Miracle-dz/UniFAR-FTUs huggingface dataset:
Size related dietary shifts of Epinephelus marginatus in a western Mediterranean littoral ecosystem: an isotope and stomach content analysis

The diet of the dusky grouper Epinephelus marginatus, from the Balearic Islands, western Mediterranean, consisted primarily of crustaceans, molluscs and fishes, but diet composition varied with body size. The smaller dusky groupers (<300 mm L T ) fed primarily on crustaceans, and particularly on brachyurans, which accounted for 46% of the prey identified. As dusky groupers grew, cephalopods became increasingly important and constituted 10 to 40% of the prey identified in subadult and adult specimens. The largest dusky groupers fed primarily on fishes that represented 40.9% of prey identified. These shifts in diet were accompanied by a positive selection of increasingly large prey and by an expansion of trophic niche. δ 15 N values of dusky grouper white muscle ranged from 8.8 to 13.1‰ and 71% of the variation in δ 15 N was explained by differences in dusky grouper size. δ 13 C values ranged from - 17.9 to - 15.9‰, and no significant body size effect on δ 13 C was detected. Stomach content and 13 C values indicated that from 1 year old, the diet of E. marginatus was based on the benthic food web. The enrichment in δ 15 N registered from juvenile to large males was c. 3.8‰. Overall, there was good agreement between gut content and stable isotope data indicating that the latter may be useful as a tool in trophic studies in marine protected areas where sampling for fishes is not allowed.
Optimization of placement in the tasks of rapid prototyping and manufacturing of volumetric parts based on additive technologies

The problem of optimizing the life cycle of complex three-dimensional objects in small-scale production is considered. Additive technologies and optimization algorithms for the placement of three-dimensional objects are considered as technologies to solve this problem. Using the multilevel synthesis method can significantly reduce the time for prototyping new products. It should be noted that since several independent parts can be manufactured at the same time, this problem belongs to the class of optimization geometric modelling problems, namely, the problem of three-dimensional irregular placement. An algorithmic solution is proposed for the most complex task - placing 3D objects in a container. The results of the analysis of the effectiveness of the proposed algorithms are discussed.
A Gas-Efficient Superlight Bitcoin Client in Solidity

Superlight clients enable the verification of proof-of-work-based blockchains by checking only a small representative number of block headers instead of all the block headers as done in simplified payment verification (SPV). Such clients can be embedded within other blockchains by implementing them as smart contracts, allowing for cross-chain verification. One such interesting instance is the consumption of Bitcoin data within Ethereum by implementing a Bitcoin superlight client in Solidity. While such theoretical constructions have demonstrated security and efficiency in theory, no practical implementation exists. In this work, we put forth the first practical Solidity implementation of a superlight client which implements the NIPoPoW superblocks protocol. Contrary to previous work, our Solidity smart contract achieves sufficient gas-efficiency to allow a proof and counter-proof to fit within the gas limit of a block, making it practical. We provide extensive experimental measurements for gas consumption. The optimizations that enable gas-efficiency heavily leverage a novel technique which we term hash-and-resubmit, which almost completely eliminates persistent storage requirements, the most expensive operation of smart contracts in terms of gas. Instead, the contract asks contesters to resubmit data and checks their veracity by hashing it. Other optimizations include off-chain manipulation of proofs in order to remove expensive look-up structures, and the usage of an optimistic schema. We show that such techniques can be used to bring down gas costs significantly and may be of independent interest. Lastly, our implementation allows us to calculate concrete cryptoeconomic parameters for the superblocks NIPoPoWs protocol and in particular to make recommendations about the monetary value of the collateral parameters. We provide such parameter recommendations over a variety of liveness settings.
Continuous Transition from Model-Driven Prototype to Full-Size Real-World Enterprise Information Systems

This paper presents our approach to create an executable prototype of an enterprise information system based only on a data structure model. This prototype, which is still easily adaptable and extendable, can be used for analysis exploration and builds a solid foundation for the final system. The presented approach transforms a data structure model to changeable and extendable graphical user interface models . In a second step, the data structure model and the GUI models are used to generate the resulting system. This approach allows the developer to generate (a) persistence, (b) basic application logic, (c) transportation layers, and (d) a variety of possible graphical representations for the prototype based only on a data structure model. Extensions and changes of the GUI are still possible on model and code level. This is possible by synthetization of GUI models and change operations defined in the same domain-specific language.
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The rise in electronic interactions has made information networks ubiquitous. Correspondingly, research across multiple domains has begun to acknowledge the social and economic value of these networks for business decision-making. In this paper, the authors introduce a new type of information artifact, implicit brand networks, for obtaining close to real-time estimates of within-industry competition and across-industry complementarities. Statistical examination of the tacit links in the network, using Exponential Random Graph Models from network theory, reveals a mix of network and brand level characteristics responsible for the observed network structure. The paper concludes by discussing the practical applications of the information network, particularly for the automatic extraction of category-specific brand ratings. As information pertaining to category-specific ratings (e.g. sports, tech, luxury etc.) is rarely found in online users’ comments, the brand network’s ability to automatically reveal such insights, with minimal a-priori assumptions, is a significant contribution of this study.
Are we Ready for Artificially Intelligent Leaders? A Comparative Analysis of Employee Perceptions Regarding Artificially Intelligent and Human Supervisors

