IBM Watson

This paper presents a deeply integrated framework for maximizing productivity in Artificial Intelligence systems while preserving ethical safeguards and systemic integrity. Combining the disciplines of data science, machine learning, neuro-adaptive feedback, database architecture, and bias-awareness, we outline a post-2025 blueprint for scalable, emotionally intelligent AI. The document explores practical tools, philosophical underpinnings, and predictions for future versions of generative models (GPT-6 to GPT-15), culminating in a roadmap for a meta-operating system for consciousness-aware intelligence.

he Turing test is one of the philosophical foundations of Artificial Intelligence. In the sixty years since Alan Turing's "Computing Machinery and Intelligence" appeared in Mind, there have been two widely accepted interpretations of the test-the canonical behaviorist and the rival inductive (or epistemic) accounts. These accounts are based on Turing's 1950 Mind paper, and few commentators know that Turing described two other versions of his imitation game. These versions are scarcely mentioned in the voluminous literature on the Turing test but are (I shall argue) essential to understanding the test. Turing described the first version in 1948, the year he moved to Manchester to run the Computing Machine Laboratory at the university. 1 Earlier, in June 1948, the world's first electronic stored-program digital computer, the Manchester "Baby", ran its first program in the Laboratory. During 1948-49, the Baby was expanded to become a much more substantial machine, and in May 1949 the Electronic Delay Storage Automatic Calculator (EDSAC) became the second electronic stored-program computer to function, at the Mathematical Laboratory of the University of Cambridge. Further developments at Manchester led to the first commercially available electronic digital computer, in February 1951. In this way, in the late 1940s and early 1950s, the abstract question whether machine intelligence is possible came to be focused on a particular form of machine. Could machinery like the Baby and the EDSAC, if given additional high-speed memory and enhanced processing speed, be said to think? To investigate this question, Turing required a "criterion for 'thinking'" 2 -the "imitation game" was to provide this. In a 1948 report on machine learning entitled "Intelligent Machinery", he * I am indebted to Jack Copeland for comments on an earlier draft of this paper. 1 On the Manchester computers, see further B.

This article uses the example of drugs that might cure Alzheimer’s
dementia in order to illustrate that consequences of undesirable drugdrug interactions may limit the treatment that may be safely used for any
medical condition. As many as 18 elements may participate in the cause of
AD, and their suppression may require choosing from 24 individual drugs.
That number of drugs may be greatly reduced by excluding those that cause
undesirable consequences from drug-drug interactions between the two drugs
in each pair. Also, there is a limit to the number of drugs that is tolerable,
especially in the elderly who have other conditions requiring drugs. In fact,
meaningful simplification of therapy intended to cure a problem such as
AD, that has several contributing components, can often be achieved only if
there are proxies for those components. In that regard, the present article is
intended to make the task easier by providing just two proxies, i.e., dopamine
(DA), and serotonin (5-HT), for the 24 drugs that might potentially cure AD.
Levels of DA and 5-HT are decreased in AD and each of them has critical
importance for brain function, so raising their levels stands a good chance
to cure AD. After excluding from the 24 drugs, those pairs of drugs that
produce undesirable effects from consequences of drug-drug interactions,
only nine drugs remain that may be safely used.

The integration of Artificial Intelligence (AI) and Blockchain technology offers transformative potential for the healthcare industry. Blockchain provides a secure, immutable, and transparent infrastructure for managing healthcare data, while AI enhances decision-making, predictive analytics, and personalized treatment. This research paper explores the synergies between AI and Blockchain in healthcare systems, focusing on how these technologies can improve patient care, streamline operations, enhance data security, and address key challenges like interoperability and trust. Through case studies and a detailed examination of their applications, this paper highlights the potential benefits and challenges of implementing AI in Blockchain-enabled healthcare systems, with a vision toward a more secure, efficient, and patient-centric healthcare ecosystem.

A vast variety of artificial intelligence techniques have been deployed to specific healthcare problems during the last thirty years with varying levels of success while there is a shortage of systematic matching of AI capabilities with the breadth of application opportunities. In this paper, we describe the process of identifying opportunities for deploying artificial intelligence to healthcare and social services on regional and national levels in Finland. The project involved a large number of stakeholders from a variety of backgrounds ranging from governmental agencies to entrepreneurs. The process described includes idea generation of an application or solution and its elaboration in workshops using a design thinking method. The resulting idea pool was filtered down to 34 best use case descriptions, which went through an architectural design process identifying AI capabilities needed in the components of these designs reported in this paper. The potential ones of the use cases were selected for prototype development. The subsequent steps in the process include feasibility prototypes and evaluation of the economic and business value of the solutions and applications.

