Cirrhosis Mortality Prediction as Classification Using Frequent Subgraph Mining

In this work, we use machine learning and data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. Our work applies modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Psychodidactic Strategies to Facilitate the Flow of Logical Thinking in the Preparation of Academic Documents

The preparation of academic documents, such as thesis, articles and research projects, is one of the requirements of the higher educational level. These documents demand the implementation of logical argumentative thinking which is experienced and executed with difficulty. To mitigate the effect of these difficulties we designed a thesis seminar, with which we have seven years of experience. It is taught in a graduate program in Psychology at the National Autonomous University of Mexico. In this seminar we use the Toulmin model as a mental heuristic and for the application of a set of psychodidactic strategies that facilitate the elaboration of the plot and culmination of the thesis. The efficiency in obtaining the degree in the groups exposed to the seminar has increased by 94% compared to the 10% that existed in the generations that were not exposed to the seminar. In this article we will emphasize the psychodidactic strategies used. The Toulmin model alone does not guarantee the success achieved. A set of actions of a psychological nature (almost psychotherapeutic) and didactics of the teacher also seem to contribute. These are actions that derive from an understanding of the psychological, epistemological and ontogenetic obstacles and the most frequent errors in which thought tends to fall when it is demanded a logical course. We have grouped the strategies into three groups: 1) strategies to facilitate logical thinking, 2) strategies to strengthen the scientific self and 3) strategies to facilitate the act of writing the text. In this work we delve into each of them.

Gas Injection Transport Mechanism for Shale Oil Recovery

The United States is now energy self-sufficient due to the production of shale oil reserves. With more than half of it being tapped daily in the United States, these unconventional reserves are massive and provide immense potential for future energy demands. Drilling horizontal wells and fracking are the primary methods for developing these reserves. Regrettably, recovery efficiency is rarely greater than 10%. Gas injection enhanced oil recovery offers a significant benefit in optimizing recovery of shale oil. This could be either through huff and puff, gas flooding, and cyclic gas injection. Methane, nitrogen, and carbon (IV) oxide, among other high-pressure gases, can be injected. Operators use Darcy's law to assess a reservoir's productive capacity, but they are unaware that the law may not apply to shale oil reserves. This is due to the fact that, unlike pressure differences alone, diffusion, concentration, and gas selection all play a role in the flow of gas injected into the wellbore. The reservoir drainage and oil sweep efficiency rates are determined by the transport method. This research evaluates the parameters that influence gas injection transport mechanism. Understanding the process could accelerate recovery by two to three times.

Technological Applications in Automobile Manufacturing Sector: A Case Study Analysis

The research focuses on the applicable technologies in the automobile industry and their effects on the productivity and annual revenue of the industry. A study has been conducted on six major automobile manufacturing industries represented in this research as M1, M2, M3, M4, M5 and M6. The results indicate that M1, which is a pioneer in technological applications, remains the market leader, followed by M5 and M2 taking the second and third positions, respectively. M3, M6 and M4 are the followers and are placed next in positions. It has also been observed that M1 and M2 have entered into an agreement to share the basic structural technologies and they maintain long-term and trusted relationships with their suppliers through the Keiretsu system. With technological giants such as Apple, Microsoft, Uber and Google entering the automobile industry in recent years, an upward trend is expected in the futuristic market with self-driving cars to dominate the automobile sector. To keep up with the market trend, it is essential for automobile manufacturers to understand the importance of developing technological capabilities and skills to be competitive in the marketplace.

Additive Friction Stir Manufacturing Process: Interest in Understanding Thermal Phenomena and Numerical Modeling of the Temperature Rise Phase

Additive Friction Stir Manufacturing, or AFSM, is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. There is still a lack in understanding of the physical phenomena taking place during the process. This research aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system due to pure friction. An analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable, due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes through a numerical modeling followed by an experimental validation to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

An E-Maintenance IoT Sensor Node Designed for Fleets of Diverse Heavy-Duty Vehicles

E-maintenance is a relatively recent concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This is clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification, cellular connectivity, connectivity to the vehicle computer, and connectivity to analog and digital sensors by means of a specially targeted design of expansion board. Specifically, the latter offers a number of adaptability features to cope with the diverse sensor types employed in different vehicles. In standard mode, the IoT sensor node communicates to the data center through cellular network, transmitting all digital/digitized sensor data, IoT device identity and position. Moreover, the proposed IoT sensor node offers connectivity, through WiFi and an appropriate application, to smart phones or tablets allowing the registration of additional vehicle- and driver-specific information and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware.

