A Dynamic Game Model of Collective Choice in Multi-Agent Systems

Inspired by successful biological collective decision mechanisms such as honey bees searching for a new colony or the collective navigation of fish schools, we consider a mean field games (MFG)-like scenario where a large number of agents have to make a choice among a set of different potential target destinations. Each individual both influences and is influenced by the group's decision, as well as the mean trajectory of all the agents. The model can be interpreted as a stylized version of opinion crystallization in an election for example. The agents' biases are dictated first by their initial spatial position and, in a subsequent generalization of the model, by a combination of initial position and a priori individual preference. The agents have linear dynamics and are coupled through a modified form of quadratic cost. Fixed point based finite population equilibrium conditions are identified and associated existence conditions are established. In general multiple equilibria may exist and the agents need to know all initial conditions to compute them precisely. However, as the number of agents increases sufficiently, we show that 1) the computed fixed point equilibria qualify as epsilon Nash equilibria, 2) agents no longer require all initial conditions to compute the equilibria but rather can do so based on a representative probability distribution of these conditions now viewed as random variables. Numerical results are reported

Effect of Sociodemographic Factors and Antipsychotics on Quality of Life in Palestinian Patients with Schizophrenia

Quality of life has a vital role in developing treatments that can help individuals with schizophrenia to lead more fulfilling and satisfying lives. To date, there are limited studies regarding the quality of life (QoL) in patients with schizophrenia in Palestine. To evaluate the impact of sociodemographic factors and antipsychotics on quality of life in Palestinian patients with schizophrenia, we used the SF-36 Questionnaire. Method: Eighty patients with schizophrenia were interviewed in both HEBRON Community Mental Health Center and Dr. Kamal Mental health hospital in Bethlehem. Data was gathered between the end of December, 2017 and the beginning of February, 2018. Data was collected by the administration of SF-36 Questionnaire during a personal interview with eighty patients. Medical files were used to obtain medication. Statistical analysis was performed using the statistical package for social sciences (SPSS), and data was analyzed by using parametric tests. A number of significant correlations were identified between QoL and the independent factors. There was no impact of gender on QoL. Similarly, the results show no significance difference in the QoL with respect to marital status. Our findings show that being employed was associated with better QoL in the physical function domain (PF) and the role physical domain (RF). Results also show a positive correlation between the two educational levels diploma degree and vocational degree and QoL in the physical function domain (PF) and the role emotional domain (RE). The results show no correlation between bachelor degree and QoL. Regarding place of living, schizophrenia patients who live in the city have better QoL in the bodily pain domain (BP) and in the social functioning domain (SF). In the current study, income higher than 4000 NIS/month was associated with high quality of life score. The study found that 82.5% of patients with schizophrenia live with a very low income, which is below 3000 NIS/month. Finally, our findings reveal that there is a significant correlation between QoL and patients who did not stay in a mental health hospital. Antipsychotic drugs are the cornerstone for the treatment of schizophrenia. These medications have always been of great interest in studying quality of life in schizophrenia. In our study, majority of the patients were receiving single typical antipsychotic medication (45%). Approximately 35.5% were receiving combinational antipsychotic medications (typical and atypical), and 20% were receiving atypical antipsychotic medications. The results show a positive significant difference between QoL and patients receiving atypical medications in the SF domain. The relationship between subjective treatment satisfaction and QoL in patients with schizophrenia was studied. Our results show that 82.5% of the patients were satisfied with their medication. Moreover, it was found that there is a positive correlation between satisfaction to medication and QoL in mental health domain (MH). The study indicates that 63.8% of schizophrenic patients are smokers. The results show that there is a positive significant difference between QoL and non-smoker patients in the RE and SF domain. Furthermore, results indicate a positive correlation between QoL and family support in all domains of the questionnaire. Unexpectedly, only 18% of our sample have medical conditions other than schizophrenia. In addition, the study found a negative correlation between age and QoL in the PF domain, which means poorer quality of life with increased age. Finally, we found a negative correlation between duration of illness and QoL (As duration of illness increases, QoL decreases). This study characterized the QoL of schizophrenic Palestinian patients and determined the factors that may impact it. The study shows that being employed was associated with better QoL. In addition, living in an area where access to specialist care is available increases QoL for schizophrenic patients. While the majority of the patients receive typical antipsychotic medication (45%), approximately 20% receive atypical antipsychotic medications. Relative to a study conducted in 2004 in which only 2% of patients received atypical medication, the increased use of atypical medication is a positive development. Consistent with literature reports, the results show a positive relationship between QoL and patients receiving atypical medications in the SF domain. This may be attributed to the known effect of atypical medications on negative symptoms. A positive correlation between satisfaction to medication and QoL in the MH domain was identified, in addition to a negative correlation with age (Poorer quality of life with increased age). Finally, we found a negative correlation between duration of illness and QoL (As duration of illness increases, QoL decreases)

