Miracle-dz/UniFAR-FTUs huggingface dataset:
An Executable Ontology for Social Simulation

Social simulations often need many of the same things – characters, locations, interactions, and relationships to name a few. These regular components of simulators are present in games ranging from major titles like The Sims [1]–[3], indie classics like Dwarf Fortress [4], and experimental interactive experiences such as Bad News (or at least in the simulator Bad News is build off – Talk of the Town ) [5], [6]. Not only do these components need reimplementation in each sim, but they are also often difficult for anyone but original developers to modify [7]. In this paper we discuss how social simulators can be declaratively authored from an ontology-based representation while still maintaining playable framerates. We argue that an ontology for these entities allows for the expressive and flexible creation of social simulations. We present a language and ontology, Socialog, which enables one to declaratively author a simulation with these ontological statements while maintaining very good performance.
Spatiotemporal dynamics of synthetic microbial consortia in micro(cid:29)uidic devices

Synthetic microbial consortia consist of two or more engineered strains that grow together and share the same resources. When intercellular signaling pathways are included in the engineered strains, close proximity of the microbes can generate complex dynamic behaviors that are di(cid:30)cult to obtain using a single strain. However, when a consortium is not cultured in a well-mixed environment the constituent strains passively compete for space as they grow and divide, complicating cell-cell signaling. Here, we explore the temporal dynamics of the spatial distribution of consortia co-cultured in micro(cid:29)uidic devices. To do this, we grew two di(cid:27)erent strains of Escherichia coli in micro(cid:29)uidic devices with cell-trapping regions (traps) of several di(cid:27)erent designs. We found that the size and shape of the traps are critical determinants of spatiotemporal dynamics. In small traps, cells can easily signal one another but the relative proportion of each strain within the trap can (cid:29)uctuate wildly. In large traps, the relative ratio of
Performance Assessment and Application of Caeli — A high-performance Raman lidar for diurnal profiling of Water Vapour, Aerosols and Clouds

Caeli is the CESAR Water Vapour, Aerosol and Cloud Lidar and is a multiwavelength, high-performance Raman lidar, capable of providing round-the-clock measurements. It is deployed at the Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands (51 58’N, 4 56’E). The instrument was developed as a key instrument for CESAR to strengthen the sites capabilities as a profiling station for atmospheric research and climate studies. Next to the lidar, other profiling techniques also routinely operated provide synergy in observations. Since the deployment at CESAR in May 2008, Caeli contributes to observation programmes and studies. The instrument is part of EARLINET, has provided data during the IMPACT and CINDI campaigns and provides correlative measurements for CALIPSO. Recently, the instrument was compared to its peers in the EARLINET Reference Lidar Intercomparison (EARLI09) in Leipzig. This paper describes the Caeli instrument configuration and shows examples of application of the data. Also, preliminary intercomparison results are shown from EARLI09.
Mismatch Quantification in Acute Stroke Techniques for MR Perfusion-Diffusion Comparison of 10 TTP and Tmax Estimation

BACKGROUND AND PURPOSE: The mismatch between lesions identiﬁed in perfusion-and diffusion-weighted MR imaging is typically used to identify tissue at risk of infarction in acute stroke. The purpose of this study was to analyze the variability of mismatch volumes resulting from different time-to-peak or time-to-maximum estimation techniques used for hypoperfused tissue deﬁnition. MATERIALS AND METHODS: Data of 50 patients with middle cerebral artery stroke and intracranial vessel occlusion imaged within 6 hours of symptom onset were analyzed. Therefore, 10 different TTP/Tmax techniques and delay thresholds between (cid:1) 2 and (cid:1) 12 seconds were used for calculation of perfusion lesions. Diffusion lesions were semiautomatically segmented and used for mismatch quantiﬁcation after registration. RESULTS: Mean volumetric differences up to 40 and 100 mL in individual patients were found between the mismatch volumes calculated by the 10 TTP/Tmax estimation techniques for typically used delay thresholds. The application of typical criteria for the identiﬁcation of patients with a clinically relevant mismatch volume resulted in different mismatch classiﬁcations in (cid:1) 24% of all cases, depending on the TTP/Tmax estimation method used. CONCLUSIONS: Highvariationsoftissue-at-riskvolumeshavetobeexpectedwhenusingdifferentTTP/Tmaxestimationtechniques.An adaption of different techniques by using correction formulas may enable more comparable study results until a standard has been established by agreement.
Taming the Turing Test: Exploring Machine Learning Approaches to Discriminate Human vs. AI-Generated Texts