Nascent Federalism in Nepal: An Observational Review in Its Evolution

Nepal practiced a centralized unitary governing system for long and has gone through the federal system after the promulgation of the new constitution on 20 September 2015. There is a big paradigm shift in terms of governance after it. Now, there are three levels of governments, one federal government in the center, seven provincial governments and 753 local governments. Federalism refers to a political governing system with multiple tiers of government working together with coordination. It is preferred for self and shared rule. Though it has opened the door for rights of the people, political stability, state restructuring, and sustainable peace and development, there are many prospects and challenges for its proper implementation. This research analyzes the discourses of federalism implementation in Nepal with special reference to one of seven provinces, Gandaki. Federalism is a new phenomenon in Nepali politics and informed debates on it are required for its right evolution. This research will add value in this regard. Moreover, tracking its evolution and the exploration of the attitudes and behaviors of key actors and stakeholders in a new experiment of a new governing system is also important. The administrative and political system of Gandaki province in terms of service delivery and development will critically be examined. Besides demonstrating the performances of the provincial government and assembly, it will analyze the inter-governmental relation of Gandaki with the other two tiers of government. For this research, people from provincial and local governments (elected representatives and government employees), provincial assembly members, academicians, civil society leaders and journalists are being interviewed. The interview findings will be analyzed by supplementing with published documents. Just going into the federal structure is not the solution. As in the case of other provincial governments, Gandaki also had to start from scratch. It gradually took a shape of government and has been functioning sluggishly. The provincial government has many challenges ahead, which has badly hindered its plans and actions. Additionally, fundamental laws, infrastructures and human resources are found to be insufficient at the sub-national level. Lack of clarity in the jurisdiction is another main challenge. The Nepali Constitution assumes cooperation, coexistence and coordination as the fundamental principles of federalism which, unfortunately, appear to be lacking among the three tiers of government despite their efforts. Though the devolution of power to sub-national governments is essential for the successful implementation of federalism, it has apparently been delayed due to the centralized mentality of bureaucracy as well as a political leader. This research will highlight the reasons for the delay in the implementation of federalism. There might be multiple underlying reasons for the slow pace of implementation of federalism and identifying them is very tough. Moreover, the federal spirit is found to be absent in the main players of today's political system, which is a big irony. So, there are some doubts about whether the federal system in Nepal is just a keepsake or a substantive achievement.

Sonic Therapeutic Intervention for Preventing Financial Fraud: A Phenomenological Study

The specific problem is that private and public organizational leaders often do not understand the importance of sonic therapeutic intervention in preventing financial fraud. The study aimed to explore sonic therapeutic intervention practitioners' lived experiences regarding the value of sonic therapeutic intervention in preventing financial fraud. The data collection methods were semi-structured interviews of purposeful samples and documentary reviews, which were analyzed thematically. Four themes emerged from the analysis of interview transcription data: Sonic therapeutic intervention enabled self-control, pro-spiritual values, consequentiality mindset, and post-conventional consciousness. The itemized four themes helped non-engagement in financial fraud. Implications for positive social change include enhanced financial fraud management, more significant financial leadership, and result-oriented decision-taking in the financial market. Also, the study results can improve the increased de-escalation of anxiety/stress associated with defrauding.

