-CoV-2 transmission follows other rules than the standards in ventilation design. This means that especially smaller rooms most likely require a significantly greater fresh air supply than usual. Further research on 50% group models in schools is suggested. The benefits of a model in which the students come to school every day, but for a limited time, should be investigated. In terms of window ventilation, it has been found that many short opening periods are not only thermally beneficial, they also reduce the exposure dose. The fresh air supply is driven by the temperature gradient and wind speed. However, the sensitivity towards these parameters is not very high and in times of low wind and temperature gradients, there are no arguments against keep windows open in order to make up for the reduced air flow rate. Long total opening periods and large window surfaces will strongly reduce the exposure. Additionally, the results underline the expectable fact that exposure doses will increase when hygiene and control measures are reduced. It seems advisable to investigate what this means for the infection rate and the fatality of infections in populations with partial immunity. Very basic considerations suggest that the value of aerosol reduction measures may be reduced with very infectious variants such as delta.
Earwig wings are highly foldable structures that lack internal muscles. The behaviour and shape changes of the wings during flight are yet unknown. We assume that they meet a great structural challenge to control the occurring deformations and prevent the wing from collapsing. At the folding structures especially, the wing could easily yield to the pressure. Detailed microscopy studies reveal adaptions in the structure and material which are not relevant for folding purposes. The wing is parted into two structurally different areas with, for example, a different trend or stiffness of the wing veins. The storage of stiff or more flexible material shows critical areas which undergo great changes or stress during flight. We verified this with high-speed video recordings. These reveal the extent of the occurring deformations and their locations, and support our assumptions. The video recordings reveal a dynamical change of a concave flexion line. In the static unfolded state, this flexion line blocks a folding line, so that the wing stays unfolded. However, during flight it extends and blocks a second critical folding line and prevents the wing from collapsing. With these results, more insight in passive wing control, especially within high foldable structures, is gained.
We propose a quantum-mechanical model to calculate the nonlinear differential conductance of a single molecular junction immersed in a solvent, either in pure form or as a binary mixture with varying volume fraction. The solvent mixture is captured by a dielectric continuum model for which the resulting spectral density is determined within the Gladstone-Dale approach. The conductance of the molecular junction is calculated by a real-time diagrammatic technique. We find a strong variation of the conductance maximum for varying volume fraction of the solvent mixture. Importantly, the calculated molecular nonlinear conductance shows a very good agreement with experimentally measured data for common molecular junctions in various polar solvent mixtures.
This technical report is about the architecture and integration of very small commercial UAVs (< 40 cm diagonal) in indoor Search and Rescue missions. One UAV is manually controlled by only one single human operator delivering live video streams and image series for later 3D scene modelling and inspection. In order to assist the operator who has to simultaneously observe the environment and navigate through it we use multiple deep neural networks to provide guided autonomy, automatic object detection and classification and local 3D scene modelling. Our methods help to reduce the cognitive load of the operator. We describe a framework for quick integration of new methods from the field of Deep Learning, enabling for rapid evaluation in real scenarios, including the interaction of methods.
Socio-cultural dynamics in spatial policy: explaining the on-going success of cluster politics
(2013)
When a hydrophilic solute in water is suddenly turned into a hydrophobic species, for instance, by photoionization, a layer of hydrated water molecules forms around the solute on a time scale of a few picoseconds. We study the dynamic buildup of the hydration shell around a hydrophobic solute on the basis of a time-dependent dielectric continuum model. Information about the solvent is spectroscopically extracted from the relaxation dynamics of a test dipole inside a static Onsager sphere in the nonequilibrium solvent. The growth process is described phenomenologically within two approaches. First, we consider a time-dependent thickness of the hydration layer that grows from zero to a finite value over a finite time. Second, we assume a time-dependent complex permittivity within a finite layer region around the Onsager sphere. The layer is modeled as a continuous dielectric with a much slower fluctuation dynamics. We find a time-dependent frequency shift down to the blue of the resonant absorption of the dipole, together with a dynamically decreasing line width, as compared to bulk water. The blue shift reflects the work performed against the hydrogen-bonded network of the bulk solvent and is a directly measurable quantity. Our results are in agreement with an experiment on the hydrophobic solvation of iodine in water.