A vast variety of artificial intelligence techniques have been deployed to specific healthcare problems during the last thirty years with varying levels of success while there is a shortage of systematic matching of AI capabilities with the breadth of application opportunities. In this paper, we describe the process of identifying opportunities for deploying artificial intelligence to healthcare and social services on regional and national levels in Finland. The project involved a large number of stakeholders from a variety of backgrounds ranging from governmental agencies to entrepreneurs. The process described includes idea generation of an application or solution and its elaboration in workshops using a design thinking method. The resulting idea pool was filtered down to 34 best use case descriptions, which went through an architectural design process identifying AI capabilities needed in the components of these designs reported in this paper. The potential ones of the use cases were selected for prototype development. The subsequent steps in the process include feasibility prototypes and evaluation of the economic and business value of the solutions and applications.

A vast variety of artificial intelligence techniques have been deployed to specific healthcare problems during the last thirty years with varying levels of success while there is a shortage of systematic matching of AI capabilities with the breadth of application opportunities. In this paper, we describe the process of identifying opportunities for deploying artificial intelligence to healthcare and social services on regional and national levels in Finland. The project involved a large number of stakeholders from a variety of backgrounds ranging from governmental agencies to entrepreneurs. The process described includes idea generation of an application or solution and its elaboration in workshops using a design thinking method. The resulting idea pool was filtered down to 34 best use case descriptions, which went through an architectural design process identifying AI capabilities needed in the components of these designs reported in this paper. The potential ones of the use cases were selected for prototype development. The subsequent steps in the process include feasibility prototypes and evaluation of the economic and business value of the solutions and applications.

The pace of deploying artificial intelligence (AI) techniques to healthcare has been speeding up. Many of the initiatives have been technology driven aiming at finding problems matching the new technology while systematic, demand driven search for solutions has been limited. Here we describe the process of identifying opportunities for deploying artificial intelligence to healthcare and social services on regional and national levels in Finland. The process includes idea generation and elaboration using a design thinking method complemented with architectural design for identifying required AI capabilities for the 34 best use cases. In this paper, we focus on the development of use case "Mobile Solution for Home Care Coordination and Communication" to observe the evolving balance of technology push and demand pull faced in the process.

Bu çalışmada, onkoloji alanında yapay zekâ yöntemleri üzerine yapılan güncel 23 makale çalışması irdelenmiştir ve çalışmalarda kullanılan yapay zekâ yöntemleri ve doğruluk payları literatür özet tablosunda yer verilerek yapılacak diğer çalışmalara teorik bir zemin hazırlanması amaçlanmıştır. Yapay zekâ, son on yılda kanser de dâhil olmak üzere çeşitli tıbbi sorunların çözümüne önemli ölçüde katkıda bulunmuştur. Yapay zekâ kanser araştırmalarının çeşitli alanlarında giderek daha fazla uygulanmaktadır. Günümüzde yapay zekâ metotları hekimlere karar verme, yöneticilere daha etkili hizmet sunmak ve maliyetleri en aza indirme, sağlık çalışanlarının iş yükünü azaltma ve hasta açısından doğruluğu yüksek hata oranı en az olan tedaviyi alma noktasında önemli ayrıcalıklar kazandırmaktadır. Bu derleme, iki kategoride değerlendirilebilir. Birincisi onkoloji alanında sık görülen hastalıklar ve günümüzde yapay zekânın onkoloji alanında kullanımı örneklerle desteklenmiştir. İkinci kategoride ise literatür özet tablosu içerisinde onkoloji alanında yapılan güncel 23 çalışma; yapay zekâ yöntemleri açısından kategorilere ayrılmış ve doğruluk oranları sunulmuştur. Hızla gelişen yapay zekâ teknolojisinin yakın gelecekte kanser alanında büyük bir etkiye sahip olmaya devam edeceği düşünülmektedir. Sonuç olarak, hekimlerin ve araştırmacıların sağlık hizmetlerindeki dijitalleşen yeniçağa ayak uydurmasının multidisipliner çalışma ve eğitim müfredatlarına yapay zekâ eğitim kurslarını dâhil etmeleri, yapay zekâ tabanlı klinik karar destek sistemlerinin kullanımının yaygınlaşması ile kişiselleştirilmiş tıp, tanı ve tedavi aşamasında zaman kazanılması, hata oranının azaltılması, hasta ve çalışan memnuniyet ile hem maliyet etkin hem de kaliteli hizmet sunumu açısından önemli bir avantaj sağlayacağı düşünülmektedir.