Translation, Cultural Adaptation and Validation of the Hungarian Version of Self-Determination Scale

There is a scarcity of validated instruments in Hungarian for the assessment of self-determination related traits and behaviors. In order to fill in this gap, the aim of this study was the translation, cultural adaptation and validation of Self-Determination Scale (SDS) for the Hungarian population. A total of 4335 adults participated in the study. The mean age of the participants was 27.97 (SD = 9.60). The sample consisted mostly of females, less than 20% were males. Exploratory and Confirmatory Factor Analysis was performed for factorial structure checking and validation Cronbach’s alpha was used to examine the reliability of the factors. Our results revealed that the Hungarian version of SDS has good psychometric properties and it is a reliable tool for psychologists who would like to study or assess self-determination traits in their clients. The adapted and validated Hungarian version of SDS is presented in this paper.

Hematologic Inflammatory Markers and Inflammation-Related Hepatokines in Pediatric Obesity

Obesity in children particularly draws attention, because it may threaten the individual’s future life due to many chronic diseases it may lead to. Most of these diseases including obesity itself altogether are related to inflammation. For this reason, inflammation-related parameters gain importance. Within this context, complete blood cell counts, ratios or indices derived from these counts have recently found some platform to be used as inflammatory markers. So far, mostly adipokines were investigated within the field of obesity. Metabolic inflammation is closely associated with cellular dysfunction. In this study, hematologic inflammatory markers and cytokines produced predominantly by the liver (fibroblast growth factor-21 (FGF-21) and fetuin A) were investigated in pediatric obesity. Two groups were constituted from 76 obese children based on World Health Organization criteria. Group 1 was composed of children, whose age- and sex-adjusted body mass index (BMI) percentiles were between 95 and 99. Group 2 consists of children, who are above 99th percentile. The first and the latter groups were defined as obese (OB) and morbid obese (MO). Anthropometric measurements of the children were performed. Informed consent forms and the approval of the institutional ethics committee were obtained. Blood cell counts and ratios were determined by automated hematology analyzer. The related ratios and indexes were calculated. Statistical evaluation of the data was performed by SPSS program. There was no statistically significant difference in terms of neutrophil-to lymphocyte ratio, monocyte-to-high density lipoprotein cholesterol ratio and platelet-to-lymphocyte ratio between the groups. Mean platelet volume and platelet distribution width values were decreased (p < 0.05), total platelet count, red cell distribution width (RDW) and systemic immune inflammation index values were increased (p < 0.01) in MO group. Both hepatokines were increased in the same group, however increases were not statistically significant. In this group, also a strong correlation was calculated between FGF-21 and RDW when controlled by age, hematocrit, iron and ferritin (r = 0.425; p < 0.01). In conclusion, the association between RDW, a hematologic inflammatory marker, and FGF-21, an inflammation-related hepatokine, found in MO group is an important finding discriminating between OB and MO children. This association is even more powerful when controlled by age and iron-related parameters.

Migrant Women English Instructors’ Transformative Workplace Learning Experiences in Post-Secondary English Language Programs in Ontario, Canada

This study aims to reveal migrant women English instructors' workplace learning experiences in Canadian post-secondary institutions in Ontario. Migrant women English instructors in higher education are an understudied group of teachers. This study employs a qualitative research paradigm. Mezirow’s Transformative Learning Theory is an essential lens for the researcher to explain, analyze, and interpret the research data. It is a collaborative research project. The researcher and participants cooperatively create photographic or other artwork data responding to the research questions. Photovoice and arts-informed data collection methodology are the main methods. Research participants engage in the study as co-researchers and inquire about their own workplace learning experiences, actively utilizing their critical self-reflective and dialogic skills. Co-researchers individually select the forms of artwork they prefer to engage with to represent their transformative workplace learning experiences about the Canadian workplace cultures that they underwent while working with colleagues and administrators in the workplace. Once the co-researchers generate their cultural artifacts as research data, they collaboratively interpret their artworks with the researcher and other volunteer co-researchers. Co-researchers jointly investigate the themes emerging from the artworks. They also interpret the meanings of their own and others’ workplace learning experiences embedded in the artworks through interactive one-on-one or group interviews. The following are the research questions that the migrant women English instructor participants examine and answer: (1) What have they learned about their workplace culture and how do they explain their learning experiences? (2) How transformative have their learning experiences been at work? (3) How have their colleagues and administrators influenced their transformative learning? (4) What kind of support have they received? What supports have been valuable to them and what changes would they like to see? (5) What have their learning experiences transformed? (6) What has this arts-informed research process transformed? The study findings implicate English language instructor support currently practiced in post-secondary English language programs in Ontario, Canada, especially for migrant women English instructors. This research is a doctoral empirical study in progress. This study has the urgency to address the research problem that few studies have investigated migrant English instructors’ professional learning and support issues in the workplace, precisely that of English instructors working with adult learners in Canada. While appropriate social and professional support for migrant English instructors is required throughout the country, the present workplace realities in Ontario's English language programs need to be heard soon. For that purpose, the conceptualization of this study is crucial. It makes the investigation of under-represented instructors’ under-researched social phenomena, workplace learning and support, viable and rigorous. This paper demonstrates the robust theorization of English instructors’ workplace experiences using Mezirow’s Transformative Learning Theory in the English language teacher education field. 