Genome-wide analysis of DNA methylation topology to understand cell fate

DNA methylation is an epignetic modification associated with gene regulation. It has extensively been studied in the context of small regulatory regions. Yet, not so much is known about large domains characterized by fuzzy methylation patterns, termed Partially Methylated Domains (PMDs). The present thesis comprises PMD analyses in various contexts and provides several new aspects to study DNA methylation. First, a comprehensive analysis of PMDs across a large cohort of WGBS samples was performed, to identify structural and functional features associated with PMDs. A newly developed approach, ChromH3M, was proposed for the analysis and integration of a large spectrum of WGBS data sets. Second, PMDs were found to be indicators of the cellular proliferation history and segmented loss of DNA methylation in PMDs supports the sequential linear differentiation model of memory T-cells. Third, assessment of genome-wide methylation changes in PMDs of Multiple Sclerosis-discordant monozygotic co-twins did not show significant differences, but local changes (DMRs) were identified. Taken together, the outcomes of the presented studies shed light on a so far neglected aspect of DNA methylation, that is PMDs, in different contexts; lineage specialization, differentiation, replication, disease, chromatin organization and gene expression.Die DNA-Methylierung ist eine epigenetische Modi1kation, die funktionell mit der Genregulation verbunden ist. Sie wurde bereits ausführlich im Kontext kleiner regulatorischer Regionen untersucht. Es ist jedoch noch nicht sehr viel bekannt über große Domänen, welche erstmals in WGBS-Daten beschrieben wurden. Sie werden als partiell methylierte Regionen (PMDs) bezeichnet und sind durch das Vorhandensein variabler Methylierungsmuster charakterisiert. Die vorliegende Arbeit umfasst PMD-Analysen in unterschiedlichen Kontexten und liefert verschiedene neue Aspekte zur Untersuchung der DNA-Methylierung. Zuerst wurde eine umfassende Analyse von PMDs in einer großen Kohorte von WGBS-Proben durchgeführt, um strukturelle und funktionelle Merkmale zu identi 1zieren, die mit PMDs assoziert sind. Ein neu entwickelter Ansatz, ChromH3M, wurde für die Analyse und Integration einer großen Kohorte vonWGBS Datensätzen angewandt. Zweitens wurde festgestellt, dass PMDs Indikatoren für die Zellproliferationshistorie sind, und der zu beobachtende graduelle Verlust der globalen DNAMethylierung bei der Differenzierung von T-Gedächtniszellen unterstützt die Hypothese der sequenziellen linearen Differenzierung. Drittens zeigte die Bewertung der genomweiten Methylierungsänderungen in PMDs von Multiple Sklerose-diskordanten monozygoten Zwillingen keine signi1kanten Unterschiede, jedoch wurden lokale Änderungen (DMRs) identi1ziert. Insgesamt geben die Ergebnisse der vorgestellten Studien Aufschluss über einen bislang eher vernachlässigten Aspekt der DNA-Methylierung, d.h. PMDs, in verschiedenen Zusammenhängen: der Festlegung der Zell-entwicklungsbahnen, der Zelldifferenzierung, der Replikation, die Krankheit, der Organisation des Chromatins, sowie der Regulation der Genexpression

Impact and controversy: effectiveness of shockvertising in for-profit and non-profit organizations

