Miracle-dz/UniFAR-FTUs huggingface dataset:
Unruly octopuses are the rule: Octopus vulgaris use multiple and individually variable strategies in an episodic-like memory task

The evolution of complex cognition can be explained by different hypotheses, mutually non-exclusive: the social intelligence hypothesis, the ecological intelligence hypothesis and the predator-prey interaction hypothesis. Episodic-like memory can be used as a proxy to study complex cognition. This ability has mainly been studied through experimental tasks where subjects have to remember what they ate, where and when or in which context. Seemingly quite common in mammals and corvids, episodic-like memory abilities have been observed in only one invertebrate species: the common cuttlefish, a cephalopod mollusc. To explore if this ability is common to all cephalopods or if it has emerged to face specific constraints, we conducted an episodic-like memory task with seven Octopus vulgaris. Only one individual learnt the replenishing rates during the training and subsequently showed episodic-like memory abilities, whereas the other individuals favoured simpler foraging strategies, such as avoidance of familiarity and alternation, use of win-stay strategy and risk-sensitivity. A high variability in the use of these strategies was observed between and within individuals throughout the training. Since octopuses seem to live under lighter environmental pressure than cuttlefish, they may not need to rely on episodic-like memory abilities to optimize foraging as cuttlefish do. These results highlight the differences in the use of complex cognitive abilities between cuttlefish and octopuses, which might be linked with different environmental, predatory and social constraints. Summary statement When trained in an episodic-like memory task, common octopuses favour individually variable foraging strategies rather than keeping track of time to solve the task as cuttlefish do.
A Blockchain Approach for Eliminating Counterfeit Drugs in Pharma Supply Chain

The following paper gives a general review of the trending Blockchain technology and the platforms that be able to deploy to build an infallible system in eradicating spurious drugs in pharmaceutical enterprises. Several report analysis indicates that introduction of substandard drugs into the supply chain by unknown sources is one of the significant problems encountered by the drug companies. Applying blockchain throughout the supply chain operations, multiple issues can be resolved as blockchain is reliable, secure and immutable in nature. Overall, this paper aims to explain how blockchain transactions can fix the existing issues faced by the stakeholders
Stress and Diabetes Mellitus

Diabetes mellitus (DM) is a metabolic disease characterized by chronic hyperglycemia that results from an alteration of the secretion or action of insulin. Modern lifestyle including unhealthy diet, a sedentary lifestyle and stress contribute to T2DM occurrence and development. The present study has been conducted on 100 clinically diagnosed diabetic patients residing in different localities of Jammu and was visiting Government Medical College /Hospital, Jammu for the treatment of the disease to observe the gender wise prevalence of diabetes among selected patients, occurrence of stress among diabetic patients and also to assess the cause of their stress. The present study results indicate the occurrence of diabetes is more common among females (59.00 per cent) than males (41.00 per cent) and that too in the age group of 40-50 years. The mean age of female and male diabetics was found to be 46.74 and 49.56 respectively. Majority of the diabetics (74.00 per cent) were found to be under stress because of one or the other reasons such as job, money, health, spouse, family while the family issues being the most common cause of their stress.
Factors Influencing Overruns of Construction Projects in Northern Nigeria

The timely completion of a project within the set budget is critical to the success of any construction project. Method of execution, labor management, equipment, schedule, and cost are only a few of the aspects that influence project management, and these factors are the cause of cost and time overruns all over the world. Using a completed project, the goal of this study is to identify and prioritize the key causes of time and expense overruns in the construction industry in northern Nigeria. The kano state ground anchoring project, a contracting firm, a consulting firm, and government parastatals all provided data. To understand the reasons of cost and time overruns, the data is studied and compared to the estimated and actual budget schedules. The most major cost reasons include increased material costs, erroneous materials estimation, and underestimating project expenses, among others, while the most significant time factors are unanticipated site conditions, increased project scope, lack of timely progress payment, and inadequate planning. It becomes clear that paying close attention to the elements that contribute to construction overruns will help to mitigate their negative effects on project performance and efficiency. Cost estimators should improve their methods of cost determination, designers should make full designs available at every stage of the construction process, and contractors should conduct adequate site visits for a better understanding of site conditions before pricing and cost forecasting, according to the recommendations.
Anesthesia for Major Thermal Injury : Anesthesiology