Research Design for Developing and Validating Ice-Hockey Team Diagnostics Scale

In the modern world, ice-hockey (and in a broader sense, team sports) is becoming an increasingly popular field of entertainment. Although the main element is most likely perceived as the show itself, winning is an inevitable part of the successful operation of any sports team. In this paper, the author creates a research design allowing to develop and validate an ice-hockey team-focused diagnostics scale, which enables researchers and practitioners to identify the problems associated with underperforming teams. The construction of the scale starts with personal interviews with experts of the field, carefully chosen from Hungarian ice-hockey sector. Based on the interviews, the author is shown to be in the position to create the categories and the relevant items for the scale. When constructed, the next step is the validation process on a Hungarian sample. Data for validation are acquired through reaching the licensed database of the Hungarian Ice-Hockey Federation involving Hungarian ice-hockey coaches and players. The Ice-Hockey Team Diagnostics Scale is to be created to orientate practitioners in understanding both effective and underperforming team work.

Participatory Financial Inclusion Hypothesis: A Preliminary Empirical Validation Using Survey Design

In Nigeria, enormous efforts/resources had, over the years, been expended on promoting financial inclusion (FI); however, it is seemingly discouraging that many of its self-declared targets on FI remained unachieved, especially amongst the Rural Dwellers and Actors in the Informal Sectors (RDAIS). Expectedly, many reasons had been earmarked for these failures: low literacy level, huge informal/rural sectors etc. This study posits that in spite of these truly-debilitating factors, these FI policy failures could have been avoided or mitigated if the principles of active and better-managed citizens’ participation had been strictly followed in the (re)design/implementation of its FI policies. In other words, in a bid to mitigate the prevalent financial exclusion (FE) in Nigeria, this study hypothesizes the significant positive impact of involving the RDAIS in policy-wide decision making in the FI domain, backed by a preliminary empirical validation. Also, the study introduces the RDAIS-focused Participatory Financial Inclusion Policy (PFIP) as a major FI policy regeneration/improvement tool. The three categories of respondents that served as research subjects are FI experts in Nigeria (n = 72), RDAIS from the very rural/remote village of Unguwar Dogo in Northern Nigeria (n = 43) and RDAIS from another rural village of Sekere (n = 56) in the Southern region of Nigeria. Using survey design (5-point Likert scale questionnaires), random/stratified sampling, and descriptive/inferential statistics, the study often recorded independent consensus (amongst these three categories of respondents) that RDAIS’s active participation in iterative FI policy initiation, (re)design, implementation, (re)evaluation could indeed give improved FI outcomes. However, few questionnaire items also recorded divergent opinions and various statistically (in)significant differences on the mean scores of these three categories. The PFIP (or any customized version of it) should then be carefully integrated into the NFIS of Nigeria (and possibly in the NFIS of other developing countries) to truly/fully provide FI policy integration for these excluded RDAIS and arrest the prevalence of FE.

