Miracle-dz/UniFAR-FTUs huggingface dataset:
Teaching Cultural Heritage through a Narrative-based Game

Games are used in various learning situations and domains, among which is cultural heritage. Storytelling is used in games regarding cultural places, but it often takes a simple form. Thus, the authors’ aim is to investigate the possibility to communicate cultural content through a narrative-based game that can function with multiple narratives. Another core element of our design is the less exploited in serious games combination of endogenous cooperation and competition. The social dimension of our design was expressed through features of Classroom Multiplayer Presential Games (CMPGs), in respect of using a one-to-many game environment projected on a single screen, while enhancing collaborative work in small teams. After providing an overview of the game, we briefly explain how this was implemented with the use of Twine, a free authoring tool for the creation of interactive stories and text-based games. Subsequently, we present the two interventions we conducted, one with teenage students (n = 19) and one with post-graduate students (n = 14), to test how our game design functions with real users. A mixed research methodology was followed in the two trials and data were collected through observation, focus group discussions, short questionnaires, and game reports. Findings indicated that the suggested design is playable but provided helpful insights into its future improvements. The game managed to engage both teenagers and adults with the cultural content and create motivation towards it. Learning gains were registered for both groups, but these were more appreciated by the adult participants, who additionally found the game to be more entertaining. The limited character of our results imposes the need for future extensive evaluation of the game design in both formal and non-formal educational contexts.
Postoperative Prolonged Mechanical Ventilation in Patients With Newly Diagnosed Glioblastoma—An Unrecognized Prognostic Factor

Objective Although the treatment of glioblastoma patients is well established in neuro-oncological surgery, precious scarce data is available on patients with glioblastoma requiring postoperative prolonged mechanical ventilation (PMV). Therefore, the aim of the present study was to determine the influence of PMV on overall survival (OS) in patients with glioblastoma. Methods Patients with newly diagnosed glioblastoma who had undergone surgical therapy and complete subsequent neuro-oncological treatment at the authors’ neuro-oncological center from January 2013 to December 2018 were selected and included in the further analysis. PMV was defined as mechanical ventilation for more than 24 h after surgery. Survival analyses were performed, including established prognostic factors such as age, Karnofsky performance score, MGMT-promoter methylation status and extent of resection. Results A total of 240 patients with newly diagnosed glioblastoma and subsequent surgical treatment were identified. 13 patients (5%) suffered from PMV during the treatment course of glioblastoma. All but one patient were successfully weaned from mechanical ventilation. Patients suffering from PMV achieved significantly less often favorable functional outcome after 3, 6, 9, and 12 months compared to patients without PMV. Multivariate analysis revealed PMV to constitute a significant prognostic factor for OS, independent of other prognostic factors (p<0.0001, OR 6.7, 95% CI 3.2–13.8). Conclusions The present study identifies PMV as significantly associated with impaired functional outcome and poor OS in patients suffering from newly diagnosed glioblastoma. These findings encourage further efforts to investigate/assess this prognostic factor in future studies.
Optimism as Predictor of Psychological Well Being among Adolescents

Optimism is associated with positive outcomes in relationships in general, possibly as a result of processes that promote and maintain Psychological Well-being. The aim of this study was to investigate the relationship between Optimism and Psychological Well being. It also investigated the difference between Hindu and Muslim, male and female Adolescents on Psychological Well-Being and Optimism. For this study 120 Adolescents were selected from Aligarh Muslim University, comprises 60 Hindu male & female and 60 Muslim male & female through random sampling. Pearson product moment correlation was also used for measuring the relationship between Optimism and Psychological Well-being, t-test was used to know the difference between male and female & Hindu and Muslim adolescents. Result shows that there is significant positive correlation between optimism and psychological well-being and there was insignificant difference between male and female adolescents on optimism and psychological well-being.
The Extracellular Matrix-Derived Biomarkers for Diagnosis, Prognosis, and Personalized Therapy of Malignant Tumors

