Search results for: German language-specific bias

Authors: Breanna Wright, Peter Bragge

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Diagnostic error rates in healthcare are approximately 10% of cases. Diagnostic errors can cause patient harm due to inappropriate, inadequate or delayed treatment, and such errors contribute heavily to medical liability claims globally. Therefore, addressing diagnostic error is a high priority. In most cases, diagnostic errors are the result of faulty information synthesis rather than lack of knowledge. Specifically, the majority of diagnostic errors involve cognitive factors, and in particular, cognitive biases. Emergency Departments are an environment with heightened risk of diagnostic error due to time and resource pressures, a frequently chaotic environment, and patients arriving undifferentiated and with minimal context. This project aimed to develop a behavioural, evidence-informed intervention to reduce diagnostic error in Emergency Departments through co-design with emergency physicians, insurers, researchers, hospital managers, citizens and consumer representatives. The Forum Process was utilised to address this aim. This involves convening a small (4 – 6 member) expert panel to guide a focused literature and practice review; convening of a 10 – 12 person citizens panel to gather perspectives of laypeople, including those affected by misdiagnoses; and a 18 – 22 person structured stakeholder dialogue bringing together representatives of the aforementioned stakeholder groups. The process not only provides in-depth analysis of the problem and associated behaviours, but brings together expertise and insight to facilitate identification of a behaviour change intervention. Informed by the literature and practice review, the Citizens Panel focused on eliciting the values and concerns of those affected or potentially affected by diagnostic error. Citizens were comfortable with diagnostic uncertainty if doctors were honest with them. They also emphasised the importance of open communication between doctors and patients and their families. Citizens expect more consistent standards across the state and better access for both patients and their doctors to patient health information to avoid time-consuming re-taking of long patient histories and medication regimes when re-presenting at Emergency Departments and to reduce the risk of unintentional omissions. The structured Stakeholder Dialogue focused on identifying a feasible behavioural intervention to review diagnoses in Emergency Departments. This needed to consider the role of cognitive bias in medical decision-making; contextual factors (in Victoria, there is a legislated 4-hour maximum time between ED triage and discharge / hospital admission); resource availability; and the need to ensure the intervention could work in large metropolitan as well as small rural and regional ED settings across Victoria. The identified behavioural intervention will be piloted in approximately ten hospital EDs across Victoria, Australia. This presentation will detail the findings of all review and consultation activities, describe the behavioural intervention developed and present results of the pilot trial.

Keywords: behavioural intervention, cognitive bias, decision-making, diagnostic error

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Authors: Giulio Rosati, Luciano Sappia, Rossana Madrid, Noemi Rozlòsnik

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The addition of PEG of different molecular weights has important effects on the physical, electrical and electrochemical properties of iron(III)-tosylate doped PEDOT. This particular polymer can be easily spin coated over plastic discs, optimizing thickness and uniformity of the PEDOT-PEG films. The conductivity and morphological analysis of the hybrid PEDOT-PEG polymer by 4-point probe (4PP), 12-point probe (12PP), and conductive AFM (C-AFM) show strong effects of the PEG doping. Moreover, the conductive films kinetics at the nanoscale, in response to different bias voltages, change radically depending on the PEG molecular weight. The hybrid conductive films show also interesting electrochemical properties, making the PEDOT PEG doping appealing for biosensing applications both for EIS-based and amperometric affinity/catalytic biosensors.

Keywords: atomic force microscopy, biosensors, four-point probe, nano-films, PEDOT

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Authors: Muhammad Umair, Syed Qasim Gilani

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A technique using Independent Component Analysis (ICA) for blind receiver signal processing is investigated. The problem of the receiver signal processing is viewed as of signal equalization and implementation imperfections compensation. Based on this, a model similar to a general ICA problem is developed for the received signal. Then, the use of ICA technique for blind signal equalization in the time domain is presented. The equalization is regarded as a signal separation problem, since the desired signal is separated from interference terms. This problem is addressed in the paper by over-sampling of the received signal. By using ICA for equalization, besides channel equalization, other transmission imperfections such as Direct current (DC) bias offset, carrier phase and In phase Quadrature phase imbalance will also be corrected. Simulation results for a system using 16-Quadraure Amplitude Modulation(QAM) are presented to show the performance of the proposed scheme.