Numerical and Experimental Analyses of a Semi-Active Pendulum Tuned Mass Damper

Modern structures such as floor systems, pedestrian bridges and high-rise buildings have become lighter in mass and more flexible with negligible damping and thus prone to vibration. In this paper, a semi-actively controlled pendulum tuned mass dampers (PTMD) is presented that uses air springs as both the restoring (resilient) and energy dissipating (damping) elements; the tuned mass damper (TMD) uses no passive dampers. The proposed PTMD can readily be fine-tuned and re-tuned, via software, without changing any hardware. Almost all existing semi-active systems have the three elements that passive TMDs have, i.e., inertia, resilient, and dissipative elements with some adjustability built into one or two of these elements. The proposed semi-active air suspended TMD, on the other hand, is made up of only inertia and resilience elements. A notable feature of this TMD is the absence of a physical damping element in its make-up. The required viscous damping is introduced into the TMD using a semi-active control scheme residing in a micro-controller which actuates a high-speed proportional valve regulating the flow of air in and out of the air springs. In addition to introducing damping into the TMD, the semi-active control scheme adjusts the stiffness of the TMD. The focus of this work has been the synthesis and analysis of the control algorithms and strategies to vary the tuning accuracy, introduce damping into air suspended PTMD, and enable the PTMD to self-tune itself. The accelerations of the main structure and PTMD as well as the pressure in the air springs are used as the feedback signals in control strategies. Numerical simulation and experimental evaluation of the proposed tuned damping system are presented in this paper.

Robot-assisted Relaxation Training for Children with Autism Spectrum Disorders

Cognitive Behavioral Therapy (CBT) has been proven an effective tool to address anger and anxiety issues in children and adolescents with Autism Spectrum Disorders (ASD). Robot-enhanced therapy has been used in psychosocial and educational interventions for children with ASD with promising results. Whenever CBT-based techniques were incorporated in robot-based interventions, they were mainly performed in group sessions. Objectives: The study’s main objective was the implementation and evaluation of the effectiveness of a relaxation training intervention for children with ASD, delivered by the social robot NAO. Methods: 20 children (aged 7–12 years) were randomly assigned to 16 sessions of relaxation training implemented twice a week. Two groups were formed: the NAO group (children participated in individual sessions with the support of NAO) and the control group (children participated in individual sessions with the support of the therapist only). Participants received three different relaxation scenarios of increasing difficulty (a breathing scenario, a progressive muscle relaxation scenario and a body scan medication scenario), as well as related homework sheets for practicing. Pre- and post-intervention assessments were conducted using the Child Behavior Checklist (CBCL) and the Strengths and Difficulties Questionnaire for parents (SDQ-P). Participants were also asked to complete an open-ended questionnaire to evaluate the effectiveness of the training. Parents’ satisfaction was evaluated via a questionnaire and children satisfaction was assessed by a thermometer scale. Results: The study supports the use of relaxation training with the NAO robot as instructor for children with ASD. Parents of enrolled children reported high levels of satisfaction and provided positive ratings of the training acceptability. Children in the NAO group presented greater motivation to complete homework and adopt the learned techniques at home. Conclusions: Relaxation training could be effectively integrated in robot-assisted protocols to help children with ASD regulate emotions and develop self-control.

The Art of Leadership: Skills to Inspire the Team to Overcome Project Challenges and Achieve Their Goals

This paper highlights skills that a leader needs to acquire to lead a team successfully. With an appropriate vision and strategy, a team can be inspired, influenced and easily led. The importance of setting codes of conduct and establishing mutual agreements between the team members can help in minimizing issues and improving overall productivity. Leadership skills include the power of questioning (PoQ), effective communication, identification of team member responsibilities, and assessment of self and the team. This paper will highlight the impact of good leadership on work progress and overall team performance. The paper explains how leaders make correct decisions by avoiding hasty actions that could generate new errors, mistakes, and issues. The importance of positive expectations for the team is addressed in this paper that could result in efficient control of the work with better outcomes.