SPICES (Simplified Particle Input ConnEction Specification) is a particle-based molecular structure representation derived from straightforward simplifications of the atom-based SMILES line notation. It aims at supporting tedious and error-prone molecular structure definitions for particle-based mesoscopic simulation techniques like Dissipative Particle Dynamics by allowing for an interplay of different molecular encoding levels that range from topological line notations and corresponding particle-graph visualizations to 3D structures with support of their spatial mapping into a simulation box. An open Java library for SPICES structure handling and mesoscopic simulation support in combination with an open Java Graphical User Interface viewer application for visual topological inspection of SPICES definitions are provided.
This report gives a brief overview to the state of the art of PEM fuel cell technology and a description of a newly developed fuel cell stack concept. One main research activity at the Westphalian Energy Institute of the Westphalian University of Applied Sciences is the development of PEM fuel cells, for which a range of different materials have been investigated for fuel cell pole plate construction. Whereas graphite is a material which has suitable properties concerning conductivity as well as manufacturing e.g. for milling, stainless steel foils are suitable for economical hydroforming processes. However, with steel coating is necessary to increase corrosion resistance as well as electrical conductivity. A new fuel cell stack design is currently under development using separated single fuel cells with hydraulic cell compression. The advantages of this stack concept are modularity, effective heat exchanging and constant, uniform cell compression which are further described in this work.
The set of transactions that occurs on the public ledger of an Ethereum network in a specific time frame can be represented as a directed graph, with vertices representing addresses and an edge indicating the interaction between two addresses.
While there exists preliminary research on analyzing an Ethereum network by the means of graph analysis, most existing work is focused on either the public Ethereum Mainnet or on analyzing the different semantic transaction layers using static graph analysis in order to carve out the different network properties (such as interconnectivity, degrees of centrality, etc.) needed to characterize a blockchain network. By analyzing the consortium-run bloxberg Proof-of-Authority (PoA) Ethereum network, we show that we can identify suspicious and potentially malicious behaviour of network participants by employing statistical graph analysis. We thereby show that it is possible to identify the potentially malicious
exploitation of an unmetered and weakly secured blockchain network resource. In addition, we show that Temporal Network Analysis is a promising technique to identify the occurrence of anomalies in a PoA Ethereum network.
Steps Towards an Open All-in-one Rich-Client Environment for Particle-Based Mesoscopic Simulation
(2018)
Stereo Camera Setup for 360° Digital Image Correlation to Reveal Smart Structures of Hakea Fruits
(2024)
About forty years after its first application, digital image correlation (DIC) has become an established method for measuring surface displacements and deformations of objects under stress. To date, DIC has been used in a variety of in vitro and in vivo studies to biomechanically characterise biological samples in order to reveal biomimetic principles. However, when surfaces of samples strongly deform or twist, they cannot be thoroughly traced. To overcome this challenge, different DIC setups have been developed to provide additional sensor perspectives and, thus, capture larger parts of an object’s surface. Herein, we discuss current solutions for this multi-perspective DIC, and we present our own approach to a 360 DIC system based on a single stereo-camera setup. Using this setup, we are able to characterise the desiccation-driven opening mechanism of two woody Hakea fruits over their entire surfaces. Both the breaking mechanism and the actuation of the two valves in predominantly dead plant material are models for smart materials. Based on these results, an evaluation of the setup for 360 DIC regarding its use in deducing biomimetic principles is given. Furthermore, we propose a way to improve and apply the method for future measurements.
Social innovations «meet social needs», are «good for society» and «enhance society’s capacity to act». But what does their rising importance tell us about the current state of public policy in Europe and its effectiveness in achieving social and economic goals? Some might see social innovation as a critique of public intervention, filling the gaps left by years of policy failure. Others emphasise the innovative potential of cross-boundary collaboration between the public sector, the private sector, the third sector and the household.
This paper explores the conditions under which the state either enables or constrains effective social innovation by transcending the boundaries between different actors. We argue that social innovation is closely linked to public sector innovation, particularly in relation to new modes of policy production and implementation, and to new forms of organisation within the state that challenge functional demarcations and role definitions.