Keywords: blind equalization, blind signal separation, equalization, independent component analysis, transmission impairments, QAM receiver

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Authors: Rachel Nir, Tina Mckee

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In the UK, reliance has been placed on the professions to ‘heal themselves’ in improving equality and diversity. This approach has faltered, in part due to the global economic climate, and stimulus is needed to make faster equality progress. Recent empirical evidence has identified specific diversity barriers, namely: the cost of training; the use of high school grades as a primary selection criteria; the significance of prior work experience in recruitment decisions; and recruitment from elite universities. Students from majority groups and affluent backgrounds are advantaged over their counterparts. We as educators are passionate about resisting this. We believe that education can be a key agent of change. As part of this belief, the presenters have recently designed learning and teaching materials for the 2015/16 academic year. These are aimed at undergraduate law students for the purpose of 1) educating them on career barriers; 2) helping them to develop personal strategies to overcome them; and 3) encouraging them to address their own biases, both conscious and implicit, so that they, themselves, may be fairer employers and managers in the future.

Keywords: career barriers, challenging professional bias, education, elitism, personal student strategies

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Authors: A. Elbaz, K. Spang

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Infrastructure projects are often subjected to delays and cost overruns and mistakenly described as unsuccessful projects. These projects have many peculiarities such as public attention, impact on the environment, subjected to special regulations, etc. They also deal with several stakeholders with different motivations and face unique risks. With this in mind we need to reconsider our approach to manage them, define their success factors and implement these success factors. Infrastructure projects are not only lacking a unified meaning of project success or a definition of success factors, but also a clear method to implement these factors. This paper investigates this gap and introduces a concept to implement success factors in an efficient way, taking into consideration the specific characteristics of infrastructure projects. This concept consists of six enablers such as project organization, project team, project management workflow, contract management, communication and knowledge transfer and project documentations. These enablers allow other success factors to be efficiently implemented in projects. In conclusion, this paper provides project managers as well as company managers with a tool to define and implement success factors efficiently in their projects, along with upgrading their assets for the coming projects. This tool consists of processes and validated checklists to ensure the best use of company resources and knowledge. Due to the special features of infrastructure projects this tool will be tested in the German infrastructure market. However, it is meant to be adaptable to other markets and industries.

Keywords: infrastructure projects, operative success factors, project success, success factors, transportation projects

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Authors: Angela Meyer

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The operation and maintenance cost for wind parks make up a major fraction of the park’s overall lifetime cost. To minimize the cost and risk involved, an optimal operation and maintenance strategy requires continuous monitoring and analysis. In order to facilitate this, we present a decision support system that automatically scans the stream of telemetry sensor data generated from the turbines. By learning decision boundaries and normal reference operating states using machine learning algorithms, the decision support system can detect anomalous operating behavior in individual wind turbines and diagnose the involved turbine sub-systems. Operating personal can be alerted if a normal operating state boundary is exceeded. The presented decision support system and method are applicable for any turbine type and manufacturer providing telemetry data of the turbine operating state. We demonstrate the successful detection and diagnosis of anomalous operating states in a case study at a German onshore wind park comprised of Vestas V112 turbines.

Keywords: anomaly detection, decision support, machine learning, monitoring, performance optimization, wind turbines

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Authors: Valerie Habbel, Magdalena Orth, Johanna Richter, Steffen Schimko

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Cooperation between development actors and the private sector is becoming increasingly important, as it is expected to mobilize additional resources to achieve the Sustainable Development Goals (SDGs), among other things. However, whether the goals of cooperation are achieved has so far only been explored in evaluations and studies of individual projects and instruments. The evaluation synthesis attempts to close this gap by systematically analyzing existing evidence (evaluations and academic studies) from national and international development cooperation on private sector engagement. Overall, the evaluations and studies considered report mainly positive effects on investors and donors, intermediaries, partner countries, and target groups. However, various analyses, including on the quality of the evaluations, point to a positive bias in the results. The evaluation synthesis makes recommendations on the definition of indicators, the measurement and evaluation of impacts and additionality, knowledge management, and the consideration of transaction costs in cooperation with private actors.

Keywords: evaluation synthesis, private sector engagement, international development, sustainable development

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Authors: Nga Yui Tong

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Mandarin, the official language of China, is based on the Beijing dialect and is spoken by more than one billion people from all over the world. To investigate the trends of Mandarin acquisition, 192 preschoolers are recruited by stratified random sampling. They are from 4 different districts in Beijing, 2 schools in each district, with 4 age groups, both genders, and 3 children in each stratum. The children are paired up to conduct semi-structured free play for 30 minutes. Their language output is videotaped, transcribed, and coded for the calculation of Mean Length of Utterance (MLU). Two-way ANOVA showed that the variation of MLU is significantly contributed by age, which is coherent to previous findings of other languages. This first large-scale study to investigate the developmental trend of Mandarin in young children in Beijing provides empirical evidence to the development of standards and curriculum planning for early Mandarin education. Interestingly, the gender effect in the study is insignificant, with boys showing a slightly higher MLU than girls across all age groups and settings, except the 4.5 years same-gender dyads. The societal factors in the Chinese context on parenting and gender bias are worth looking into.