THERMAL injuries cause many complications and deaths. In the United States, approximately 1.25 million persons are treated annually for burns, 50,000 patients are admitted to hospitals, and 5,500 die from major thermal injury. [1] Although many studies have documented a progressive improvement in outcome and survival after major burns, [2-5] management of these patients remains challenging to all involved in their care. Improvements in survival have been attributed to the development of the multidisciplinary burn team, an early aggressive surgical approach to major burns, and improved understanding of the pathophysiologic nature of thermal injuries. [6] This article reviews the literature and describes developments that are relevant to anesthesiologists involved in the care of burn patients.
Kartagener's Syndrome a Case Report and Literature Review

Kartagener syndrome is a very rare genetic disorder with autosomal recessive inheritance, characterized by a triad of chronic bronchorrhea with bronchiectasis, chronic sinusitis and situs inversus. It is part of a syndrome of primary ciliary immobility called primary ciliary dyskinesia. Imaging is the key examination in the workup of Kartagener's syndrome and is usually discovered during a CT scan. The treatment is essentially symptomatic and preventive based on the treatment of episodes of respiratory superinfections, physiotherapy for bronchial drainage and anti-influenza and anti-pneumococcal vaccinations. We report a case of Kartagener's syndrome collected in the radiology department of the emergency room.
Quantitative expression analysis of different cold-responsive (COR) and C-repeat binding factors (CBF) genes in wild and cultivated barley under cold acclimation conditions

Cold stress affects plant metabolism and transcripts. The effect on plant metabolism was caused both by direct inhibition of metabolic enzymes at cold temperatures and by reprogramming the gene expression. The main objective of this study was to evaluate and identify of expression level of some cold-related genes under control and cold stress conditions in 11 spring/winter barley (Hordeum vulgare L.) varieties and 2 Hordeum spontaneum wild genotypes. For this purpose, expression profile of the main C-repeat binding factor )CBF( genes along with expression profiles of the two cold-responsive )COR( genes in plants exposed to low temperatures (+4 °C) were investigated. In parallel, measurements of leaf water potential of varieties were performed in control and at low temperature conditions. Results revealed that, the expression level changes of COR14b gene under cold conditions are more consistent with those of the upstream CBF9 gene expression levels in different varieties and time points rather than the other upstream gene (CBF1). The dehidrin8 )DHN8( expression level was also related to the CBF9 gene expression level and the decreased expression of the CBF9 gene resulted in decreased expression or non-expression of the DHN8 gene. Based on results, it could be said that CBF9 interacts with CBF1 to regulate DHN8 expression. Wild genotypes showed statistically insignificant expression increment for investigated genes in days 1 and 8 of stress. This result is an indicator of the increase at expression levels in the stress genes of more tolerant varieties
Isolating functions at the hardware limit with virtines

An important class of applications, including programs that leverage third-party libraries, programs that use user-defined functions in databases, and serverless applications, benefit from isolating the execution of untrusted code at the granularity of individual functions or function invocations. However, existing isolation mechanisms were not designed for this use case; rather, they have been adapted to it. We introduce virtines, a new abstraction designed specifically for function granularity isolation, and describe how we build virtines from the ground up by pushing hardware virtualization to its limits. Virtines give developers fine-grained control in deciding which functions should run in isolated environments, and which should not. The virtine abstraction is a general one, and we demonstrate a prototype that adds extensions to the C language. We present a detailed analysis of the overheads of running individual functions in isolated VMs, and guided by those findings, we present Wasp, an embeddable hypervisor that allows programmers to easily use virtines. We describe several representative scenarios that employ individual function isolation, and demonstrate that virtines can be applied in these scenarios with only a few lines of changes to existing codebases and with acceptable slowdowns.
Solving generalised Padé approximations over polynomial rings