This paper describes the participation of the turing-testers team in the AuTexTification shared task, at IberLEF 2023, on Automated Text Identification. In this shared task, two subtasks has been proposed for English and Spanish: subtask 1, on determining whether a text has been automatically generated or it is a human-written text and, subtask 2, on the attribution of Large Language Models to automatically generated texts. We have addressed subtask 1 in both languages testing traditional machine and deep learning approaches and exploring with the integration of metadata related to readability, comprehensi-bility, complexity, sentiment, emotion and toxicity of texts. In total, 76 runs were submitted for subtask 1 in English and 52 runs for subtask 1 in Spanish. The best run sent by our team placed in position 27th for English and position 9th for Spanish with a macro F1-score of 64.32 and 66.5, respectively.
Long-term high-yield skeletal muscle stem cell expansion through staged perturbation 3 of cytokine signaling in a soft hydrogel culture platform 4

30 Muscle stem cells (MuSCs) are an essential stem cell population for skeletal muscle homeostasis and 31 regeneration throughout adulthood. MuSCs are an ideal candidate for cell therapies for chronic and acute 32 muscle injuries and diseases given their inherent ability to self-renew and generate progenitor cells 33 capable of myogenic commitment and fusion. Given their rarity and propensity to lose stem-cell potential 34 in prolonged culture, methods for ex vivo MuSC expansion that achieve clinical-scale stem cell yields 35 represent a critical unmet need in muscle cell-therapeutic development. Here, we tested a 36 microenvironment engineering approach to achieve long-term adult mouse MuSC expansion suitable for 37 clinical demands through the combined optimization of techniques previously reported to achieve small-38 yield MuSC expansion in short-term cultures. We developed an optimized protocol for high-yield MuSC 39 expansion through the combination of inflammatory cytokine and growth factor co-stimulation, temporally-40 staged inhibition of the p38α/β mitogen activated protein kinase signaling pathway, and modulation of 41 substrate rigidity in long-term hydrogel cultures. We found that, on soft, muscle-mimicking (12 kPa) 42 hydrogel substrates, a mixture of the cytokines TNF-α, IL-1α, IL-13, and IFN-γ and the growth factor 43 FGF2 stimulated robust exponential proliferation of adult MuSCs from both wildtype and mdx dystrophic 44 mice for up to five weeks of culture that was accompanied by a phenotype shift towards committed 45 myocytes. After observing that the temporal variation in myogenic commitment coincided with an 46 oscillatory activation of p38α/β signaling, we tested a late-stage p38α/β inhibition strategy and found that 47 blocking p38α/β signaling after three weeks, but not earlier, substantially enhanced cell yield, stem-cell 48 phenotypes, and, critically, preserved transplantation potential for up to five weeks of FGF2/cytokine mix 49 culture on soft hydrogels. Notably, this retention of transplant engraftment potency was not observed on 50 traditional plastic substrates. We estimate that this protocol achieves >10 8 -fold yield in Pax7 + stem cells 51 from each starting MuSC,
Antecedents of Brand personality: Brand Communication, Playing the Mediating Role

There are limited studies available which measure the antecedents of brand personality and explain the mechanism through mediation of brand communication. This study develops a research model to addresses this gap by utilizing a well-known theory of self-congruity to explain the mediating role played by brand communication between the two variables i.e corporate visual identity elements and brand personality. Cellular service providing companies of Pakistan are selected as the population of this study. A sampling data of 1536 users of cellular service providing companies of Pakistan including Telenor, Ufone, Zong and Jazz was collected through convenience sampling and tested using AMOS. Findings of the study reveal a positive association between corporate visual identity and brand personality and also shows that brand communication significantly mediated this relationship. In this way it not only adds to the literature but also help the practitioners and marketing executives develop their branding strategies while keeping in mind the brand personality concept.
Random Waves on a Vertically-sheared Current

This paper considers the interaction between two-dimensional random waves and a co-linear, depth-varying, current. Two rotational wave-current models, capable of incorporating the effects of a depth dependent vorticity distribution, are combined with a conservation equation describing the total energy flux. This provides new solutions capable of predicting the change in a wave spectrum due to the interaction with a current. Comparisons between these solutions and a new data set confirms that a successful wavecurrent model must incorporate both the Doppler shift associated with the surface current and the near-surface vorticity distribution. Typical design calculations, based on a uniform current approximation, commonly satisfy neither of these constraints. Accordingly, they are shown to provide a poor description of the laboratory data. Furthermore, the nature of the wave-current interaction, which is shown to be significantly larger than the nonlinear wave-wave interactions, involves both a currentinduced change in the wave motion and a wave-induced change in the current. While the former is reasonably well understood, the latter remains difficult to predict. Indeed, both parts of this overall interaction are shown to be strongly vorticity dependent.
Metalearning: Applications to Data Mining

Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.
Quadratic Dynamic Matrix Control for Fast Cloth Manipulation