Keywords: Beijing, language development, Mandarin, preschoolers

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Authors: María Laura Guevara Campos

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The increasing number of vending machines makes it easy for people to find them more frequently in stores, universities, workplaces, and even hospitals. These machines usually offer products with high contents of sugar and fat, which, if consumed regularly, can result in serious health threats, as overweight and obesity. Additionally, the energy consumption of these machines tends to be high, which has an impact on the environment as well. In order to promote the consumption of healthy food, a vending machine was designed to give the customer the opportunity to choose between a customized fruit salad and a customized fruit juice, both of them prepared instantly with the ingredients selected by the customer. The main parameters considered to design the machine were: the storage of the preferred fruits in a salad and/or in a juice according to a survey, the size of the machine, the use of ecologic recipients, and the overall energy consumption. The methodology used for the design was the one proposed by the German Association of Engineers for mechatronics systems, which breaks the design process in several stages, from the elaboration of a list of requirements through the establishment of the working principles and the design concepts to the final design of the machine, which was done in a 3D modelling software. Finally, with the design of this machine, the aim is to contribute to the development and implementation of healthier vending machines that offer freshly-made products, which is not being widely attended at present.

Keywords: design, design methodology, mechatronics systems, vending machines

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Authors: Anjana Sreedharan, Harish Rao

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Background: India has the world’s third largest population of people living with HIV/AIDS, with a prevalence rate of 0.69 in the state of Karnataka. This study aims at assessing the HIV/AIDS related knowledge, attitude and behavior of the medical personnel in 3 hospitals in the city of Mangalore. Methods: Surgeons, Anesthetists, OT staff nurses, ward nursing staff, House surgeons working in the hospitals associated with Kasturba Medical college, Mangalore were given questionnaires and interviewed. Their knowledge about HIV, their attitude towards HIV positive patients and bias in management of the patients was assessed. Conclusion: So far, it has been found that amongst doctors, discrimination was mainly in the form of HIV testing without consent and a lack of confidentiality. However, the doctors rarely changed the treatment plan on knowing the HIV status of the patient. Amongst the nursing staff and interns, there is a serious lacuna of knowledge regarding HIV transmission, as compared to consultants. The patient seldom faced verbal abuse from the team. Use of universal precautions is less among the entire team due to insufficient availability of the same.

Keywords: discrimination, HIV/ AIDS, medical colleges, stigma

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Authors: Lenka Mynaříková, Hedvika Boukalová

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The study looks at the ability to detect nonverbal deception among police officers and management students in the Czech Republic. Respondents from police departments (n=197) and university students of human resources (n=161) completed a deception detection task and evaluated veracity of the statements of suspects in 21 video clips from real crime investigations. Their evaluations were based on nonverbal behavior. Voices in the video clips were modified so that words were not recognizable, yet paraverbal voice characteristics were preserved. Results suggest that respondents have a tendency to lie bias based on their profession. In the evaluation of video clips, stereotypes also played a significant role. The statements of suspects of a different ethnicity, younger age or specific visual features were considered deceitful more often. Research might be beneficial for training in professions that are in need of deception detection techniques.

Keywords: deception detection, police officers, human resources, forensic psychology, forensic studies, organizational psychology

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Authors: Betina Luiza Koop, Lenilton Santos Soares, Karina Cesca, Germán Ayala Valencia, Alcilene Rodrigues Monteiro

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Active and smart food packaging has been studied to control and extend the food shelf-life. However, active compounds such as anthocyanins (ACNs) are unstable to high temperature, light, and pH changes. Several alternatives to stabilize and protect the anthocyanins have been researched, such as adsorption on nanoclays. Thus, this work aimed to stabilize anthocyanin extracted from jambolan fruit (Syzygium cumini), a noncommercial fruit, to development of food package sensors. The anthocyanin extract from jambolan pulp was concentrated by ultrafiltration and adsorbed on montmorillonite. The final biohybrid material was characterized by pH and color. Anthocyanins were adsorbed on nanoclay at pH 1.5, 2.5, and 3.5 and temperatures of 10 and 20 °C. The highest adsorption values were obtained at low pH at high temperatures. The color and antioxidant activity of the biohybrid was maintained for 60 days. A test of the color stability at pH from 1 to 13, simulating spoiled food using ammonia vapor, was performed. At pH from 1 to 5, the ACNs pink color was maintained, indicating that the flavylium cation form was preserved. At pH 13, the biohybrid presented yellow color due to the ACN oxidation. These results showed that the biohybrid material developed has potential application as a sensor to indicate the freshness of meat products.