The tumor biomarkers already have proven clinical value and have become an integral part in cancer management and modern translational oncology. The tumor tissue microenvironment (TME), which includes extracellular matrix (ECM), signaling molecules, immune and stromal cells, and adjacent non-tumorous tissue, contributes to cancer pathogenesis. Thus, TME-derived biomarkers have many clinical applications. This review is predominately based on the most recent publications (manuscripts published in a last 5 years, or seminal publications published earlier) and fills a gap in the current literature on the cancer biomarkers derived from the TME, with particular attention given to the ECM and products of its processing and degradation, ECM-associated extracellular vesicles (EVs), biomechanical characteristics of ECM, and ECM-derived biomarkers predicting response to the immunotherapy. We discuss the clinical utility of the TME-incorporating three-dimensional in vitro and ex vivo cell culture models for personalized therapy. We conclude that ECM is a critical driver of malignancies and ECM-derived biomarkers should be included in diagnostics and prognostics panels of markers in the clinic.
Massively Parallel Join Algorithms

Due to the rapid development of massively parallel data processing systems such as MapReduce and Spark, there have been revived interests in designing algorithms in a massively parallel computational model. Computing multi-way joins, as one of the central algorithmic problems in databases, has received much attention recently. This paper surveys some of the recent algorithms, as well as lower bounds. We focus on multi-round algorithms, while referring readers to [27] for single-round algorithms.
From Immersion’s Bleeding Edge to the Augmented Telegrapher

Immersive technologies can be used to broaden the possibilities of storytelling in heritage contexts to enrich the ways in which museum collections are interpreted and to facilitate more active engagement with history. To this end, as part of the United Kingdom’s Industrial Strategy, new models, methods, and workflows are being developed to help realise the value of such technologies across the country. However, prior art shows that immersive technologies present particular challenges with respect to usability, uptake, onboarding, sustainability, and authenticity. Towards addressing these challenges, a programme of action research has been established across a series of museums in Cornwall. Focusing upon the Augmented Telegrapher at Porthcurno Telegraph Museum, a co-designed social escape room experience that utilises the Microsoft HoloLens to simulate a telegraphy training exercise from World War 2, this article addresses what partnerships with smaller, rural establishments need to effectively realise the value of immersive technologies. Using the work of Erik Champion as a critical lens, the article shows how an iterative constructivist approach leveraging game design principles can underpin success. This is distilled into a set of recommended interaction blueprints and transdisciplinary working practices that will be of interest to curators, researchers, and serious game developers.
SkyCore: Moving Core to the Edge for Untethered and Reliable UAV-based LTE Networks

The advances in unmanned aerial vehicle (UAV) technology have empowered mobile operators to deploy LTE base stations (BSs) on UAVs, and provide on-demand, adaptive connectivity to hotspot venues as well as emergency scenarios. However, today's evolved packet core (EPC) that orchestrates the LTE RAN faces fundamental limitations in catering to such a challenging, wireless and mobile UAV environment, particularly in the presence of multiple BSs (UAVs). In this work, we argue for and propose an alternate, radical edge EPC design, called SkyCore that pushes the EPC functionality to the extreme edge of the core network - collapses the EPC into a single, light-weight, self-contained entity that is co-located with each of the UAV BS. SkyCore incorporates elements that are designed to address the unique challenges facing such a distributed design in the UAV environment, namely the resource-constraints of UAV platforms, and the distributed management of pronounced UAV and UE mobility. We build and deploy a fully functional version of SkyCore on a two-UAV LTE network and showcase its (i) ability to interoperate with commercial LTE BSs as well as smartphones, (ii) support for both hotspot and standalone multi-UAV deployments, and (iii) superior control and data plane performance compared to other EPC variants in this environment.
On Alignment of Textual Elements in a Parallel Diachronic Corpus