If artificially intelligent agents autonomously make decisions, which might personally affect employees, their perceptions are crucial. By applying a quasi-experimental survey design, we will compare to which degree varying levels of transparency and complexity influence trust towards human supervisors and intelligent systems. Our findings would contribute to the understanding of individual-level perceptions regarding situational and task-related antecedents of trust towards intelligent systems in a hierarchical, organizational context. Moreover, the comparative approach could highlight (dis)advantages of artificially intelligent agents in comparison to human supervisors under specific circumstances. Thereby, we could validate the MABA-HABA framework and identify opportunities for the application of intelligent systems.
Business/IT Integration: Challenging the Boundaries of Alignment

Digitalization requires innovations in information and communication technologies for organizations to stay competitive. To this day, IT functions are mainly responsible for providing and ensuring information flows and thus play a key role in the realization of innovations. To manage and use IT in accordance to organizational needs, business/IT alignment offers several entry-points to connect IT functions to business goals. However, the alignment idea still considers IT and business as separate and self-sufficient entities, pursuing their own strategies and (hidden) agendas. Pursuing both strategies cannot sufficiently meet the requirements of digitalization. Therefore, we challenge the boundaries of alignment by presenting our approach of business/IT integration considering IT functions as fully integrated into value creation processes. The result is a merger of both entities resolving its functional separation. By conducting an online survey examining current limitations of interaction between business and IT, we suggest rethinking former separation to overcome existing boundaries.
Ecological, Behavioral, and Life‐History Correlates of Mammal Extinctions in West Africa

Abstract: Identifying the biological traits of species that predispose them to extinction is a focus of research in evolutionary ecology and conservation biology. This research has traditionally been divided between studies of extinction or decline in undisturbed habitat islands and studies of the persistence of species affected adversely by human influence. I combined these approaches to test for correlations between nine ecological, behavioral, and life‐history traits and vulnerability to local extinction for 41 species of carnivores, primates, and ungulates in fragmented and exploited habitats in Ghana, West Africa, while accounting statistically for phylogeny. Species distributed in isolated populations were most prone to local extinction, and monogamous species and those wherein males defended small harems were also prone to extinction. Body size, fecundity, abundance, habitat specialization, trophic group, and the degree to which hunters and consumers preferred a species generally were unrelated to species persistence. Although population isolation and mating system were the only traits that explained a significant amount of the observed variation in persistence of all species, analyses of carnivores, primates, and ungulates as groups yielded varied results. Mammals most prone to local extinction in my study reserves were also those listed by the World Conservation Union as being at greatest risk of global extinction. Thus, my results suggest that the relative isolation of populations and the mating system displayed by mammals may be good general predictors of their persistence.
Multi-Currency Ledgers

This paper extends an abstract formal model of UTxO - based and account-based transactions to allow the creation and use of multiple cryptocurrencies on a single ledger. The new model also includes a general framework to establish and enforce monetary policies for created currencies. In contrast to alternative approaches, all currencies in this model exist natively on the ledger and do not necessarily depend on a main currency. In comparison to non-native approaches based on scripts and smart contracts, native currencies allow smaller transactions that can be more eﬃciently processed and can be moved between chains through a sidechain approach.
Describing coevolution of business and IS alignment via agent-based modeling

The coevolution of business and IS alignment is a growing concern for researchers and practitioners alike. Extant literature on describing and modeling the coevolution is still in infancy, which makes it hard to capture the complexity and to offer reasonable decisions in the evolution of organizations. This paper focuses on the actors’ behaviors, and explores their emergent effects on the holistic alignment. We build an agent-based model to describe the complex alignment landscape and to improve the coevolution governance. The model embraces the emergent behaviors shaped by the interactions of business and IS agents, and guides the coevolution of alignment driven by the external changes. The development of this model forms a necessary step towards suggesting guidance how to analyze and implement coevolution in companies. The paper also shows the capability of an agent-based model to capture some of the emergent behaviors that emerge from bottom-level behaviors.
Improving Mental Health Outcomes through Machine Learning Feedback of Social Media Behavior