Keywords: anthocyanin, biohybrid, food, smart packaging

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Authors: Tao Lin, Shanghong Zhao, Yufu Yin, Zihang Zhu, Wei Jiang, Xuan Li, Qiurong Zheng

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A simple operated, stable and compact multi-band frequency conversion and multi-phase shift is proposed to satisfy the demands of multi-band communication and radar phase array system. The dual polarization quadrature phase shift keying (DP-QPSK) modulator is employed to support the LO sideband and the optical frequency comb simultaneously. Meanwhile, the fiber is also used to introduce different phase shifts to different sidebands. The simulation result shows that by controlling the DC bias voltages and a C band microwave signal with frequency of 4.5 GHz can be simultaneously converted into other signals that cover from C band to K band with multiple phases. It also verifies that the multi-band and multi-phase frequency conversion system can be stably performed based on current manufacturing art and can well cope with the DC drifting. It should be noted that the phase shift of the converted signal also partly depends of the length of the optical fiber.

Keywords: microwave photonics, multi-band frequency conversion, multi-phase shift, conversion efficiency

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Authors: Maximilian Winkens, Matthias Goerke

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The state-oriented maintenance enables the preventive intervention before the failure of a component and guarantees avoidance of expensive breakdowns. Because the timing of the maintenance is defined by the component’s state, the remaining service life can be exhausted to the limit. The basic requirement for the state-oriented maintenance is the ability to define the component’s state. New potential for this is offered by gentelligent components. They are developed at the Corporative Research Centre 653 of the German Research Foundation (DFG). Because of their sensory ability they enable the registration of stresses during the component’s use. The data is gathered and evaluated. The methodology developed determines the current state of the gentelligent component based on the gathered data. This article presents this methodology as well as current research. The main focus of the current scientific work is to improve the quality of the state determination based on the life-cycle data analysis. The methodology developed until now evaluates the data of the usage phase and based on it predicts the timing of the gentelligent component’s failure. The real failure timing though, deviate from the predicted one because the effects from the production phase aren’t considered. The goal of the current research is to develop a methodology for state determination which considers both production and usage data.

Keywords: state-oriented maintenance, life-cycle data, gentelligent component, preventive intervention

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Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

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Authors: Michael Josef Schwerer

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Background: The identification of unknown victims from mass disasters, violent crimes, or terrorist attacks is frequently facilitated through information from missing persons lists, portrait photos, old or recent pictures showing unique characteristics of a person such as scars or tattoos, or simply reference samples from blood relatives for DNA analysis. In contrast, the identification or at least the characterization of an unknown perpetrator from criminal or terrorist actions remains challenging, particularly in the absence of material or data for comparison, such as fingerprints, which had been previously stored in criminal records. In scenarios that result in high levels of destruction of the perpetrator’s corpse, for instance, blast or fire events, the chance for a positive identification using standard techniques is further impaired. Objectives: This study shows the forensic genetic procedures in the Legal Medicine Service of the German Air Force for the identification of unknown individuals, including such cases in which reference samples are not available. Scenarios requiring such efforts predominantly involve aircraft crash investigations, which are routinely carried out by the German Air Force Centre of Aerospace Medicine as one of the Institution’s essential missions. Further, casework by military police or military intelligence is supported based on administrative cooperation. In the talk, data from study projects, as well as examples from real casework, will be demonstrated and discussed with the audience. Methods: Forensic genetic identification in our laboratories involves the analysis of Short Tandem Repeats and Single Nucleotide Polymorphisms in nuclear DNA along with mitochondrial DNA haplotyping. Extended DNA analysis involves phenotypic markers for skin, hair, and eye color together with the investigation of a person’s biogeographic ancestry. Assessment of the biological age of an individual employs CpG-island methylation analysis using bisulfite-converted DNA. Forensic Investigative Genealogy assessment allows the detection of an unknown person’s blood relatives in reference databases. Technically, end-point-PCR, real-time PCR, capillary electrophoresis, pyrosequencing as well as next generation sequencing using flow-cell-based and chip-based systems are used. Results and Discussion: Optimization of DNA extraction from various sources, including difficult matrixes like formalin-fixed, paraffin-embedded tissues, degraded specimens from decomposed bodies or from decedents exposed to blast or fire events, provides soil for successful PCR amplification and subsequent genetic profiling. For cases with extremely low yields of extracted DNA, whole genome preamplification protocols are successfully used, particularly regarding genetic phenotyping. Improved primer design for CpG-methylation analysis, together with validated sampling strategies for the analyzed substrates from, e.g., lymphocyte-rich organs, allows successful biological age estimation even in bodies with highly degraded tissue material. Conclusions: Successful identification of unknown individuals or at least their phenotypic characterization using pigmentation markers together with age-informative methylation profiles, possibly supplemented by family tree search employing Forensic Investigative Genealogy, can be provided in specialized laboratories. However, standard laboratory procedures must be adapted to work with difficult and highly degraded sample materials.