Artificial intelligence has contributed significantly to solving various medical problems, including cancer, over the past decade. Artificial intelligence is being applied more and more in various fields of cancer research. Today, artificial intelligence methods provide physicians with important privileges in making decisions, providing more effective service to managers and minimizing costs, reducing the workload of healthcare professionals, and receiving the treatment with the highest accuracy rate for the patient and the least error rate. This review can be evaluated in two categories. First of all, common diseases in the field of oncology and the use of artificial intelligence in the field of oncology are supported with examples. In the second category, 23 recent studies in the field of oncology in the literature summary table; artificial intelligence methods are divided into categories and accuracy rates are presented. It is thought that the rapidly developing artificial intell...

Mainframe, büyük ölçekli veri işleme, depolama ve yönetim ihtiyaçlarını karşılamak üzere tasarlanmış, yüksek performanslı bilgisayarlardır. Genellikle finans,  sağlık, yüksek teknoloji gerektiren sahalarda, havacılık ve kamu sektörü gibi alanlarda kritik uygulamaları desteklemek için kullanılır. Yüksek işlem gücü, güvenilirlik, güvenlik ve ölçeklenebilirlik sunarak, çok sayıda kullanıcıya ve uygulamaya eşzamanlı olarak hizmet edebilirler. Mainframe’ler, özellikle büyük veri analizleri ve karmaşık hesaplamalar için idealdir.

This paper describes the development of chatbots that can help learners make the most appropriate use of a large body of content. The purpose of a COntent-based Learning Assistant, COLA, is to suggest optimal educational paths, along with a persuasive and empathic coaching. COLAs are supported by a novel technology, iCHAT, based on the cognitive engine Watson (by IBM).

The adoption of artificial intelligence with multi-cloud is one useful area that businesses and organizations should explore mainly due to its scalability, flexibility, and efficiency. As a result, this integration must come with several pulls that have to be dealt with to realize proper implementation. This paper seeks to identify the major issues of implementing AI and coming up with the best solutions in multi-cloud infrastructures. Firstly, compatibility problems appear as a fundamental issue in the process of implementing AI across more than one cloud. Every cloud provider uses different APIs, formats for data, and possibilities to configure the infrastructure that hinders data and services integration. To counter this, there is a need to have the compliance that comes in terms of standard development through the use of data formats, APIs, and interoperability frameworks. Furthermore, features such as Docker and Kubernetes make the work with ports lighter and let the AI components smoothly interconnect regardless of the used cloud environment. Secondly, data management as well as the governance of big data serve up significant challenges for multi-cloud AI implementation. Legal requirements concerning data privacy, global compliance standards, as well as data sovereignty concerns call for strong governance of cloud data to ensure they are accurate, secure, as well as compliant in the required cloud settings. These risks must be addressed, nonetheless, to build trust in the multi-cloud AI utilization; in this regard, robust data management, encompassing data encryption, access privileges, as well as data auditing, can be implemented in organizational settings. In addition, the optimization of performance is another significant issue to consider as AI computational tasks may be executed across different cloud environments resulting in increased throughput time and network congestion and contention. Through auto-scaling and workload scheduling algorithms used in orchestration, resources can be effectively allocated and loaded in the heterogeneous cloud infrastructures in the most efficient and optimum way thus reducing operational costs. The other is achieving robustness and dependability of multi-cloud AI applications. It is an immutable fact that one can always imagine a situation when clouds, networks, or hardware will fail; therefore, specific measures should be taken to ensure the availability and reliability of the system. The TCP/IP model also classes the means used for implementing redundant mechanisms, data replication strategies and disaster recovery protocols in different geographically situated cloud regions that improve the dependable computing system's resources.

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Reconstruction conjecture asks whether it is possible to reconstruct a unique (up to isomorphism) graph from set of its one vertex deleted subgraphs. We show here the validity of reconstruction conjecture for every connected graph which is uniquely reconstructible from the set of all its spanning trees. We make use of a well known result, namely, the reconstruction of a tree from the deck of its pendant point deleted subtrees.