With mental health issues on the rise, the need for early diagnosis is especially pivotal to reduce the risk of suicide and disease. Both social media usage and social media content can act as indicators of a user’s mental health status. We posit that through using machine learning feedback, we can assist users in early self-diagnoses and monitor how that feedback affects their social media behavior and their mental health. By providing continuous feedback about users’ men tal health, we can encourage users to change their social media habits and seek help from a mental health professional
Dynamic viscosity of olive oil as a function of composition and temperature: A first approach

Knowledge of the viscosity of virgin olive oils (VOOs) is of great importance for the design of pilot plants, to determine the time required for the settling of particles at the end of the production chain and from a sensory view point. The dynamic viscosities of French VOOs from four different cultivars (‘Aglandau’, ‘Bouteillan’, ‘Salonenque’ and ‘Tanche’) were studied as a function of their fatty acid and TAG compositions and of the temperature [10–50°C]. These four VOOs had different TAG and fatty acid compositions representative of the range of compositional variations in the main French oils. Their viscosities were similar, although small but measurable differences that depended on their compositions were apparent. All the VOO samples exhibited the same dynamic viscosity pattern over temperature. For a given temperature, the viscosity difference was the greatest between Aglandau and Salonenque oils, Aglandau being the oil with the highest viscosity. The correlation between temperature and viscosity was highlighted by an Arrhenius model for this Newtonian fluid. The Arrhenius activation energy was correlated (R2 = 0.993) with the percentage of triolein, the main TAG in olive oil.
What is Yours is "Mine"! A Model to Examine Consumers' Value Co-Creation in Accommodation Sharing

In this study, we conceptualize a research model in the context of accommodation sharing platforms to examine the antecedents of consumers (guests) value co-creation behaviors using the theoretical lens of psychological ownership (PO). We theorize that the mechanisms of perceived control, intimate knowledge and social interactions moderated by platform mediated communications can induce the development of PO towards target accommodations. We conceptualize the outcome of PO as positive value co-creation behaviors (feedback, advocacy, helping and tolerance) that can be valuable for sustaining participation in accommodation sharing. We plan to collect data from Airbnb users and use SEM to test our research model. Theoretically, our research has the potential to contribute to the emerging phenomenon of sharing economy and value co-creation enabled by online platforms. Also, practitioners can use the conceptual framework to leverage value co-creation behaviors for sustaining participation in accommodation sharing.
Efficient Multi-Client Functional Encryption for Conjunctive Equality and Range Queries

In multi-client functional encryption (MC-FE) for predicate queries, clients generate ciphertexts of plaintexts <inline-formula> <tex-math notation="LaTeX">$x_{1}, \ldots, x_{n}$ </tex-math></inline-formula> binding with a time period <inline-formula> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> and store them on a cloud server, and the cloud server receives a function key corresponding to a predicate <inline-formula> <tex-math notation="LaTeX">$f$ </tex-math></inline-formula> from a trusted center and learns whether <inline-formula> <tex-math notation="LaTeX">$f(x_{1}, \ldots, x_{n}) = 1$ </tex-math></inline-formula> or not by running the decryption algorithm on the multiple ciphertexts of the same time period. MC-FE for predicates can be used for a network event or medical data monitoring system based on time series data gathered by multiple clients. In this paper, we propose efficient MC-FE schemes that support conjunctive equality or range queries on encrypted data in the multi-client settings. First, we propose an efficient multi-client hidden vector encryption (MC-HVE) scheme in bilinear groups and prove the selective security with static corruptions. Our MC-HVE scheme is very efficient since a function key is composed of four group elements, a ciphertext consists of <inline-formula> <tex-math notation="LaTeX">$O(\ell)$ </tex-math></inline-formula> group elements where <inline-formula> <tex-math notation="LaTeX">$\ell $ </tex-math></inline-formula> is the size of a plaintext, and the decryption algorithm only requires four pairing operations. Second, we propose an efficient multi-client range query encryption (MC-RQE) scheme and prove the selective weak security with static corruptions. Our MC-RQE scheme which uses a binary tree is efficient since a ciphertext consists of <inline-formula> <tex-math notation="LaTeX">$O(\log D)$ </tex-math></inline-formula> group elements and a function key consists of <inline-formula> <tex-math notation="LaTeX">$O(n \log D)$ </tex-math></inline-formula> group elements where <inline-formula> <tex-math notation="LaTeX">$D$ </tex-math></inline-formula> is the maximum value of a range.
Improved Methods for In-situ Measurement Railway Noise Barrier Insertion Loss