Keywords: identification, forensic genetics, phenotypic markers, CPG methylation, biological age estimation, forensic investigative genealogy

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Authors: Farid Habibi Tanha, Mojtaba Jahanbazi, Morteza Foroutan, Rasidah Mohd Rashid

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This paper depicts the effects of asymmetric information in determining capital inflows to be captured through stock market microstructure. The model can explain several stylized facts regarding the capital immobility. The first phase of the research involves in collecting and refining 150,000,000 daily data of 11 stock markets over a period of one decade in an effort to minimize the impact of survivorship bias. Three micro techniques were used to measure information asymmetries. The final phase analyzes the model through panel data approach. As a unique contribution, this research will provide valuable information regarding negative effects of information asymmetries in stock markets on attracting foreign investments. The results of this study can be directly considered by policy makers to monitor and control changes of capital flow in order to keep market conditions in a healthy manner, by preventing and managing possible shocks to avoid sudden reversals and market failures.

Keywords: asymmetric information, capital inflow, market microstructure, investment

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Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

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Authors: Laboratory of Semiconducting, Metallic Materials (LMSM) Biskra Algeria

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InZnSnO2 (IZTO)/β-Ga2O3 Schottky solar barrier photodetector (PhD) exposed to 255 nm was simulated and compared to the measurement. Numerical simulations successfully reproduced the photocurrent at reverse bias and response by taking into account several factors, such as conduction mechanisms and material parameters. By adopting reducing the density of the trap as an improvement. The effect of reducing the bulk trap densities on the photocurrent, response, and time-dependent (continuous conductivity) was studied. As the trap density decreased, the photocurrent increased. The response was 0.04 A/W for the low Ga2O3 trap density. The estimated decay time for the lowest intensity ET (0.74, 1.04 eV) is 0.05 s and is shorter at ∼0.015 s for ET (0.55 eV). This indicates that the shallow traps had the dominant effect (ET = 0.55 eV) on the continuous photoconductivity phenomenon. Furthermore, with decreasing trap densities, this PhD can be considered as a self-powered solar-blind photodiode (SBPhD).

Keywords: IZTO/β-Ga2O3, self-powered solar-blind photodetector, numerical simulation, bulk traps

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Authors: Anudeep Appe, Bhanu Poluparthi, Lakshmi Kasivajjula, Udai Mv, Sobha Bagadi, Punya Modi, Aditya Singh, Hemanth Gunupudi, Spenser Troiano, Jeff Paul, Justin Stovall, Justin Yamamoto

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The necessity of data-driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a healthcare provider facility or a hospital (from here on termed as facility) market share is of key importance. This pilot study aims at developing a data-driven machine learning-regression framework which aids strategists in formulating key decisions to improve the facility’s market share which in turn impacts in improving the quality of healthcare services. The US (United States) healthcare business is chosen for the study, and the data spanning 60 key facilities in Washington State and about 3 years of historical data is considered. In the current analysis, market share is termed as the ratio of the facility’s encounters to the total encounters among the group of potential competitor facilities. The current study proposes a two-pronged approach of competitor identification and regression approach to evaluate and predict market share, respectively. Leveraged model agnostic technique, SHAP, to quantify the relative importance of features impacting the market share. Typical techniques in literature to quantify the degree of competitiveness among facilities use an empirical method to calculate a competitive factor to interpret the severity of competition. The proposed method identifies a pool of competitors, develops Directed Acyclic Graphs (DAGs) and feature level word vectors, and evaluates the key connected components at the facility level. This technique is robust since its data-driven, which minimizes the bias from empirical techniques. The DAGs factor in partial correlations at various segregations and key demographics of facilities along with a placeholder to factor in various business rules (for ex. quantifying the patient exchanges, provider references, and sister facilities). Identified are the multiple groups of competitors among facilities. Leveraging the competitors' identified developed and fine-tuned Random Forest Regression model to predict the market share. To identify key drivers of market share at an overall level, permutation feature importance of the attributes was calculated. For relative quantification of features at a facility level, incorporated SHAP (SHapley Additive exPlanations), a model agnostic explainer. This helped to identify and rank the attributes at each facility which impacts the market share. This approach proposes an amalgamation of the two popular and efficient modeling practices, viz., machine learning with graphs and tree-based regression techniques to reduce the bias. With these, we helped to drive strategic business decisions.