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RESUMO O presente artigo terá como objetivo estudar os Sistemas Especialistas sob a perspectiva das novas tecnologias de Inteligência Artificial e Big Data e será organizado de maneira a, em um primeiro momento, apresentar os aspectos conceituais relativos à Inteligência Artificial e a Inteligência Artificial na Medicina (IAM), bem como apresentar os Sistemas Especialistas e relacionar tais sistemas com as novas tecnologias da Inteligência Artificial e Big Data. A segunda parte desse estudo irá propor algumas reflexões e problemáticas referentes aos Sistemas Especialistas sob a perspectiva do Direito, com maior foco em questões de Propriedade Intelectual, Responsabilidade, Privacidade e Ética. A terceira e última parte do estudo compreenderá as considerações finais sobre o tema e sugestões para estudos futuros.

In the era of digitalization and rapidly changing technology, artificial intelligence is one the fastest evolving technology across the globe. Artificial intelligence deals with the study and development of intelligence of machines and software.

In the era of digitalization and rapidly changing technology, artificial intelligence is one the fastest evolving technology across the globe. Artificial intelligence deals with the study and development of intelligence of machines and software. Further this technology has vast applications in various sectors like education, healthcare and manufacturing. Artificial intelligence has potential to lift various industries by reducing the human effort and increasing productivity. In education sector application of artificial intelligence has been the subject of research for 30 years. Artificial intelligence in education sector is applied in every field where learning occurs, in traditional educational institutes or in workplaces in order to support learning and formal education. Artificial intelligence helps to promote the development of learning environments and other artificial intelligence tools that effective, engaging and personalized. Recent growth in numbers of universities and post graduate programs globally will provide boost in the growth of the market. Additionally, government initiatives to improve the quality of education and increased expenditures to modernize the education sector by deployment of various education programs and education software such as ERP (enterprise resource planning), LMS (learning management system) will help North America to dominate the market in coming years. Another trend that can be seen in educational sector is artificial intelligence based educational games. Educational games help teachers to deliver their teachings in an interactive and engaging manner. Such methods create curiosity within the learners and helps in better development of mind. These games are embedded with adaptive learning features so that students can be guided in real time and timely suggestions for better learning experience. Moreover, rising number of startups and huge investments in AI by large market players like Intel, Microsoft, Google naming few, will help the artificial market to grow significantly in nearby future.

The distinguishing number (index) D(G) (D ′ (G)) of a graph G is the least integer d such that G has an vertex labeling (edge labeling) with d labels that is preserved only by a trivial automorphism. A graphoidal cover of G is a collection ψ of (not necessarily open) paths in G such that every path in ψ has at least two vertices, every vertex of G is an internal vertex of at most one path in ψ and every edge of G is in exactly one path in ψ. Let Ω(G, ψ) denote the intersection graph of ψ. A graph H is called a graphoidal graph, if there exists a graph G and a graphoidal cover ψ of G such that H ∼ = Ω(G, ψ). In this paper, we study the distinguishing number and the distinguishing index of the line graph and the graphoidal graph of a simple connected graph G.

In this article we describe the narratives of two characters who in the last decade published videos about their most intimate secrets, usually love affairs and everyday life that have gained worldwide repercussion, through the space offered by Youtube. We propose to analyze the channels Ary Régis Lima and Raymundinho Furacão. For this, we selected four videos produced for entertainment, but in which the characters portray the violence experienced by them, through their sexual orientation. Although the narratives are full of satires, humor and exhibitionism, Baia Bahia and Raymundinho Furação militate while presenting moments of danger and distress.

The distinguishing number (index) D(G) (D ′ (G)) of a graph G is the least integer d such that G has an vertex labeling (edge labeling) with d labels that is preserved only by a trivial automorphism. A graphoidal cover of G is a collection ψ of (not necessarily open) paths in G such that every path in ψ has at least two vertices, every vertex of G is an internal vertex of at most one path in ψ and every edge of G is in exactly one path in ψ. Let Ω(G, ψ) denote the intersection graph of ψ. A graph H is called a graphoidal graph, if there exists a graph G and a graphoidal cover ψ of G such that H ∼ = Ω(G, ψ). In this paper, we study the distinguishing number and the distinguishing index of the line graph and the graphoidal graph of a simple connected graph G.

Inserted in the field of communication in strong dialogue with socio-anthropology, from the methodological approach of ethnography to the internet, this article identifies the existence of groups on digital social media that create spaces to share content related to suicide. The main results point to three issues: first, suicide is an act of communication on the internet. Second, digital social media enables other ways of creating social bonds. These bonds, perceived as intermediate bonds, can collaborate to prevent and combat selfinflicted death. Third, the absence of institutional organizations that mediate content sharing in groups that, especially, are composed of members considered vulnerable and at risk. Mostly, these groups are occupied by young people.