Robotic cloth manipulation is an increasingly relevant area of research, challenging classic control algorithms due to the deformable nature of cloth. While it is possible to apply linear model predictive control to make the robot move the cloth according to a given reference, this approach suffers from a large dimensionality of the state-space representation of the cloth models. To address this issue, in this work we study the application of an input-output model predictive control strategy, based on quadratic dynamic matrix control, to robotic cloth manipulation. To account for uncertain disturbances on the cloth's motion, we further extend the algorithm with suitable chance constraints. In extensive simulated experiments, involving disturbances and obstacle avoidance, we show that quadratic dynamic matrix control can be successfully applied in different cloth manipulation scenarios, with significant gains in optimization speed compared to standard model predictive control strategies. The experiments further demonstrate that the closed-loop model used by quadratic dynamic matrix control can be beneficial to the tracking accuracy, leading to improvements over the standard predictive control strategy. Moreover, a preliminary experiment on a real robot shows that quadratic dynamic matrix control can indeed be employed in real settings.
Input Distribution Aware Library of Approximate Adders Based on Memristor-Aided Logic

—Memristor-aided logic (MAGIC) is one of the most popular design styles for implementing Logic-in-Memory (LiM) using memristors. MAGIC-based LiM has been shown to be useful for high throughput applications, as the same design can be mapped to multiple rows of a crossbar. The computations can be performed simultaneously on all these rows on different inputs to achieve high throughput. In recent years, approximate circuits have been extensively explored to obtain benefits in power, performance, and area for traditional CMOS designs. While these approximate circuits produce erroneous outputs, several applications can produce an acceptable quality output even with these approximations. In this work, we propose approximate circuits for MAGIC-based LiM. We have used the Ripple Carry Adder (RCA) architecture and introduced functional approximation to generate the approximate RCAs. We obtained the mapping of these approximate RCAs on the memristor crossbar using the SIMPLER MAGIC tool. We generated the Pareto-optimal designs using Gate Count and Total Cycles as design metrics against Mean Square Error and Mean Absolute Error as error metrics. We generated separate Pareto-optimal designs for three different input data distributions namely uniform, exponential, and normal data distributions.
Factors Enhancing the Expatriate Intent to Stay in Pakistan: A Structural Equation Modeling Approach

Purpose: Expatriates are the key players in establishing and running the international business in the host country. Therefore, a burgeoning debate has been done regarding their effectiveness and their intent to stay in the host country. In this regard, most of the researchers have explored the organizational factors. However, there is scant research that explores the psychological capabilities of an individual as an expatriate to sense and act in accordance with the cultural and social environment of the host country. Therefore, the present study aims to assess the effect of cultural and social intelligence on expatriate’s intent to stay through job satisfaction. Design/Methodology/Approach: In order to meet the objectives of the research, 303 expatriates in Pakistan were selected as target respondents using simple random sampling technique. The collected data was then analyzed by adopting PLS-SEM approach using Smart PLS 3.0 software. Findings: The findings of the study revealed a significant association of cultural and social intelligence with job satisfaction. In addition, the relationship of job satisfaction and expatriates’ intent to stay was also established. The findings of the study also confirm the mediating role of job satisfaction between the relationship of cultural and social intelligence with expatriate intent to stay. Implications/Originality/Value: The significance of expatriates cannot be overlooked from the host country’s perspective. Therefore, this study is unique in its kind that explains the factors that are significant in enhancing expatriates’ intent to stay in Pakistan.
An AeroCom Initial Assessment - Optical Properties in Aerosol Component Modules of Global Models

The AeroCom exercise diagnoses multi-component aerosol modules in global modeling. In an initial assessment simulated global distributions for mass and mid-visible aerosol optical thickness (aot) were compared among 20 different modules. Model diversity was also explored in the context of previous comparisons. For the component combined aot general agreement has improved for the annual global mean. At 0.11 to 0.14, simulated aot values are at the lower end of global averages suggested by remote sensing from ground (AERONET ca. 0.135) and space (satellite composite ca. 0.15). More detailed comparisons, however, reveal that larger differences in regional distribution and significant differences in compositional mixture remain. Of particular concern are large model diversities for contributions by dust and carbonaceous aerosol, because they lead to significant uncertainty in aerosol absorption (aab). Since aot and aab, both, influence the aerosol impact on the radiative energy-balance, the aerosol (direct) forcing uncertainty in modeling is larger than differences in aot might suggest. New diagnostic approaches are proposed to trace model differences in terms of aerosol processing and transport: These include the prescription of common input (e.g. amount, size and injection of aerosol component emissions) and the use of observational capabilities from ground (e.g. measurements networks) or space (e.g. correlations between aerosol and clouds).
Predictors of Dizziness and Hearing Disorders in People with Long COVID