This paper presents the description of some tools and resources for aligning diachronic parallel texts. We try to emphasize the idea of improving the lexicographical similarity between words and expressions used in old and modern texts, using a special technique of natural language processing namely the BLEU score. The overall result of the research is a package of language tools and resources, which will serve to the automatic alignment of the old Romanian text with the modern text.
Crowd Motion Editing Based on Mesh Deformation

Computer simulation is a significant technology on making great scenes of crowd in the film industry. However, current animation making process of crowdmotion requires large manual operations which are time-consuming and inconvenient. To solve the above problem, this paper presents an editing method on the basis of mesh deformation that can rapidly and intuitively edit crowd movement trajectories from the perspective of time and space. The method is applied to directly generate and adjust the crowd movement as well as avoid the crash between crowd and obstacles. As for collisions within the crowd that come along with path modification problem, a time-based solution is put forward to avoid this situation by retaining relative positions of individuals. Moreover, an experiment based on a real venue was performed and the result indicates that the proposed method can not only simplify the editing operations but also improve the efficiency of crowd motion editing.
A Separation Factor Method for the Analysis of Ideal Binary Mixtures in Gas-Solid Adsorption

Abstract A correlation formula based on the separation factor is proposed for the mixture concentration in the adsorbed phase of an ideal binary solution in gas-solid adsorption. This formula is shown to apply to two binary systems (viz., 1,3-butadiene and n-butane on cross-linked polystyrene at 25°C, and acetylene and ethane on activated carbon at 25°C) with similar molecular and thermodynamic properties in the two components for each system. Comparison between the calculated and experimental values of the separation factor showed that the assumption of an ideal mixture is justified for each of these two binary systems. Mixture isotherms for the two ideal binary systems are calculated by the proposed correlation formula from the corresponding single-component isotherms. Good agreement between the calculated and experimental mixture isotherm data confirms that a binary system of two components with similar molecular properties (viz., molecular weight, normal boiling point, vapor pressure, number of carbon.
Low-depth quantum state preparation

A crucial subroutine in quantum computing is to load the classical data of $N$ complex numbers into the amplitude of a superposed $n=\lceil \log_2N\rceil$-qubit state. It has been proven that any algorithm universally implementing this subroutine would need at least $\mathcal O(N)$ constant weight operations. However, the proof assumes that only $n$ qubits are used, whereas the circuit depth could be reduced by extending the space and allowing ancillary qubits. Here we investigate this space-time tradeoff in quantum state preparation with classical data. We propose quantum algorithms with $\mathcal O(n^2)$ circuit depth to encode any $N$ complex numbers using only single-, two-qubit gates and local measurements with ancillary qubits. Different variances of the algorithm are proposed with different space and runtime. In particular, we present a scheme with $\mathcal O(N^2)$ ancillary qubits, $\mathcal O(n^2)$ circuit depth, and $\mathcal O(n^2)$ average runtime, which exponentially improves the conventional bound. While the algorithm requires more ancillary qubits, it consists of quantum circuit blocks that only simultaneously act on a constant number of qubits and at most $\mathcal O(n)$ qubits are entangled. We also prove a fundamental lower bound $\mit\Omega(n)$ for the minimum circuit depth and runtime with arbitrary number of ancillary qubits, aligning with our scheme with $\mathcal O(n^2)$. The algorithms are expected to have wide applications in both near-term and universal quantum computing.
Forecasting of ionospheric time delays at low latitude region using ARMA model under Geomagnetic storm conditions