Los tres trabajos que siguen tratan el ejercicio de la historia de la medicina, pero desde tres diferentes posiciones. La idea es sumamente atractiva, porque los escritos reflejan las ideas, experiencias, sentimientos e incluso expectativas de tres estudiosos con tres formaciones diferentes y que han dedicado una parte importante de su vida profesional al ejercicio de la historia de la medicina. Surgió de conversaciones entre los tres, pláticas muchas veces en el ámbito de lo social pero que reflejaban las inquietudes académicas. No a todos los médicos les es posible (o permitido) ser oftalmólogos o patólogos, pero curiosamente, parece que todos pueden ser historiadores de la me

Traditional Power Grid is transformed to Smart Grid by utilizing the technological advancements of Information and Communication Technology. In Smart Grid data is flowing between different components of the system. Advanced and online analytic on this massive data is required to trigger instantaneous action for grid operation and management. Traditional Big Data handling techniques store and analyze high volume data with variety, but failed to handle high velocity data. Stream computing can analyze high velocity data with variety which is essentially required in online data analytics. This paper compared different Big Data analysis techniques and reveals the importance of stream computing and its opportunities in Smart Grid data analytics.

Background: Breast cancer has the highest incidence and is the leading cause of cancer-related mortality among women worldwide. IBM Watson® for Oncology (WfO), an artificial intelligence-based clinical decision-support system, provides therapeutic options for consideration to cancer-treating physicians. We conducted a targeted review of studies evaluating concordance of therapeutic options offered by the system with treatment decisions by practicing clinicians in breast cancer. Methods: PubMed, EMBASE, Cochrane, trial registers, conference abstracts, and an internal publication database were searched to identify studies evaluating the concordance of system-generated therapeutic options with treatment decisions by individual clinicians and multidisciplinary tumor boards for breast cancer patients reported in peer-reviewed abstracts or papers published in English between 01/01/2015 and 11/15/2019.Results: Ten breast cancer concordance studies (4703 patients) that met the inclusion cri...

O impacto da obra de J. B. Watson tem sido explorado na historiografia da psicologia. Neste âmbito, destacam-se estudos que utilizam como método a análise bibliométrica. Tais pesquisas, no entanto, não utilizam parâmetros comparativos que possam indicar de forma mais precisa o grau de impacto daquela obra. O presente estudo busca preencher tal lacuna por meio de uma análise bibliométrica comparativa das referências às obras de Watson e outros três relevantes psicólogos do período: Edward B. Titchener, Edward L. Thorndike e William James. A pesquisa foi realizada em cinco importantes periódicos norte-americanos da área, entre os anos 1903 e 1923 – uma década antes e uma década após a publicação do Manifesto Behaviorista. Os resultados permitem concluir que, embora não possa ser tomada propriamente como um marco revolucionário, a obra de Watson teve, na década posterior à publicação do Manifesto Behaviorista (1914-1923), um impacto próximo ao de Titchener e maior do que o de Thorndike...

Labelled "ground truth" datasets are routinely used to evaluate and audit AI algorithms applied in high-stakes settings. However, there do not exist widely accepted benchmarks for the quality of labels in these datasets. We provide empirical evidence that quality of labels can significantly distort the results of algorithmic audits in real-world settings. Using data annotators typically hired by AI firms in India, we show that fidelity of the ground truth data can lead to spurious differences in performance of ASRs between urban and rural populations. After a rigorous, albeit expensive, label cleaning process, these disparities between groups disappear. Our findings highlight how trade-offs between label quality and data annotation costs can complicate algorithmic audits in practice. They also emphasize the need for development of consensus-driven, widely accepted benchmarks for label quality.

Bireylerin doğumlarından önce başlayan ve hayatları boyunca devam eden temel ihtiyaçlarının başında sağlık hizmetleri gelmektedir. Teknolojinin insanlara sunduğu gelişmeler sonucunda medikal cihazlar sadece sağlık kurumları ve personeli tarafından değil, aynı zamanda bireylerin evlerinde kişisel olarak da kullanılmaya başlanmıştır. Hem bireylerin evde kullandıkları basit medikal cihazlar hem de sağlık kurumlarında verilen hizmetler nedeni ile durmadan büyüyen sağlık verisi üretilmektedir. Son yıllarda nesnelerin interneti (IoT) kavramı akıllı sistemler için yeni bir eğilim olmuştur. Bu çalışmada, kişilere özgü sağlık verileri, ölçümleri yapıldığı medikal cihazlardan akıllı telefonlara ve cihazlara, bu cihazlardan da buluta aktarımının gerçekleştirilmesi için geliştirilen sağlık alanına özel bir nesnelerin interneti platformu anlatılmaktadır. Böylece, kişiye özel sağlık verileri hasta mahremiyeti sağlanarak kayıt altına alınacak, sorgulanabilecek ve belirlenen kurallara göre verilerdeki sapmalar doğrultusunda kişiye ve/veya sorumlu kişiye ve kurumlara uyarı hizmetlerinin verilmesi sağlanacaktır. Ayrıca, geliştirilmiş olan platformda ilk olarak tansiyon ve nabız bilgiler işlenmiş ve bu bilgileri kullanarak kişisel sağlık hizmetleri ve alarmlar oluşturulmuştur.