Background and Objectives: Individuals report persistent symptoms after becoming infected by SARS-CoV-2 (COVID-19) that last for >4 weeks (long-COVID syndrome). Dizziness and hearing loss have been reported among long-COVID symptoms. However, little is known about the potential predictors of dizziness and hearing loss in individuals with long COVID. This study aimed to explore the presence and correlates of dizziness and hearing loss in a sample of people with long-COVID syndrome. Materials and Methods: Individuals aged 18 years and older who were infected with COVID-19 at least 8 weeks prior to the start of the study were included if they were not diagnosed with dizziness or hearing loss before getting COVID-19. Demographics and COVID-19-related information were collected. Participants completed the Dizziness Handicap Inventory (DHI), Activities-Specific Balance Confidence (ABC) scale, Falls Efficacy Scale International (FES-I), Modified Fatigue Impact Scale (MFIS), and Medical Outcomes Study Short Form 12 (SF-12). Finally, hearing was assessed using pure-tone audiometry (PTA) in a subsample. Results: Two hundred and nine individuals (66% female) with a mean (SD) age of 27 (9) participated in the study. Perceived dizziness and hearing loss were reported in 26 and 15.3% of the sample, respectively. Logistic regression was conducted to identify potential predictors of dizziness and hearing loss separately. After controlling for age and severity of dizziness, female sex and high fatigue severity were associated with an increased likelihood of reporting dizziness (R2 = 31%). The severity of dizziness and neurological symptoms during the acute stage of COVID-19 were associated with an increased likelihood of reporting hearing loss (R2 = 10.4%) after controlling for age. Conclusions: Dizziness and hearing loss present in long COVID and can be disabling. Females with high levels of fatigue should be questioned about persistent dizziness. Hearing loss should be considered in individuals with neurological symptoms and severe dizziness as a consequence of long COVID.
Banking in a challenging environment: Business models, ethics and approaches towards risks

The current crisis with its on-going banking sector problems has brought to the fore various cases of financial fraud and banking scandals that have additionally undermined the already low confidence in the sector. This has raised concerns about structural flaws in the way banks operate and are being regulated and supervised. Restoring investor confidence may require new approaches to redesign the incentives, rules and regulations for the financial sector. This was the backdrop for the discussions at the October 2012 OECD Financial Roundtable that this article summarises. Topics covered the current outlook and risks for banks as well as banking business models, ethics and approaches towards risks. Participants pointed out that, while downsizing and adjusting their business models, banks had already made improvements in their risk management. At the same time, the now observed renationalisation of assets could worsen the situation particularly in the European periphery. This could be attenuated by a European Banking Union that would also help to break the detrimental link between banks and sovereigns. As banks are deleveraging, non-banks are substituting for part of the reduced bank lending, but to do so would need regulatory support – while the shadow banking sector more generally will come under closer regulatory and supervisory scrutiny. Consumer groups in particular regard financial consumer protection as important to help improve the social value of financial activities that had often been unproductive, if not destructive. Bank representatives opposed regulatory separation of bank business on the grounds that it is insufficient to address problems of risk taking and control. Finally, it was pointed out that regulatory reforms need to be targeted and harness market forces by balancing penalties and rewards. Governance of regulation should also be enhanced, and regulation should be proactive and be complemented by strong macro and micro-supervision. Co-ordinating reforms should ensure a level playing field, but a one-size-fits-all approach should be avoided.
GAP iNTERDISCIPLINARITIES – Volume - V Issue I

In the development of an economy fiscal policy plays a very important role. Impact of fiscal deficit on economic growth is one of the alarming issues not only for India but also for the other emerging economies. The role of fiscal policy and fiscal deficit in influencing economic growth has been a widely debated issue in economic literature. In macroeconomic literature as each major school of economic thought views impact of budget deficits on economic activity situation. There is clear a division of opinion on this issue. Some economists argue that budget deficit have a positive effect, some argue negative effect and neutral effect on the macroeconomic activity. To understand this, the paper examines theoretical perspective of different economist view like alternative measures of government deficit and alternative school of thought (Classical, Neo-classical, and Keynesian, Ricardian equivalence) to show various impact of fiscal deficit on economic growth
ANALYSIS AND LOW ORDER MODELING OF THE ACOUSTIC DAMPING FOR HIGH-FREQUENCY COMBUSTION INSTABILITIES PREDICTION IN LIQUID ROCKET ENGINES

: The phenomena liable for acoustic damping in thermo-acoustic instabilities in liquid rocket engines are investigated. Modelings to account for the nozzle impedance, in compact hypothesis, and for the visco-thermal losses at walls are derived according to the Galerkin framework, where pressure variations are decomposed over the acoustic eigen-modes. Models are implemented in a low order tool and compared successfully to analytic and numerical predictions. The turbulent/acoustic interaction, responsible for acoustic absorption at the jets, is reviewed, and an in-progress strategy is presented.