Neuroscientists want to inspect the data their simulations are producing while these are still running. This will on the one hand save them time waiting for results and therefore insight. On the other, it will allow for more efficient use of CPU time if the simulations are being run on supercomputers. If they had access to the data being generated, neuroscientists could monitor it and take counter-actions, e.g., parameter adjustments, should the simulation deviate too much from in-vivo observations or get stuck.
As a first step toward this goal, we devise an in situ pipeline tailored to the neuroscientific use case. It is capable of recording and transferring simulation data to an analysis/visualization process, while the simulation is still running. The developed libraries are made publicly available as open source projects. We provide a proof-of-concept integration, coupling the neuronal simulator NEST to basic 2D and 3D visualization.
Streptavidin is a 58 kDa tetrameric protein with the highest known affinity to biotin with a wide range of applications in bionanotechnology and molecular biology. Dissolved streptavidin is stable at a broad range of temperature, pH, proteolytic enzymes and exhibits low non‐specific binding. In this study, a streptavidin monolayer was assembled directly on a biotinylated TiO2‐surface to investigate its stability against proteolytic digestion and its suppression of initial bacterial adsorption of Escherichia coli, Bacillus subtilis, and Streptococcus intermedius. In contrast to nonmodified TiO2 surfaces, streptavidin‐coated substrates showed only a negligible non‐specific protein adsorption at physiological protein concentrations as well as a significantly reduced bacterial adhesion. The antiadhesive properties were demonstrated to be the main reason for the suppression of bacterial adhesion, which makes this approach a promising option for future surface biofunctionalization applications.
Streptavidin-coated TiO2 surfaces are biologically inert: Protein adsorption and osteoblast adhesion
(2012)
Non‐fouling TiO2 surfaces are attractive for a wide range of applications such as biosensors and medical devices, where biologically inert surfaces are needed. Typically, this is achieved by controlled surface modifications which prevent protein adsorption. For example, polyethylene glycol (PEG) or PEG‐derived polymers have been widely applied to render TiO2 surfaces biologically inert. These surfaces have been further modified in order to achieve specific bio‐activation. Therefore, there have been efforts to specifically functionalize TiO2 surfaces with polymers with embedded biotin motives, which can be used to couple streptavidin for further functionalization. As an alternative, here a streptavidin layer was immobilized by self‐assembly directly on a biotinylated TiO2 surface, thus forming an anti‐adhesive matrix, which can be selectively bio‐activated. The anti‐adhesive properties of these substrates were analyzed by studying the interaction of the surface coating with fibronectin, lysozym, and osteoblast cells using surface plasmon resonance spectroscopy, atomic force microscopy, and light microscopy. In contrast to non‐modified TiO2 surfaces, streptavidin‐coated TiO2 surfaces led to a very biologically inert substrate, making this type of surface coating a promising alternative to polymer coatings of TiO2 surfaces.
Geometries, stabilities, electronic properties and NMR-shielding of cucurbit[6]uril–spermine host-ligand complexes are investigated with DFT calculations and compared to experimental results. Cucurbit[6]uril and spermine can form complexes with two different minimum energy geometries and corresponding characteristic differences in NMR shielding. The energetically preferred complex geometry has a perfect inversion symmetry and its proton NMR shielding agrees very well with experimental results. The cucurbit[6]uril host molecule shows a distinct geometrical flexibility in ligand binding which allows an induced fit of the spermine ligand. The energetic barrier for the rotation of spermine in the favourable complex is approximated to be in the order of a few kilocalories per mole.
Studies on Pulse Electrodeposition of Pt-Ni binary Alloy For Electrochemical Cell Applications
(2018)
The two-state two-path model is introduced as a minimized model to describe the quantum dynamics of an electronic wave packet in the vicinity of a conical intersection. It involves two electronic potential energy surfaces each of which hosts a pair of quasi-classical trajectories over which the wave packet is assumed to be delocalized. When both trajectories evolve dynamically either diabatically or adiabatically, the full wave packet dynamics shows only features of the dynamics around avoided level crossings in the vicinity of the conical intersection. When one trajectory evolves adiabatically whereas the other trajectory follows a diabatic evolution, quantum mechanical interference of the wave packet components on each path generates Stueckelberg oscillations in the transition probability. These are surprisingly robust against a dissipative environment and, thus, should be a marker for conical intersections.