Author profiling consists of predicting some author's characteristics (e.g. age, gender, personality) from her writing. After addressing at PAN@CLEF mainly age and gender identification, and also personality recognition in Twitter 1 , in this PAN@FIRE track on Personality Recognition from SOurce COde (PR-SOCO) we have addressed the problem of predicting author's personality traits from her source code. In this paper, we analyse 48 runs sent by 11 participant teams. Given a set of source codes written in Java by students who answered also a personality test, participants had to predict personality traits, based on the big five model. Results have been evaluated with two complementary measures (RMSE and Pearson product-moment correlation) that have permitted to identify whether systems with low error rates may work due to random chance. No matter the approach, openness to experience is the trait where the participants obtained the best results for both measures.

Despite the progressive research and recent advances in drug therapy to treat solid tumours, the number of cases and deaths in patients with cancer is still a major health problem. Drug repurposing coupled to drug combination strategies has been gaining interest among the scientific community. Recently, our group proposed novel drug combinations for breast and colon cancer using repurposed drugs from different classes (antimalarial and central nervous system (CNS)) and chemotherapeutic agents such as 5-fluorouracil (5-FU), paclitaxel (PTX), and found promising results. Here, we proposed a novel drug combination using different CNS drugs and doxorubicin (DOX), an antineoplastic used in breast cancer therapy, and studied their anticancer potential in MCF-7 breast cancer cells. Cells were treated with each drug alone and combined with increasing concentrations of DOX and cell viability was evaluated by MTT and SRB assays. Studies were also complemented with morphological evaluation. As...

Several central nervous system (CNS) drugs exhibit potent anti-cancer activities. This study aimed to design a novel model of combination that combines different CNS agents and antineoplastic drugs (5-fluorouracil (5-FU) and paclitaxel (PTX)) for colorectal and breast cancer therapy, respectively. Cytotoxic effects of 5-FU and PTX alone and in combination with different CNS agents were evaluated on HT-29 colon and MCF-7 breast cancer cells, respectively. Three antimalarials alone and in combination with 5-FU were also evaluated in HT-29 cells. Different schedules and concentrations in a fixed ratio were added to the cultured cells and incubated for 48 h. Cell viability was evaluated using MTT and SRB assays. Synergism was evaluated using the Chou-Talalay, Bliss Independence and HSA methods. Our results demonstrate that fluphenazine, fluoxetine and benztropine have enhanced anticancer activity when used alone as compared to being used in combination, making them ideal candidates for ...

Introduction: Cancer cells may exhibit outsourcing of their high energy need in order to avoid the intrinsic mitochondrial apoptosis. Reduced mitochondrial respiration and accumulation of mitochondrial genome mutations are among metabolic transformations in this regard. Mitochondrial humanin (MT-RNR2) is a small peptide with anti-apoptotic activities attributed to binding some pro-apoptotic proteins. Aim of the work: The current study aims at investigating the expression of mitochondrial humanin in bladder tumor cells and the possible casting of humanin anti-apoptotic action through orchestrating some of the mitochondrial metabolic enzymes. Material and methods: Here messenger RNA of humanin, succinate dehydrogenase, glutaminase, isocitrate dehydrogenase were compared in tissues from patients with T2 bladder carcinoma in comparison to tumor associated normal tissues from the same patients. Levels of lactate and mitochondrial pyruvate carrier (MPC1) mRNA were determined to scrutinize the prevalence of aerobic glycolysis. Results: The present study found that tumor cells had suppressed aerobic glycolysis, augmented mitochondrial respiration and interrupted tricarboxylic acid cycle, all of which were suggested to serve tumor aggressiveness. MT-RNR2 was found closely related to the alterations in mitochondrial activity. Conclusion: MT-RNR2 plays its anti-apoptotic role partly by avoiding deploying energy from complete oxidation of organic compounds to inorganic wastes. Thus MT-RNR2 can potentially serve as a new biomarker in the diagnosis of bladder carcinoma especially that it is present in blood circulation.