Treball Final de Grau en Publicitat i Relacions Públiques. Codi: PU0932. Curs acadèmic: 2022/2023En el actual panorama publicitario, caracterizado por la sobreexposición a mensajes comerciales, resulta cada vez más desafiante captar la atención de los consumidores. Frente a esta realidad, las organizaciones se ven obligadas a buscar estrategias creativas que les permitan trascender en la mente del público. Una de estas estrategias es el shockvertising, que busca generar sorpresa, incomodidad o incluso controversia con el fin de crear impacto en el público. El objetivo principal de este trabajo de fin de grado es analizar la efectividad del shockvertising tanto para empresas capitalistas como para organizaciones sin ánimo de lucro. Para lograr este objetivo, se llevará a cabo un análisis crítico de cuatro spots publicitarios que aplican el shockvertising de manera distinta. Estos anuncios serán sometidos a la mirada de una muestra representativa de la población, con el fin de recopilar datos relevantes acerca de las reacciones y percepciones generadas. El análisis crítico de los spots publicitarios permitirá evaluar cómo reacciona la población ante el shockvertising, identificando las emociones y percepciones que suscita en los espectadores. Además, se establecerán comparativas entre los resultados obtenidos entre las empresas capitalistas y las empresas sin ánimo de lucro, con el fin de identificar posibles diferencias significativas en la efectividad de esta estrategia en ambos ámbitos. La combinación de los datos recogidos y el análisis exhaustivo llevará a formular conclusiones fundamentadas en la aplicabilidad en empresas campitalistas y sin ánimo de lucro, y la efectividad del shockvertising, en la que es esencial identificar el mensaje central que se quiere transmitir, y su coherencia con la misión y objetivos de la organización.In today’s advertising landscape, characterized by an overwhelming exposure to commercial messages, getting costumers attention has become increasingly challenging. Facing this reality, organizations are compelled to seek creative strategies than can trascend the audience mindset. One such strategy is shockverting, which aims to generate surprise, discomfort, or even controversy to create an impact on the audience. The main objective of this final degree project is to analyze the effectiveness of shockvertising for capitalist companies and non-profit organizations. To achive this goal, a critical analysis will be conducted on four distinct advertising spots that employ shockvertising in different ways. These advertisements will be shown to a representative sample of the population to gather relevant data on their reactions and perceptions. The critical analysis of the spots will evaluate how the audience responds to shockvertising, identifying the emotions and perceptions it evokes in viewers. Furthermore, a comparison will be made between the results obtained from capitalist companies and non-profit organizations to identify potential significant differences in the effectiveness of this strategy in both domains. By combining the collected data with an exhaustive analysis, well-founded conclusions, as essential as it is to identify the central message, and its coherence with the mission and objectives of the organization, will be formulated regarding the applicability of shockvertising in capitalist and non-profit organizations, as well as the effectiveness of shockvertising

Optimal land use allocation for the Heathrow opportunity area using multi-objective linear programming

The London Plan, the Greater London Authority's spatial development strategy for London, has defined Heathrow as an Opportunity Area - an area with the capacity to support additional homes and jobs - since 2004, but progress on developing the area has been minimal. Uncertainty around the expansion of Heathrow Airport appears to have adversely affected progress. Nevertheless, the most recent London Plan stipulates that the Heathrow Opportunity Area should accommodate 13,000 new homes and 11,000 new jobs. In this article, multi-objective linear programming is used to investigate whether these figures are achievable given constraints on land availability and land use mix. How land uses might best be assigned to maximise home, job and gross value added (GVA) creation within the Heathrow Opportunity Area is also explored. The main contributions are to provide independent scrutiny of London's development strategy and to present a mathematical framework for land use allocation planning decisions in urban areas. Findings show that given 700 ha of available land, as indicated in the London Plan, home and job creation figures can be met. However, there is insufficient brownfield land to meet these targets, and development on Green Belt land would very likely be necessary. Strong land use allocations for the area are found to more heavily feature financial and professional services, other office-based businesses, and shops. Rather than presenting a single land use "solution", results are presented using a wide range of visualisations to illustrate key trade-offs between different goals, with the secondary aim of promoting multi-objective linear programming to planners as a valuable tool to support spatial decisions and policy making

AraSpot: Arabic Spoken Command Spotting

Spoken keyword spotting (KWS) is the task of identifying a keyword in an audio stream and is widely used in smart devices at the edge in order to activate voice assistants and perform hands-free tasks. The task is daunting as there is a need, on the one hand, to achieve high accuracy while at the same time ensuring that such systems continue to run efficiently on low power and possibly limited computational capabilities devices. This work presents AraSpot for Arabic keyword spotting trained on 40 Arabic keywords, using different online data augmentation, and introducing ConformerGRU model architecture. Finally, we further improve the performance of the model by training a text-to-speech model for synthetic data generation. AraSpot achieved a State-of-the-Art SOTA 99.59% result outperforming previous approaches.Comment: A preprin

Proof of Deep Learning: Approaches, Challenges, and Future Directions

The rise of computational power has led to unprecedented performance gains for deep learning models. As more data becomes available and model architectures become more complex, the need for more computational power increases. On the other hand, since the introduction of Bitcoin as the first cryptocurrency and the establishment of the concept of blockchain as a distributed ledger, many variants and approaches have been proposed. However, many of them have one thing in common, which is the Proof of Work (PoW) consensus mechanism. PoW is mainly used to support the process of new block generation. While PoW has proven its robustness, its main drawback is that it requires a significant amount of processing power to maintain the security and integrity of the blockchain. This is due to applying brute force to solve a hashing puzzle. To utilize the computational power available in useful and meaningful work while keeping the blockchain secure, many techniques have been proposed, one of which is known as Proof of Deep Learning (PoDL). PoDL is a consensus mechanism that uses the process of training a deep learning model as proof of work to add new blocks to the blockchain. In this paper, we survey the various approaches for PoDL. We discuss the different types of PoDL algorithms, their advantages and disadvantages, and their potential applications. We also discuss the challenges of implementing PoDL and future research directions