Keywords: competition, DAGs, facility, healthcare, machine learning, market share, random forest, SHAP

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Authors: Weisi Guo

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It is well established that there may be running correlations in sequential exam marks due to students sitting in the order of course registration patterns. As such, a random and non-sequential sampling of exam marks is a standard recommended practice. Here, the paper examines a large number of exam data stretching several years across different modules to see the degree to which it is true. Using the real mark distribution as a generative process, it was found that random simulated data had no more sequential randomness than the real data. That is to say, the running correlations that one often observes are statistically identical to chance. Digging deeper, it was found that some high running correlations have students that indeed share a common course history and make similar mistakes. However, at the statistical scale of a module question, the combined effect is statistically similar to the random shuffling of papers. As such, there may not be the need to take random samples for marks, but it still remains good practice to mark papers in a random sequence to reduce the repetitive marking bias and errors.

Keywords: data analysis, empirical study, exams, marking

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Authors: Duncan Oteki, Andebut Yeneneh, Daba Gedafa, Nabil Suleiman

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Most agencies lack the equipment required to measure the dynamic modulus (|E*|) of asphalt mixtures, necessitating the need to use predictive models. This study compared measured |E*| values for nine North Dakota asphalt mixes using the original Witczak, modified Witczak, and Hirsch models. The influence of temperature on the |E*| models was investigated, and Pavement ME simulations were conducted using measured |E*| and predictions from the most accurate |E*| model. The results revealed that the original Witczak model yielded the lowest Se/Sy and highest R² values, indicating the lowest bias and highest accuracy, while the poorest overall performance was exhibited by the Hirsch model. Using predicted |E*| as inputs in the Pavement ME generated conservative distress predictions compared to using measured |E*|. The original Witczak model was recommended for predicting |E*| for low-reliability pavements in North Dakota.

Keywords: asphalt mixture, binder, dynamic modulus, MEPDG, pavement ME, performance, prediction

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Authors: Odón R. Sánchez-Ccoyllo, Elizabeth Ayma-Choque, Alan Llacza

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Sulphur dioxide (SO₂) and surface-ozone (O₃) concentrations are associated with diseases. The objective of this research is to evaluate the effectiveness of the air-quality-WRF-Chem model with a horizontal resolution of 5 km x 5 km. For this purpose, the measurements of the hourly SO₂ and O₃ concentrations available in three air quality monitoring stations in Lima, Peru were used for the purpose of validating the simulations of the SO₂ and O₃ concentrations obtained with the WRF-Chem model in February 2018. For the quantitative evaluation of the simulations of these gases, statistical techniques were implemented, such as the average of the simulations; the average of the measurements; the Mean Bias (MeB); the Mean Error (MeE); and the Root Mean Square Error (RMSE). The results of these statistical metrics indicated that the simulated SO₂ and O₃ values over-predicted the SO₂ and O₃ measurements. For the SO₂ concentration, the MeB values varied from 0.58 to 26.35 µg/m³; the MeE values varied from 8.75 to 26.5 µg/m³; the RMSE values varied from 13.3 to 31.79 µg/m³; while for O₃ concentrations the statistical values of the MeB varied from 37.52 to 56.29 µg/m³; the MeE values varied from 37.54 to 56.70 µg/m³; the RMSE values varied from 43.05 to 69.56 µg/m³.

Keywords: ground-ozone, lima, sulphur dioxide, WRF-chem

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Authors: Martin A. Curry

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Madeline Island is a small island community in Wisconsin, USA. Located in Lake Superior, it has been home to the Anishinaabe/Ojibway people for 1000s of years and is known as Moningwankuaning Minis-"The Island of the Golden Breasted Woodpecker". The community relies on summer tourism as its source of income, with a small population of 400 year-round residents. Supervisor Martin A. Curry (Ojibway/German descent) has been working on a fiscally responsible, environmentally principled and culturally centered approach to waste diversion and recycling. The tenets of this program encompass plastics, paper, food waste, local farming, energy production and art education. Through creative writing for the local newspaper and creative interactions, Martin has worked to engage the community in a more robust interest in waste diversion, including setting up a free-will donation store that incorporates elder volunteering opportunities, a compost program that works with the local community garden, biodiesel production and an art program that works with children from the local island school to make paper, grow local food and paint murals. The entirety of this program is based on the Ojibway concept of Mino-Bimadiiziwiin- "The Good Life" and benefits the community and its guests and represents a microcosm of the global dilemmas of waste and recycling.

Keywords: recycling, waste diversion, island, Native American, art

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Authors: Hamed Rahmani, Wim Groot

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The term "youth not in employment, education or training (NEET)" refers to a combination of youth unemployment and school dropout. This study investigates the variables that increase the risk of becoming NEET in Iran. A selection bias-adjusted Probit model was employed using machine learning to identify these risk factors. We used cross-sectional data obtained from the Statistical Centre of Iran and the Ministry of Cooperatives Labour and Social Welfare that was taken from the labour force survey conducted in the spring of 2021. We look at years of education, work experience, housework, the number of children under the age of six in the home, family education, birthplace, and the amount of land owned by households. Results show that hours spent performing domestic chores enhance the likelihood of youth becoming NEET, and years of education and years of potential work experience decrease the chance of being NEET. The findings also show that female youth born in cities were less likely than those born in rural regions to become NEET.