This edition reflected new findings and the latest trends in the areas of pharmacological treatment. The aim of this study is to present strategies and treatment options according to the subtype of depression using data from the KMAP-DD-2021. Methods Ninety-seven psychiatrists with clinical experience in depressive disorder were selected. The questionnaires for KMAP-DD 2021 were sent to participants via mail. KMAP-DD 2021 consists of overall treatment strategies and treatment options under specific circumstances. Each treatment strategy or treatment option was evaluated with an overall score of nine and was divided into the three phases of recommendation that include primary, secondary, and tertiary. Results For persisting depressive disorder, antidepressant monotherapy including selective

This paper proposes a general approach for using conversational interfaces such as chatbots to offer adaptive learning of business processes in an environment involving different actors. Adaptivity concerns both the content being proposed, the sequence of learning items, and the way the conversation is conducted. The original approach allows the development of sustainable chatbots and empowers various non-technical actors (authors, teachers, publishers, and learners) to control the chatbot features directly. The aCHAT-WF framework (adaptive CHATbot for WorkFlows), proposed in this paper for managing conversational interfaces, conceptually represents all the aspects related to a conversation about business processes, with different facets for the user, the conversation flow, and the conversation contents, combining them to obtain a flexible interaction with the user. The paper focuses on the different preparation phases for instructional material based on Business Process Modeling No...

Author profiling consists of predicting some author's characteristics (e.g. age, gender, personality) from her writing. After addressing at PAN@CLEF mainly age and gender identification, and also personality recognition in Twitter 1 , in this PAN@FIRE track on Personality Recognition from SOurce COde (PR-SOCO) we have addressed the problem of predicting author's personality traits from her source code. In this paper, we analyse 48 runs sent by 11 participant teams. Given a set of source codes written in Java by students who answered also a personality test, participants had to predict personality traits, based on the big five model. Results have been evaluated with two complementary measures (RMSE and Pearson product-moment correlation) that have permitted to identify whether systems with low error rates may work due to random chance. No matter the approach, openness to experience is the trait where the participants obtained the best results for both measures.

In the industry domains such as transportation, power generation and heavy engineering industries utilize complex machinery, as their working principles are very complex and it is very difficult to predict their exact life and operational availability due to difficulties involved in their operations. PHM-Prognostics and health management is one such domain which supports in the management of this machinery also known as assets for continuous monitoring for their best utilization and maximum efficiency. For any machine, the current health of the system can be determined by operational and raw sensor data. This data can also be utilized for the prediction of remaining useful life (RUL) of the system provided a reliable prediction model is available. It is always be challenging to determine the remaining useful life of complex machines such as turbofan jet engines from the knowledge of the data available from operating conditions and sensor data. An HPT LSTM-advanced hyper parameter tuned LSTM-Long Short Term Memory neural network model is developed to accurately determine the remaining useful life of the turbojet fan engines. To test this predictive model, a NASA developed database CMAPSS-Commercial Modular Aero Propulsion System Simulation is used. The performance of this HPT LSTM is found to be much improved as compared to reference machine learning algorithms such as simple linear regression and Lagged Multi-Layer Perceptron Models

In 1967 IBM (International Business Machines) commissioned Henri Cartier-Bresson to produce a portfolio of photographs depicting human relationships with technology around the world. These images, along with a selection from the photographer's archive were realized in 1968 as the touring exhibition and photobook Man and Machine. In contrast to the images of war, revolution and protest, so often mobilized as the documentary imaginary and record of these years, Man and Machine appears to celebrate a harmonious technologically mediated world over which man was still in control. More than this, it seemingly flattens the stark divides between First and Third World experiences under the leveling glow of liberal humanism and what was being naturalized as its equivalent: global Capital. Approaching Man and Machine retrospectivelyfrom the perspective of the New Left's 1970s critique of documentary humanist photographyas well as in terms of its own contemporaneousness, resituating it in the contemporary image cultures of the Cold War-I propose that documentary photography's ideological mobility at this juncture might be understood not only as an inherent weakness or limitas the means of its compromise and ultimate failurebut also as a resource: a potential arsenal of unpredictable, disjunctive and even radical political affects and effects.