The two-state two-path model is introduced as a minimized model to describe the quantum dynamics of an electronic wave packet in the vicinity of a conical intersection. It involves two electronic potential energy surfaces each of which hosts a pair of quasi-classical trajectories over which the wave packet is assumed to be delocalized. When both trajectories evolve dynamically either diabatically or adiabatically, the full wave packet dynamics shows only features of the dynamics around avoided level crossings in the vicinity of the conical intersection. When one trajectory evolves adiabatically whereas the other trajectory follows a diabatic evolution, quantum mechanical interference of the wave packet components on each path generates Stueckelberg oscillations in the transition probability. These are surprisingly robust against a dissipative environment and, thus, should be a marker for conical intersections.
We study the nonequilibrium dynamics of a quantum system under the influence of two noncommuting fluctuation sources, i.e., purely dephasing fluctuations and relaxational fluctuations. We find that increasing purely dephasing fluctuations suppress increasing relaxation in the quantum system. This effect is further enhanced when both fluctuation sources are fully correlated. These effects arise for medium to strong primary fluctuations already when the secondary fluctuations are weak due to their noncommuting coupling to the quantum system. Dephasing, in contrast, is increased by increasing any of the two fluctuations. Fully correlated fluctuations result in overdamping at much lower system-bath coupling than uncorrelated noncommuting fluctuations. In total, we observe that treating subdominant secondary environmental fluctuations perturbatively leads, as neglecting them, to erroneous conclusions.
Tunneling two-level systems (TLSs) are ubiquitous in amorphous solids, and form a major source of noise in systems such as nano-mechanical oscillators, single electron transistors, and superconducting qubits. Occurance of defect tunneling despite their coupling to phonons is viewed as a hallmark of weak defect-phonon coupling. This is since strong coupling to phonons results in significant phonon dressing and suppresses tunneling in two-level tunneling defects effectively. Here we determine the dynamics of a tunneling defect in a crystal strongly coupled to phonons incorporating the full 3D geometry in our description. Wefind that inversion symmetric tunneling is not dressed by phonons whereas other tunneling pathways are dressed by phonons and, thus, are suppressed by strong defect-phonon coupling. We provide the linear acoustic and dielectric response functions for a tunneling defect in a crystal for strong defect-phonon coupling. This allows direct experimental determination of the defect-phonon coupling. The singling out of inversion-symmetric tunneling states in single tunneling defects is complementary to their dominance of the low energy excitations in strongly disordered solids as a result of inter-defect interactions for large defect concentrations. This suggests that inversion symmetric TLSs play a unique role in the low energy properties of disordered solids.
Three dinuclear zinc carboxylate complexes [L1−3Zn(μ,η2-O2CPh)]2 (1, 2, 4) containing either the bidentate N,N′-chelating β-diketiminate ligand RNC(Me)C(H)C(Me)NR (R = 2,6-iPr2-C6H3, L1, complex 1), the tridentate O,N,N-chelating ligand OC(Me)C(H)C(Me)NCH2CH2NMe2 (L2, complex 2) or the bis-N,N′-chelating bis-β-diketiminate ligand RNC(Me)C(H)C(Me)NNC(Me)C(H)C(Me)NR (R = 2,6-iPr2-C6H3, L3, complex 4) were synthesized and characterized including single-crystal X-ray diffraction. Reaction of the neutral bis-β-diketimine (L3(H)2) with two equivalents of ZnMe2 leads to the expected heteroleptic dinuclear zinc complex L3(ZnMe)2 3 in 93 % yield. Further reaction with benzoic acid PhCO2H leads to complex 4. Complex 2 forms a rather strong carboxylate-bridged dimer, whereas the carboxylate groups in complexes 1 and 4 act as asymmetrical bridges between both Zn atoms, pointing to the formation of a weakly bonded dimer. The zinc atoms in 1 and 4 are tetrahedrally coordinated, whereas in 2 the coordination number is increased to five due to the coordination of the pendant donor arm. The ring opening polymerization (ROP) of rac-lactide was investigated with the zinc complexes 1–4 and diazabicycloundec-7-ene (DBU) as a co-catalyst. Complexes 2 and 3 are active polymerization catalysts, which in the presence of DBU converted 200 equiv. of rac-lactide into polylactide within 10 min at ambient temperature. The analysis of the crude polymer showed that the lactide polymerization with catalyst 2 occurs via a slightly modified activated-monomer mechanism.