The accurate forecasting of ionospheric disturbances is a strong requirement for reliable performance of many applications such as communication, navigation and surveillance system. Accurate ionospheric time delay modeling and forecasting is necessary especially for Indian low latitude region due to the of the Appleton anomaly, Equatorial Ionization Anomaly (EIA), equatorial spread F. Ionospheric Time delay is responsible for the range error in GPS signals which is proportional to the total electron content (TEC). The intent of this work is to forecast (1 hour ahead) the TEC variations at low latitude regions during eruptive events. Dual frequency GPS receiver at K L University, Vaddeswaram (16.31° N, 80.37° E), India (falls under the transition zone of the Equatorial Ionization Anomaly in low latitude) is considered for the analysis. An Auto Regressive Moving Average (ARMA) model is used for short term forecasting of the VTEC (Vertical TEC) values. ARMA model with the order p = 2 and q = 4 is selected. Three recent and most severe Geomagnetic storms occurred in the solar maximum period of March 2013 to February 2014 are used to test the performance of ARMA model (March17, 2013, June 29, 2013, February 19, 2014 and February 20, 2014 storms are analyzed). During March 17, 2013 storm enhancement in VTEC with Kp value 6 and Disturbance storm time (Dst) index -137nT is observed. During June 29, 2013 storm VTEC depletions with Kp value 7 and Dst -98nT is observed. During February 19, 2014 storm VTEC enhancement occurred with Kp value 6 and Dts -123nT is observed. The forecasted VTEC values are compared with original VTEC values. The RMSE of ARMA model is about 0.4 to 1.486 m. The preliminary results indicate that ARMA model would be an effective tool for developing early warning ionospheric disturbances.
Relationship Between GDF5 +104T/C Polymorphism and the Susceptibility of Lumbar Disc Degeneration: A Meta-Analysis

Lumbar disc degeneration (LDD) is a multifactorial and chronic disease with a complex genetic background. Previous studies have reported the strong association between growth differentiation factor 5 (GDF5) +104T/C polymorphism and the risk of LDD in different ethnic populations. The aim of this study was to analyze the association between the GDF5 +104T/C polymorphism and the susceptibility of LDD by a meta-analysis. Potentially relevant studies were selected by electronic databases (PubMed, EMBASE, Web of science, the Cochrane Library Chinese National Knowledge Infrastructure) up to 10th April 2017. Summary odds ratio (OR) and 95% confidence intervals (CIs) were used to assess the strength of association between the GDF5 +104T/C polymorphism and LDD risk. Six case-control studies, including 1107 LDD cases and 4353 controls, were included. The combined results showed that GDF5 +104T/C polymorphism was significantly associated with increased susceptibility to LDD at the allele level (T vs . C: OR = 1.52, 95%CI = 1.21-1.90) and genotype level (TT vs . CC: OR = 2.43, 95%CI = 1.81-3.25; TC vs . CC: OR = 1.84, 95%CI = 1.37-2.47; TT+TC vs . CC: OR = 2.14, 95%CI = 1.61-2.84; TT vs . TC+CC: OR = 1.42, 95%CI = 1.01-1.99) in the overall population. After stratified by ethnicity, we found a strong significant association (OR = 1.80 to 3.70, all P <0.05) in Asian population and weaker associations (OR =1.20 to 1.64, all P <0.05) in Caucasian population. This meta-analysis suggests an increased risk of GDF5 +104T/C polymorphism against intervertebral disc degeneration among populations especially in Asians.
The Information Systems Student

It is widely considered that ‘friction’ in user experience and digital journeys leads to a negative user engagement, drop o ff rates, and ultimately impacts pro fi ts for business in the digital space. The aspect of individuals’ perception to risk, privacy and convenience is brought in as it directly pertains to the context within which this study occurs. Here, friction is studied in the context of Open Banking solutions, where to allow for the service to be provided, customers need to consent their data to be shared. Mocked-up digital journeys of a consent model are presented and discussed with participants in focus groups. This paper aims to explore what user perceptions are about friction and how these perceptions and behaviours are impacted by their preferences and expectations about privacy, and convenience. Expectancy Theory dimensions – Expectancy, Instrumentality and Valence - are used to analyse and discuss the fi ndings. This paper is an abridged adaptation of the author’s Masters’ Thesis Dissertation, for the Management of Information Systems and Digital Innovation course at the LSE, with an original word count of 11,000 words. Thus, fi ndings have been summarised in a table and representative quotes have been omitted due to the wordcount constraints in the iSChannel journal. Appendices and visual representations of the digital journeys, have also been omitted in this publication (link to full thesis: https://bit.ly/2N2MGeQ).
Design and Performance Calculation using MATLAB for Multiple Effect Evaporator Desalination Process with Different Configurations