Keywords: NEET youth, probit, CART, machine learning, unemployment

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Authors: Sabrina S. W. Chan, Emily Schwartzman, Nicholas O. Rule

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Past literature showed mixed findings on how smiling affects a person’s chance of getting hired. On one hand, smiling suggests enthusiasm, cooperativeness, and enthusiasm, which can elicit positive impressions. On the other hand, smiling can suggest weaker professionalism or a filler to hide nervousness, which can lower a candidate’s perceived competence. Emotion expressions can also be perceived differently depending on the person’s gender and can activate certain gender stereotypes. Women especially face a double bind with respect to hiring decisions and smiling. Because women are socially expected to smile more, those who do not smile will be considered stereotype incongruent. This becomes a noisy signal to employers and may lower their chance of being hired. However, women’s smiling as a formality may also be an obstacle. They are more likely to put on fake smiles; but if they do, they are also likely to be perceived as inauthentic and over-expressive. This paper sought to investigate how smiling affects hiring decisions, and whether this relationship is moderated by gender. In Study 1, participants were shown a series of smiling and emotionally neutral face images, incorporated into fabricated LinkedIn profiles. Participants were asked to rate how hireable they thought that candidate was. Results showed that participants rated smiling candidates as more hireable than nonsmiling candidates, and that there was no difference in gender. Moreover, individuals who did not study business were more biased in their perceptions than those who did. Since results showed a trending favoritism over female targets, in suspect of desirability bias, a second study was conducted to collect implicit measures behind the decision-making process. In Study 2, a mouse-tracking design was adopted to explore whether participants’ implicit attitudes were different from their explicit responses on hiring. Participants asked to respond whether they would offer an interview to a candidate. Findings from Study 1 was replicated in that smiling candidates received more offers than neutral-faced candidates. Results also showed that female candidates received significantly more offers than male candidates but was associated with higher attractiveness ratings. There were no significant findings in reaction time or change of decisions. However, stronger hesitation was detected for responses made towards neutral targets when participants perceived the given position as masculine, implying a conscious attempt of making situational judgments (e.g., considering candidate’s personality and job fit) to override automatic processing (evaluations based on attractiveness). Future studies would look at how these findings differ for positions which are stereotypically masculine (e.g., surgeons) and stereotypically feminine (e.g., kindergarten teachers). Current findings have strong implications for developing bias-free hiring policies in workplace, especially for organizations who maintain online/hybrid working arrangements in the post-pandemic era. This also bridges the literature gap between face perception and gender discrimination, highlighting how engendered facial cues can affect individual’s career development and organization’s success in diversity and inclusion.

Keywords: engendered facial cues, face perception, gender stereotypes, hiring decisions, smiling, workplace discrimination

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Authors: Kate Whitman, Zahra Murad, Joe Cox, Adam Cox

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This study investigates the influence of normative communications on digital piracy intentions. Although descriptive norms are thought to influence behavior, the study examines the potential bias in one's own behavior, leading to false consensus—a phenomenon perpetuating undesirable activities. The research tests the presence of false consensus and the effect of correcting normative predictions on changes in piracy intentions, examining gender differences. Results from a controlled experiment (N = 684) indicate that normative communications, reflecting the "real" norm based on government data (N=5000), increase (decrease) piracy intentions among men (women) underestimating their peers' behavior. Conversely, neither men nor women overestimating their peers' piracy show any notable change in intentions. Considering men consume more illegal content than women, suggesting they pose a higher risk, the study highlights the need for cautious use of normative communications. Therefore, policymakers should minimize the visibility of piracy behavior for effective digital piracy management.

Keywords: digital piracy, false consensus, normative interventions, persuasive messages

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Authors: Panagiota Katsikouli, William Hamilton Byrne, Thomas Gammeltoft-Hansen, Tijs Slaats