A systematic method for obtaining a novel electrode structure based on PtCoMn ternary alloy catalyst supported on graphitic carbon nanofibers (CNF) for hydrogen evolution reaction (HER) in acidic media is proposed. Ternary alloy nanoparticles (Co0.6Mn0.4 Pt), with a mean crystallite diameter under 10 nm, were electrodeposited onto a graphitic support material using a two-step pulsed deposition technique. Initially, a surface functionalisation of the carbon nanofibers is performed with the aid of oxygen plasma. Subsequently, a short galvanostatic pulse electrodeposition technique is applied. It has been demonstrated that, if pulsing current is employed, compositionally controlled PtCoMn catalysts can be achieved. Variations of metal concentration ratios in the electrolyte and main deposition parameters, such as current density and pulse shape, led to electrodes with relevant catalytic activity towards HER. The samples were further characterised using several physico-chemical methods to reveal their morphology, structure, chemical and electrochemical properties. X-ray diffraction confirms the PtCoMn alloy formation on the graphitic support and energy dispersive X-ray spectroscopy highlights the presence of the three metallic components from the alloy structure. The preliminary tests regarding the electrocatalytic activity of the developed electrodes display promising results compared to commercial Pt/C catalysts. The PtCoMn/CNF electrode exhibits a decrease in hydrogen evolution overpotential of about 250 mV at 40 mA cm−2 in acidic solution (0.5 M H2SO4) when compared to similar platinum based electrodes (Pt/CNF) and a Tafel slope of around 120 mV dec−1, indicating that HER takes place under the Volmer-Heyrovsky mechanism.
Purpose
Although the systemic approach to the leadership concept seems to fit well into our modern complex and dynamic work environment, only little research has been conducted to define and assess systemic leadership. In this study we therefore developed and assessed criterion validity of the
multidimensional systemic leadership inventory (SLI, Sülzenbrück & Externbrink, 2017).
Methodology
We conducted two cross-sectional survey among managers and employees of various organizations (N = 143 and N = 150).
Results
We found a robust five-factor structure of the SLI, comprising systemic thinking, self-knowledge, solution-oriented communication, creating meaning and delegation. Regarding criterion validity, a significant positive correlation of systemic leadership was found with affective commitment, while a significant negative correlation with emotional strain in occupational contexts occurred. These overall positive outcomes for employees were not undermined by negative personality traits of the employee (Machiavellianism), while strong growth need strength further enhanced positive effects on affective commitment.
Limitations
Since all variables were measured as self-reports, common method variance could limit our findings.
Practical Implications
Systemic leadership is a very promising new approach for leaders to ensure committed and less strained employees.
Value
Systemic leadership, especially in terms of a leaders’ understanding of organizational and private systems influencing work behaviour of all members of an organization, is a promising novel leadership model suitable to address challenges of complex and dynamic work environments.
Purpose
So far, there are several approaches of measuring the Dark Triad traits, but still all of them are
personality questionnaires with at least questionable usability for applied contexts such as Human
Resource Management.
The purpose of the study is the development of a structured interview with the aim of measuring the Dark Triad in a rather qualitative way that increases social validity for the respondents.
Design/Methodology/Approach/Intervention
In the present study, 15 executives from the telecommunications industry were interviewed on their personal evaluation of management success and derailment. Afterwards, their personality traits of the Dark Triad were measured with the help of the Short Dark Triad Scale. Subsequently, the data from qualitative and quantitative research were examined for correlations using the mixed-method approach.
Results
The results of the mixed-method approach showed a statistically significant correlation between the Short Dark Triad Scale and the ratings for narcissism, Machiavellianism and subclinical psychopathy in the Dark Triad interview.
Limitations
Replicating the results in a bigger sample and a deeper investigation of the criterion-related validity as well as an integration of multiple raters can provide more confidence in our results.