Mnemotopic Perspectives: Communication Design as Stabilizer for the Memory of Places

The ancestral relationship between humans and geographical environment has long been at the center of an interdisciplinary dialogue, which sees one of its main research nodes in the relationship between memory and places. Given its deep complexity, this symbiotic connection continues to look for a proper definition that appears increasingly negotiated by different disciplines. Numerous fields of knowledge are involved, from anthropology to semiotics of space, from photography to architecture, up to subjects traditionally far from these reasonings. This is the case of Design of Communication, a young discipline, now confident in itself and its objectives, aimed at finding and investigating original forms of visualization and representation, between sedimented knowledge and new technologies. In particular, Design of Communication for the Territory offers an alternative perspective to the debate, encouraging the reactivation and reconstruction of the memory of places. Recognizing mnemotopes as a cultural object of vertical interpretation of the memory-place relationship, design can become a real mediator of the territorial fixation of memories, making them increasingly accessible and perceptible, contributing to build a topography of memory. According to a mnemotopic vision, Communication Design can support the passage from a memory in which the observer participates only as an individual to a collective form of memory. A mnemotopic form of Communication Design can, through geolocation and content map-based systems, make chronology a topography rooted in the territory and practicable; it can be useful to understand how the perception of the memory of places changes over time, considering how to insert them in the contemporary world. Mnemotopes can be materialized in different format of translation, editing and narration and then involved in complex systems of communication. The memory of places, therefore, if stabilized by the tools offered by Communication Design, can make visible ruins and territorial stratifications, illuminating them with new communicative interests that can be shared and participated.

The Impact of Alumina Cement on Properties of Portland Cement Slurries and Mortars

The addition of a small amount of alumina cement to Portland cement results in immediate setting, a rapid increase in the compressive strength and a clear increase of the adhesion to concrete substrate. This phenomenon is used, among others, for the production of liquid floor self-levelling compounds. Alumina cement is several times more expensive than Portland cement and is a component having a significant impact on prices of products manufactured with its use. For the production of liquid floor self-levelling compounds, low-alumina cement containing approximately 40% Al2O3 is normally used. The aim of the study was to determine the impact of Portland cement with the addition of alumina cement on the basic physical and mechanical properties of cement slurries and mortars. CEM I 42.5R and three types of alumina cement containing 40%, 50% and 70% of Al2O3 were used for the tests. Mixes containing 4%, 6%, 8%, 10% and 12% of different varieties of alumina cement were prepared; for which, the time of initial and final setting, compressive and flexural strength and adhesion to concrete substrate were determined. The analysis of the obtained test results showed that a similar immediate setting effect and clearly better adhesion strength can be obtained using the addition of 6% of high-alumina cement than 12% of low-alumina cement. As the prices of these cements are similar, this can give significant financial savings in the production of liquid floor self-levelling compounds.

Impact of Climate Change on Sea Level Rise along the Coastline of Mumbai City, India

Sea-level rise being one of the most important impacts of anthropogenic induced climate change resulting from global warming and melting of icebergs at Arctic and Antarctic, the investigations done by various researchers both on Indian Coast and elsewhere during the last decade has been reviewed in this paper. The paper aims to ascertain the propensity of consistency of different suggested methods to predict the near-accurate future sea level rise along the coast of Mumbai. Case studies at East Coast, Southern Tip and West and South West coast of India have been reviewed. Coastal Vulnerability Index of several important international places has been compared, which matched with Intergovernmental Panel on Climate Change forecasts. The application of Geographic Information System mapping, use of remote sensing technology, both Multi Spectral Scanner and Thematic Mapping data from Landsat classified through Iterative Self-Organizing Data Analysis Technique for arriving at high, moderate and low Coastal Vulnerability Index at various important coastal cities have been observed. Instead of data driven, hindcast based forecast for Significant Wave Height, additional impact of sea level rise has been suggested. Efficacy and limitations of numerical methods vis-à-vis Artificial Neural Network has been assessed, importance of Root Mean Square error on numerical results is mentioned. Comparing between various computerized methods on forecast results obtained from MIKE 21 has been opined to be more reliable than Delft 3D model.

Improving Subjective Bias Detection Using Bidirectional Encoder Representations from Transformers and Bidirectional Long Short-Term Memory

Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.