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The development of base metal electrodes that can act as active and stable oxygen generating electrodes in water electrolysis systems, especially at low pH levels, remains a challenge. The use of suspensions as electrolytes for water splitting has until recently been limited to photoelectrocatalytic approaches. A high current density (j=30 mA/cm2) for water electrolysis has been achieved at a very low oxygen evolution reaction (OER) potential (E=1.36 V vs. RHE) using a SnO2/H2SO4 suspension-based electrolyte in combination with a steel anode. More importantly, the high charge-to-oxygen conversion rate (Faraday efficiency of 88% for OER at j=10 mA/cm2 current density). Since cyclic voltammetry (CV) experiments show that oxygen evolution starts at a low, but not exceptionally low, potential, the reason for the low potential in chronoamperometry (CP) tests is an increase in the active electrode area, which has been confirmed by various experiments. For the first time, the addition of a relatively small amount of solids to a clear electrolyte has been shown to significantly reduce the overpotential of the OER in water electrolysis down to the 100 mV region, resulting in a remarkable reduction in anode wear while maintaining a high current density.
Background
The current development of sensor technologies towards ever more cost-effective and powerful systems is steadily increasing the application of low-cost sensors in different horticultural sectors. In plant in vitro culture, as a fundamental technique for plant breeding and plant propagation, the majority of evaluation methods to describe the performance of these cultures are based on destructive approaches, limiting data to unique endpoint measurements. Therefore, a non-destructive phenotyping system capable of automated, continuous and objective quantification of in vitro plant traits is desirable.
Results
An automated low-cost multi-sensor system acquiring phenotypic data of plant in vitro cultures was developed and evaluated. Unique hardware and software components were selected to construct a xyz-scanning system with an adequate accuracy for consistent data acquisition. Relevant plant growth predictors, such as projected area of explants and average canopy height were determined employing multi-sensory imaging and various developmental processes could be monitored and documented. The validation of the RGB image segmentation pipeline using a random forest classifier revealed very strong correlation with manual pixel annotation. Depth imaging by a laser distance sensor of plant in vitro cultures enabled the description of the dynamic behavior of the average canopy height, the maximum plant height, but also the culture media height and volume. Projected plant area in depth data by RANSAC (random sample consensus) segmentation approach well matched the projected plant area by RGB image processing pipeline. In addition, a successful proof of concept for in situ spectral fluorescence monitoring was achieved and challenges of thermal imaging were documented. Potential use cases for the digital quantification of key performance parameters in research and commercial application are discussed.
Conclusion
The technical realization of “Phenomenon” allows phenotyping of plant in vitro cultures under highly challenging conditions and enables multi-sensory monitoring through closed vessels, ensuring the aseptic status of the cultures. Automated sensor application in plant tissue culture promises great potential for a non-destructive growth analysis enhancing commercial propagation as well as enabling research with novel digital parameters recorded over time.
This paper introduces ideas to reduce talent scarcity by binding female talent in India. As a theoretical lens Neo-Institutionalism in the Indian context is combined with the family-relatedness of work decision model. The qualitative research design and first results as well as propositions for companies are included.
Career Decisions of Indian Female Talent: Implications for Gender-sensitive Talent Management
(2020)
Purpose: Talent scarcity in emerging economies such as India poses challenges for companies,and limited labour market participation among well-educated women has been observed. The reasons that professionals decide not to pursue a further corporate career remain unclear. By investigating career decision making, this article aims to highlight (1) the contextual factors that impact those decisions, (2) individuals’ agency to handle them, and (3) the implications for talent management (TM).
Design/methodology/approach: Following a qualitative research design, computer-aided analysis was conducted on interviews with 24 internationally experienced Indian business professionals. A novel application of neo-institutionalism in the Indian context was combined with the family-relatedness of work decisions (FRWD) model.
Findings: Career decisions indicate that rebellion against Indian societal and family expectations is essential to following a career path, especially for women. TM as part of the current institutional framework serves as a legitimising façade veiling traditional practices that hinder females’ careers.
Research limitations: Interviewees adopted a retrospective perspective when describing their career decisions; therefore, different views might have existed at the moment of decision making.
Practical implications: Design and implementation of gender-sensitive TM adjusted to fit the specific Indian context can contribute to retaining female talent in companies and the labour market.