Research/Practical Implications
Structured interviews allow the measurement of personality traits in a more convenient way especially in personnel selection and development processes. Identifying subclinical traits in leadership candidates can, e.g. prevent management derailment.
Originality/Value
The present study advances the measurement methods of the Dark Triad.
The German supply chain law ( Lieferkettensorgfaltspflichtengesetz, abbreviated: LkSG) which enters into force on 1 January 2023 is part of the developing legal framework for human rights in global supply chains. Like the French vigilance law, it represents a new generation of supply chain laws which impose mandatory human rights due diligence obligations. The LkSG requires enterprises to exercise a number of due diligence obligations – from conducting risk analysis to undertaking preventive measures or remedial actions. The law is based on public enforcement via a competent authority, the Federal Office for Economic Affairs and Export Control (BAFA). The BAFA monitors and enforces compliance with the due diligence obligations. Non-compliant enterprises can be fined with up to 800,000 Euros and, in some cases, up to 2% of the annual turnover. Whilst the LkSG is an important step towards achieving greater corporate sustainability, it also has limitations. It was a political compromise and, as such, it does not include a new civil liability for non-compliance. Moreover, by default, it only applies to the enterprise’s own business area and its direct suppliers, whereas indirect suppliers are only included where the enterprise has substantiated knowledge that an obligation has been violated.
This Article introduces two research projects towards assistive robotic arms for people with severe body impairments. Both projects aim to develop new control and interaction designs to promote accessibility and a better performance for people with functional losses in all four extremities, e.g. due to quadriplegic or multiple sclerosis. The project MobILe concentrates on using a robotic arm as drinking aid and controlling it with smart glasses, eye-tracking and augmented reality. A user oriented development process with participatory methods were pursued which brought new knowledge about the life and care situation of the future target group and the requirements a robotic drinking aid needs to meet. As a consequence the new project DoF-Adaptiv follows an even more participatory approach, including the future target group, their family and professional caregivers from the beginning into decision making and development processes within the project. DoF-Adaptiv aims to simplify the control modalities of assistive robotic arms to enhance the usability of the robotic arm for activities of daily living. lo decide on exemplary activities, like eating or open a door, the future target group, their family and professional caregivers are included in the decision making process. Furthermore all relevant stakeholders will be included in the investigation of ethical, legal and social implications as well as the identification of potential risks. This article will show the importance of the participatory design for the development and research process in MobILe and DoF-Adaptiv.
This paper reveals various approaches undertaken over more than two decades of teaching undergraduate programming classes at different Higher Education Institutions, in order to improve student activation and participation in class and consequently teaching and learning effectiveness.
While new technologies and the ubiquity of smartphones and internet access has brought new tools to the classroom and opened new didactic approaches, lessons learned from this personal long-term study show that neither technology itself nor any single new and often hyped didactic approach ensured sustained improvement of student activation. Rather it needs an integrated yet open approach towards a participative learning space supported but not created by new tools, technology and innovative teaching methods.
The article highlights gender codes in design, particularly in web design, by means of current examples. Different aspects of gender-specific design are looked at in detail and their inherent problems discussed: on the one hand the development of a special solution (gender-specific for women), on the other hand, web design with reduced functionality and simplification of information (i.e. image representation) which sometimes even leads to a negation of technology. The article illustrates that gender codes and stereotypical role models can be embodied on different design levels of web design (use and artefact): in structure/navigation, in creative elements by the use of shape, colour and imagery and on a textual level. These design decisions have an impact on the power of users to act, their individual gender identity and the structural gender identity/social perception of gender. The article demonstrates that gender codes in current web design are very present and aims to sensitize the topic.
The disruptive nature of the changing media landscape and technology-driven advances in communication have led to innovative ways of organizing work in the information and communication industry. This reorganization of work is reflected in the concept of New Work, which rethinks working concepts, styles, and employee behavior. Based on a survey among staff in the information and communication industry (n = 380), this study investigates the status quo of the implementation of New Work measures and their effectiveness in helping companies reach organizational goals. The results show that New Work measures are widely adopted although there is still unused potential. Moreover, the study demonstrates that the implementation of New Work measures supports companies in achieving New Work goals as well as overall organizational goals in the contexts of agile management, change management, internal communication, and evaluation.