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An individual who demonstrates a well-founded fear of persecution or faces real risk of being subjected to torture is eligible for asylum. In Danish law, the exact legal thresholds reflect those established by international conventions, notably the 1951 Refugee Convention and the 1950 European Convention for Human Rights. These international treaties, however, remain largely silent when it comes to how states should assess asylum claims. As a result, national authorities are typically left to determine an individual’s legal eligibility on a narrow basis consisting of an oral testimony, which may itself be hampered by several factors, including imprecise language interpretation, insecurity or lacking trust towards the authorities among applicants. The leaky ground, on which authorities must assess their subjective perceptions of asylum applicants' credibility, questions whether, in all cases, adjudicators make the correct decision. Moreover, the subjective element in these assessments raises questions on whether individual asylum cases could be afflicted by implicit biases or stereotyping amongst adjudicators. In fact, recent studies have uncovered significant correlations between decision outcomes and the experience and gender of the assigned judge, as well as correlations between asylum outcomes and entirely external events such as weather and political elections. In this study, we analyze a publicly available dataset containing approximately 8,000 summaries of asylum cases, initially rejected, and re-tried by the Refugee Appeals Board (RAB) in Denmark. First, we look for variations in the recognition rates, with regards to a number of applicants’ features: their country of origin/nationality, their identified gender, their identified religion, their ethnicity, whether torture was mentioned in their case and if so, whether it was supported or not, and the year the applicant entered Denmark. In order to extract those features from the text summaries, as well as the final decision of the RAB, we applied natural language processing and regular expressions, adjusting for the Danish language. We observed interesting variations in recognition rates related to the applicants’ country of origin, ethnicity, year of entry and the support or not of torture claims, whenever those were made in the case. The appearance (or not) of significant variations in the recognition rates, does not necessarily imply (or not) bias in the decision-making progress. None of the considered features, with the exception maybe of the torture claims, should be decisive factors for an asylum seeker’s fate. We therefore investigate whether the decision can be predicted on the basis of these features, and consequently, whether biases are likely to exist in the decisionmaking progress. We employed a number of machine learning classifiers, and found that when using the applicant’s country of origin, religion, ethnicity and year of entry with a random forest classifier, or a decision tree, the prediction accuracy is as high as 82% and 85% respectively. tentially predictive properties with regards to the outcome of an asylum case. Our analysis and findings call for further investigation on the predictability of the outcome, on a larger dataset of 17,000 cases, which is undergoing.

Keywords: asylum adjudications, automated decision-making, machine learning, text mining

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Authors: Piotr-Robert Lazik, Lena Teichmann, Harald Garrecht

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Many concrete technologists are looking for a solution to replace fly ashes as a component that occurs as a major component of many types of concrete. The importance of such a component is clear -it saves cement and reduces the amount of CO₂ in the atmosphere that occurs during cement production. For example, the amount of cement in ultrahigh strength concrete (UHPC) is approximately 700-800 kg/m³ in normal concrete up to 350 kg/m³. For this reason, it is easy to follow that the use of components like fly ashes or wood ashes protect the environment. The newest investigations carried out at the University of Stuttgart have clearly shown that the use of wood ashes with appropriate pre-treatment in concrete has a positive effect. German-wide, there are hundreds of tons of wood ashes, which can be used in a wide range of construction materials. The strengths of the concrete with different types of cement and with wood ashes have given the same or, in some cases, better results than those with the use of fly ashes. There are many areas in building construction, where the clays of wood ashes can be used as a by-product. This does not only require a strength test but also, for example, an examination of structural-physical parameters. Especially the heat and moisture characteristics have an important role in times of energy-efficient construction. These are therefore determined and then compared with the characteristics of the concretes with fly ashes. The University of Stuttgart has decided to investigate the buildings' physical properties of different types of concrete with wood ashes to find their application in construction. After the examination of the buildings' physical properties in combination with strength tests, it is possible to determine in which field of civil engineering, this type of concrete can be used.

Keywords: fly ashes, wood ashes, structural-physical parameters, UHPC

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Authors: M. Mokrzecka, A. Aly, A. K. Obwona, Piotrowska M., Richardson S.

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Frankfurt am Main, the fifth largest city in Germany, ranked 15th by the Global Financial Centers Index in 2014, and a finalist of European Green Capital 2014, is a crucial player in German Environmental Policy. In 2012 the city authorities agreed a target to reduce the city’s energy consumption by 50%, and fully switch to renewable energy by the year 2050. To achieve this goal, the Municipality of Frankfurt has begun preparing the Master plan, which will be introduced to public by the end of 2015. Transitions theory tells, that to address challenges as complex as Climate Change and the Energiewende, the development of new technologies and systems is not sufficient. Transition by definition is a process, and in such a large scale (city and region transition) can be fulfilled only, when operates within a broad socio – technical system. Thus, the Authors believe that only by close cooperation with citizens, as well as different stakeholders, can the Transition in Frankfurt be successful. The city therefore needs a strategy which will ensure the engagement, sense of ownership and broad support within Frankfurt society for the aims of the Master plan. This paper presents a proposal for how the city can achieve this based therefore, on fostering the citizens’ engagement through a comprehensive, innovative communication strategy. The proposal was originally developed by the authors as a winning submission for the Climate-KIC Transitions PhD Summer School 2014..

Keywords: city development, communication strategies, social transition, sustainability

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