Originality/value: The importance of gender-sensitive TM can be concluded from an empirical study of the context-based career decision making of experienced business professionals from India. The synthesis of neo-institutionalism, the FRWD model and the research results provides assistance in mapping talent experiences and implications for overcoming the challenges of talent scarcity in India.
Talent scarcity in many parts of the world leads to the necessity to enlarge talent pools in order to provide enough future holders of key positions. Taking the scholarly discussion at the overlap of talent management and current careers literature as a starting point our qualitative empirical research provides insights in talent’s career decisions in an eastern emerging market, India, and a western developed country, Germany. 49 interviews with internationally experienced knowledge-workers were held to find out how to they come to career decisions throughout their career. Special focus was the balancing act of professional and private life sphere. An inductive-deductive approach was used to develop categories in MaxQda. Results show the impact of institutional frame, cultural context, and gender differences. Consequently, a stronger focus on talent’s different life phases with context specific deviations when configuring Talent Management in Multinational Enterprises can be advised.
HRM processes are increasingly AI-driven, and HRM supports the general digital transformation of companies’ viable competitiveness. This paper points out possible positive and negative effects on HRM, workplaces, and workersorganizations along the HR processes and its potential for competitive advantage in regard to managerial decisions on AI implementation regarding augmentation and automation of work.
A systematic literature review that includes 62 international journals across different disciplines and contains top-tier academic and German practitioner journals was conducted. The literature analysis applies the resource-based view (RBV) as a lens through which to explore AI-driven HRM as a potential source of organizational capabilities.
The analysis shows four ambiguities for AI-driven HRM that might support sustainable company development or might prevent AI application: job design, transparency, performance and data ambiguity. A limited scholarly discussion with very few empirical studies can be stated. To date, research has mainly focused on HRM in general, recruiting, and HR analytics in particular.
The four ambiguities’ context-specific potential for capability building in firms is indicated, and research avenues are developed.
This paper critically explores AI-driven HRM and structures context-specific potential for capability building along four ambiguities that must be addressed by HRM to strategically contribute to an organization’s competitive advantage.
Despite normal neurological bedside and electrodiagnostic, some patients with non-specific neck arm pain (NSNAP) have heightened nerve mechanosensitivity upon neurodynamic testing [1, 2]. It remains however unclear whether this is associated with a minor nerve injury. The aim of this study was to evaluate potential differences in somatosensory function among patients with unilateral NSNAP with and without positive neurodynamic tests and healthy controls.
Quantitative sensory testing was performed in 40 patients with unilateral NSNAP; 23 with positive upper limb neurodynamic tests (ULNTPOS) and 17 with negative neurodynamic tests (ULNTNEG). The protocol comprised thermal and mechanical detection and pain thresholds as well as mechanical pain sensitivity, wind-up ratio and dynamic mechanical allodynia. All parameters were measured in the maximal pain area on the affected side as well as over the corresponding area on the unaffected side. Symptom severity, functional deficits, psychological parameters, quality of life and sleep disturbance were also recorded.
Fifty-seven percent of patients with NSNAP had positive neurodynamic tests despite normal bedside neurological integrity tests and nerve conduction parameters. Clinical profiles did not differ between patient groups. Somatosensory profiling revealed a more pronounced loss of function phenotype in ULNTPOS patients compared to healthy controls. Hyperalgesia (cold, heat and pressure pain) was present bilaterally in both NSNAP group. The ULNTNEG subgroup represented an intermediate phenotype between ULNTPOS patients and healthy controls in both thermal and pressure pain thresholds as well as mechanical detection thresholds.
In conclusion, heightened nerve mechanosensitivity was present in over half of patients with NSNAP. Our data suggest that NSNAP presents as a spectrum with some patients showing signs suggestive of a minor nerve dysfunction.
[1] Elvey RL. Physical evaluation of the peripheral nervous system in disorders of pain and dysfunction. J Hand Ther 1997;10:122-129.
[2] van der Heide B, Bourgoin C, Eils G, Garnevall B, Blackmore M. Test-retest reliability and face validity of a modified neural tissue provocation test in patients with cervicobrachial pain syndrome. J Man Manip Ther 2006;14:30-36.