The paper presents the convergences and divergences of Nonprofit Organizations (NPO) theory and Social Management. Then, it present the possibilities of development of Social Management in the NPO. At the end of the paper, the main contributions of Brazilian Social Management theory to the international nonprofit debate are summarized and leave open some guidelines to future researchers that may want to follow this research stream..

Sağlık alanında dijital dönüşüm, sağlıkla ilgili tüm verilerin, bilgilerin ve süreçlerin dijitalize edilmesini içeren kapsayıcı dönüşümdür. Kriptopara konusunda duymaya alıştığımız blokzincir teknolojisi, verilerin işlenmesi, güvenliği, paylaşılması ve depolanması konusunda sağlık alanında da bilişim teknolojisinin entegrasyonu ile birlikte kendisine önemli bir yer edinmeye başlamıştır. Blokzincir teknolojisi, çeşitli kriptografiler kullanılarak birbirine bağlanan blokların tutulduğu, sürekli büyüyen bir kayıt defteri olarak tanımlanır. Merkezi olmayan bağlantılar ile birbirine bağlanan bloklar, verileri saldırı ve sonradan değiştirilmeye karşı korunaklı hale getirmektedir. Bütüncül bir yaklaşımla bakıldığında diş hekimliği sağlık alanının ayrılmaz bir parçasıdır. Diş hekimliğinde yapılan uygulamaların çoğu girişimseldir ve her uygulama öncesinde hastanın genel sağlığı ile ilgili detaylı bilgi ihtiyacı bulunmaktadır. Tıp ve diş hekimliği arasında güvenilir, değiştirilemez ve merkezi olmayan blokzincir gibi teknolojilerin entegre edilmesi, daha sağlıklı bilgi edinilmesi ve yapılan işin kalitesi açısından da önem taşımaktadır. Ayrıca sağlık alanında olduğu gibi diş hekimliğinde de etik ve kişisel verilerin korunması bakımından yasal zorunluluklar bulunmaktadır. Sanal ortamda çeşitli kurumlara yapılan saldırılar ve sızdırılan kişisel bilgiler, verilen korunması için farklı teknolojilerin kullanımını zorunlu kılmaktadır. Blokzincir teknolojisi veri güvenliği konusunda diş hekimliği alanında da yeni ufuklar açmaktadır. Yapılan araştırma verilerinin korunması ve paylaşılması, tanısal doğruluğun arttırılması, yapay zekanın diş hekimliğine adaptasyonu gibi konularda da blokzincir teknolojisinden faydalanılması öngörülmektedir. Araştırmalarda verilerin değiştirilmeden saklanılması, meta-analiz gibi çalışmaların daha sağlıklı yapılması ve birden fazla merkezli çalışma yapmanın daha kolay hale gelmesi açısından blokzincir teknolojilerinin avantajları bulunmaktadır. Sonuç olarak blokzincir teknolojisinin özerk, değiştirilemez ve güvenilir olması, diş hekimliği alanında da veri yönetiminde altın standart haline dönüşmesinde rol oynamaktadır.

We present IoTutor that is a cognitive computing solution for education of students in the IoT domain. We implement the IoTutor as a platform-independent web-based application that is able to interact with users via text or speech using natural language. We train the IoTutor with selected scientific publications relevant to the IoT education. To investigate users' experience with the IoTutor, we ask a group of students taking an IoT master level course at the Linnaeus University to use the IoTutor for a period of two weeks. We ask students to express their opinions with respect to the attractiveness, perspicuity, efficiency, stimulation, and novelty of the IoTutor. The evaluation results show a trend that students express an overall positive attitude towards the IoTutor with majority of the aspects rated higher than the neutral value.

Il contributo descrive due proposte didattiche CLIL per la scuola secondaria di primo e secondo grado tese a stimolare una riflessione sui sistemi di Intelligenza Artificiale (IA). La prima proposta prevede l’impiego del software di AI art DALL·E 2 nell’ambito della storia dell’arte, mentre la seconda si avvale delle funzionalità di sentiment e tone analysis del servizio Natural Language Understanding di IBM Watson per supportare l’interpretazione letteraria e la traduzione contrastiva.

Given the financial and resource constraints of the thesis, semi structured interviews and Wizard of Oz experiments were chosen as the methods of study. These methods helped in delving deep into user issues within limited time period. The study finds that investors were happy to get response in text and graphics mode but not in voice since the information was considered confidential. There were apprehensions in using chatbot for getting investment advice. Findings of this study may be helpful to wealth management organisations in designing conversation UI strategy. However, the study was conducted with clients in India, hence the findings are more relevant to countries with similar sociocultural conditions.