In this study modular MATLAB program is presented, where an equation oriented programming with MatLab 2020 is used to provide friendly user-interface of the developed program. This program can be used to perform reliable design, performance, and optimization calculations for multiple effect evaporator (MEE) desalination systems with different configurations under different operating conditions. In addition, by using this program modifications for existing desalination plants can be conducted. The developed program manipulates the considered configuration based on the graph theory with the number of units, streams and their types where the relationships between the streams and the units are identified. The program constructs a large matrix that is solved for temperatures, flow rates of the streams and the heat transfer area of the effects and heat exchangers. The accuracy and reliability of our program were verified using six different cases from the available data in the literature. These cases include forward, backward, mixed, and parallel feed MEE configurations with and without thermal-vapor compressor. Different computation modes were used for large number of plant configurations, this illustrates the capability of the developed program. Comparable and accurate results were obtained, the absolute relative errors for the studied cases ranged from 0.412% to 11.292%. This indicates that the program has potential applicability to work with different configuration for Multiple Effect Evaporator (MEE) desalination plants.
The reliability of rating curve estimates of suspended sediment yield: some further comments

A number of recent papers have suggested that the underestimation bias inherent in the use of log-transformed regression to derive suspended sediment rating relationships is a major cause of the error commonly associated with rating curve estimates of suspended sediment yield, and that this bias can be largely removed by applying simple correction factors. However, there is conflicting evidence as to the extent to which bias-corrected rating estimates provide reliable values of sediment yield. In order to investigate this uncertainty further, the authors have assembled continuous records of suspended sediment concentration and discharge for three rivers in Devon, UK. These records have been used to calculate actual loads and to synthesize a variety of replicate data sets, representing different manual sampling strategies, for rating curve derivation. The resulting load estimates obtained using rating curves and bias-corrected rating curves have been compared with the actual loads. The results indicate that bias-correction procedures do not provide accurate estimates for these rivers and that other sources of error associated with rating curves are more important in producing inaccurate estimates. La validité des données relatives aux charges solides en suspension obtenues en utilisant les courbes de tarage: quelques commentaires supplémentaires Résumé Plusieurs articles récents ont prétendu que la tendance à la sous-estimation inhérente à l'emploi de la régression des logarithmes pour dériver les courbes de tarage est une cause majeure des erreurs associées fréquemment aux données relatives aux charges solides en suspension obtenues à partir des courbes de tarage, et que cette tendance peut être corrigée par l'application de facteurs de correction simples. Cependant il n'est pas évident que les courbes de tarage corrigées de cette tendance puissent fournir des estimations exactes. Afin d'examiner cette incertitude plus à fond, les auteurs ont assemblé des données continues des concentrations des sédiments en suspension et des écoulements pour trois rivières du
CEAT: A Cluster based Energy Aware Scheduler for Real-Time Heterogeneous Systems

Modern real-time systems based on heterogeneous multicore platforms can efficiently meet the disparate and high computation needs of the applications. The management of energy has become a topic of an incredible enthusiasm for analysts and practitioners during the past few years. Hence, this research presents a heuristic strategy named, CEAT, for energy-aware scheduling of a set of real-time periodic tasks on a DVFS enabled heterogeneous multicore platform. The presented strategy operates in three stages, namely Deadline Partitioning, Task-to-Core Allocation, and Energy-Aware Scheduling. Our experimental analysis shows that CEAT is not only able to successfully schedule more task sets (as high as 3.44% and 21.83%) compared to state-of-the-art [1] but also improve energy savings in the system.