Technological support options for the usage of Brazilian Açaí berries in the European Food Market
(2022)
The highly perishable fruit açaí grows on palm trees in northern Brazil and is colloquially known as a berry with high nutritional value. The seed of the drupe makes up around 85 percent of the fruits weight and only the pulp around the seed is used for human consumption. The manufacturing step after harvest includes the pulping and the preservation of the fruit. The preservation step is necessary, because the açaí pulp contains a high microbial load. There are several preservation processes including the use of chlorinated or ozonated water, alcoholic fermentation, pasteurization, freezing or dehydration. Those techniques are overall not very gentle and have the potential to leave residues in the final product, which can change its typical sensorial characteristics. Therefore, an experiment was conducted, to see if a relatively new gentle preservation method called PEF can reduce the microbial load in an açaí- smoothie.
For this purpose, a PEF-machine was built and verified based on the paper from HEINZ ET AL. [2003]. The self-built machine works efficiently, when there is a reduction of microorganisms like Escherichia coli in apple juice due to the induced Pulsed Electric Fields. If this is the case, the described experiment with açaí-smoothie can be carried out with the self-built PEF- machine. In this experiment the results of the validation of this PEF-machine were not comparable to those from the paper from HEINZ ET AL. [2003]. So, the self-built PEF-machine in Brazil did not work sufficiently. Hence, the experiment which should show that a reduction of microorganisms, such as Escherichia coli, in açaí-smoothie with PEF is possible, was performed in Germany. It was accrued out at ELEA with using the PEFPilotTM Dual. This experiment confirmed the assumption, that microorganisms can be reduced in açaí-smoothie with PEF. Escherichia coli was reduced by 2 logs, Saccharomyces cerevisiae by 3 logs and Lactobacillus plantarum by 6 logs. And a comparison between PEF and the known preservation methods for açaí showed that it can be a compatible alternative.
Moreover, the topic, how açaí fits into the European Food Market is answered within this paper. When offering açaí food products to the European population, ideas can be originated from the well-working Brazilian market. It can be helpful to mix açaí with known European fruits for a better acceptance by the people. Then açaí can help to meet the Europeans needs of the current time for fresh and healthy food, especially when preserved with PEF. Furthermore, it is important to work towards a sustainable supply chain system from the cultivation until the unloading at the destination in Europe. Sustainability is important for the integration in the European market, not only for environmental protection, but also in terms of social stability and marketing purposes. In addition, access requirements, further food-related regulations, and the seasonality of açaí present a major hurdle.
Building on this thesis, further papers shall be written, not only in the field of the preservation of the açaí pulp with PEF, but also in the direction of combined preservation methods for açaí, the sustainable usage of the açaí seeds, product innovations containing the Brazilian fruit or various market research.
The Internet of Things (IoT) relies on sensor devices to measure real-world phenomena in order to provide IoT services. The sensor readings are shared with multiple entities, such as IoT services, other IoT devices or other third parties. The collected data may be sensitive and include personal information. To protect the privacy of the users, the data needs to be protected through an encryption algorithm. For sharing cryptographic cipher-texts with a group of users Attribute-Based Encryption (ABE) is well suited, as it does not require to create group keys. However, the creation of ABE cipher-texts is slow when executed on resource constraint devices, such as IoT sensors. In this paper, we present a modification of an ABE scheme, which not only allows to encrypt data efficiently using ABE, but also reduces the size of the cipher-text, that must be transmitted by the sensor. We also show how our modification can be used to realise an instantaneous key revocation mechanism.
The Internet of Things (IoT) is the enabler for new innovations in several domains. It allows the connection of digital services with real, physical entities. These entities are devices of different categories and range in size from large machinery to tiny sensors. In the latter case, devices are typically characterized by limited resources in terms of computational power, available memory and sometimes limited power supply. As a consequence, the use of security algorithms requires expert knowledge in order for them to work within the limited resources. That means to find a suitable configuration for the algorithms to perform properly on the device. On the other side, there is the desire to protect valuable assets as strong as possible. Usually, security goals are captured in security policies, but they do not consider resource availability on the involved device and their consumption while executing security algorithms. This paper presents a resource aware information exchange model and a generation tool that uses high-level security policies as input. The model forms the conceptual basis for an automated security configuration recommendation system.