Many countries which seek to understand the acoustic performance of railway noise barriers have established standards for the conduct of in-situ experiments. However, there are no universally acknowledged receiver positions for the evaluation of the barrier performance, a fact which may be leading to uncertainty over the noise reduction capabilities of available barriers. In terms of the descriptor of the barrier performance, the general recommendation is the A-weighted sound pressure level, although the latter is considered to underestimate low frequencies for railway noise barrier. Thus, in this study, the comparison of receiver positions and the descriptors among existing Chinese, ISO and European standards were investigated. Based upon a combination of diffraction theory and standards, a rearrangement of receiver positions and one-third-octave-band analysis were proposed. In addition, in line with improved methods, an in-situ measurement of insertion loss for a 1.5m high railway noise barrier was designed and conducted. The results of the experiment validate as effective and applicable the new receiver positions. These results also suggest that one-third-octave-band analysis is indispensable.
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Recommender Systems have been intensively used in Information Systems in the last decades, facilitating the choice of items individually for each user based on your historical. Clustering techniques have been frequently used in commercial and scientific domains in data mining tasks and visualization tools. However, there is a lack of secondary studies in the literature that analyze the use of clustering algorithms in Recommender Systems and their behavior in different aspects. In this work, we present a Systematic Literature Review (SLR), which discusses the different types of information systems with the use of the clustering algorithm in Recommender Systems, which typically involves three main recommendation approaches found in literature: collaborative filtering, content-based filtering, and hybrid recommendation. In the end, we did a quantitative analysis using K-means clustering for finding patterns between clustering algorithms, recommendation approaches, and some datasets used in their publications.
Strategies to Enhance Logic Modeling-Based Cell Line-Specific Drug Synergy Prediction

Discrete dynamical modeling shows promise in prioritizing drug combinations for screening efforts by reducing the experimental workload inherent to the vast numbers of possible drug combinations. We have investigated approaches to predict combination responses across different cancer cell lines using logic models generated from one generic prior-knowledge network representing 144 nodes covering major cancer signaling pathways. Cell-line specific models were configured to agree with baseline activity data from each unperturbed cell line. Testing against experimental data demonstrated a high number of true positive and true negative predictions, including also cell-specific responses. We demonstrate the possible enhancement of predictive capability of models by curation of literature knowledge further detailing subtle biologically founded signaling mechanisms in the model topology. In silico model analysis pinpointed a subset of network nodes highly influencing model predictions. Our results indicate that the performance of logic models can be improved by focusing on high-influence node protein activity data for model configuration and that these nodes accommodate high information flow in the regulatory network.
Ultrarapid Delayed Rectifier K+ Channelopathies in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes

Atrial fibrillation (AF) is the most common cardiac arrhythmia. About 5–15% of AF patients have a mutation in a cardiac gene, including mutations in KCNA5, encoding the Kv1.5 α-subunit of the ion channel carrying the atrial-specific ultrarapid delayed rectifier K+ current (IKur). Both loss-of-function and gain-of-function AF-related mutations in KCNA5 are known, but their effects on action potentials (APs) of human cardiomyocytes have been poorly studied. Here, we assessed the effects of wild-type and mutant IKur on APs of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). We found that atrial-like hiPSC-CMs, generated by a retinoic acid-based differentiation protocol, have APs with faster repolarization compared to ventricular-like hiPSC-CMs, resulting in shorter APs with a lower AP plateau. Native IKur, measured as current sensitive to 50 μM 4-aminopyridine, was 1.88 ± 0.49 (mean ± SEM, n = 17) and 0.26 ± 0.26 pA/pF (n = 17) in atrial- and ventricular-like hiPSC-CMs, respectively. In both atrial- and ventricular-like hiPSC-CMs, IKur blockade had minimal effects on AP parameters. Next, we used dynamic clamp to inject various amounts of a virtual IKur, with characteristics as in freshly isolated human atrial myocytes, into 11 atrial-like and 10 ventricular-like hiPSC-CMs, in which native IKur was blocked. Injection of IKur with 100% density shortened the APs, with its effect being strongest on the AP duration at 20% repolarization (APD20) of atrial-like hiPSC-CMs. At IKur densities < 100% (compared to 100%), simulating loss-of-function mutations, significant AP prolongation and raise of plateau were observed. At IKur densities > 100%, simulating gain-of-function mutations, APD20 was decreased in both atrial- and ventricular-like hiPSC-CMs, but only upon a strong increase in IKur. In ventricular-like hiPSC-CMs, lowering of the plateau resulted in AP shortening. We conclude that a decrease in IKur, mimicking loss-of-function mutations, has a stronger effect on the AP of hiPSC-CMs than an increase, mimicking gain-of-function mutations, whereas in ventricular-like hiPSC-CMs such increase results in AP shortening, causing their AP morphology to become more atrial-like. Effects of native IKur modulation on atrial-like hiPSC-CMs are less pronounced than effects of virtual IKur injection because IKur density of atrial-like hiPSC-CMs is substantially smaller than that of freshly isolated human atrial myocytes.