We consider a type of Pad´e approximations over polynomial rings over ﬁelds, dubbed “2D Pad´e approximations”, which generalise both simultaneous and Hermitian Pad´e approximations. This form is related to but distinct from both matrix-Pad´e approximations as well as order bases. These approximations occur in e.g. decoding of algebraic codes. We demonstrate how to solve such approximations us-ing row reduction of polynomial matrices, and we review the achieved asymptotic complexity when using various fast, known methods for this. We take a closer look at the Mulders–Storjohann for row reduction and show that its complexity is linked to the orthogonality defect of the input matrix, implying that it is fast when applied to 2D Pad´e approximations. We design a new algorithm, which essentially carries out the computations performed by Mulders–Storjohann in a demand-driven manner, yielding an algorithm which is often even faster. This algorithm could be considered as a heavy generalisation of the classical Berlekamp–Massey algorithm. We also consider “weighted” variants of 2D Pad´e approximations, and it is shown how the considered algorithms can handle this with very little speed penalty.
Framing Causal Events in Japanese and English

This paper is an investigation of whether or not the concept of frame developed in the FrameNet project can function as a tool for assessing the accuracy of scientific translation, in which conceptual clarity dominates other considerations. First, in order to illustrate rhetorical differences between English and Japanese prose, the paper will attempt to reformulate as empirical hypotheses the cognitively deep typological characteristics claimed to differentiate the two languages and will explore ways of testing them with data taken from parallel texts. It will then analyze a sentence pair exhibiting characteristic differences between them using descriptive notions developed in FrameNet. In 1930 Japan, a silent movie entitled Nani ga kanojo o soo saseta ka? ‘What made her do it? ’ made a sensation and achieved box-office success.
Molecular Scale Simulations of the Self–Assembly of Amphiphilic Molecules: Current State-of-the-Art and Future Directions

Gaining an understanding of the self–assembly of amphiphilic molecules has been a goal for experimental, theoretical and computational research in the field of soft matter for approximately a century. In the field of materials modelling, understanding the self–assembly of amphiphilic molecules at experimental conditions has proven to be a challenging problem and has led to several developments that have driven the entire field of computational materials science forward. In this review, we present the current-state-ofthe-art in terms of applying all-atom and coarse–grain molecular dynamics simulations in order to study the self–assembly process and the structure that results. Additionally, we present a few of the challenges that still exist with some ideas as to future directions that may be used to overcome them.
Governing the Geneva Tram Network: Making Decisions without Making Choices

Abstract This paper discusses the challenges of managing urban technical networks exploring four complementary dimensions: the autonomy of technical objects, the decision-making model, the reversibility of changes, and the centralization of command and control. The analysis is based on the example of the Geneva tram network, which has experienced an important change of its operating system over recent years. This transformation has created a vigorous social and political controversy. We argue that what is regarded as an intrinsic condition of ungovernability should be better understood as a more or less consciously constructed situation where (a) public transit development does not appear as a real priority within overall transportation policy in Geneva, (b) a delegation of responsibility of managing the tram network occurs from the political to the technical level, and (c) some of the decisions taken at the technical level have, in turn, physically compromised the development of the network.
Uncovering Library Features from API Usage on Stack Overflow

Selecting an appropriate library for reuse within a vast software ecosystem can be a daunting task. A list of features for each library, i.e., a short description of the functionality that can be reused with code examples that illustrate its usage, may alleviate this problem. In this paper, we propose a data-driven approach that uses both the code snippets and the accompanying natural language descriptions from Stack Overflow posts to produce a list of features of a given library. Each extracted feature corresponds to a cluster of API classes and methods considered related based on attributes of the Stack Overflow posts in which they appear. We evaluated the approach considering seven Maven libraries and compared the resulting features against library descriptions from cookbook-like tutorials. The approach achieves an average accuracy of 67% across the seven libraries for the tutorial-like features. For at least 73% of the features extracted by the approach but missing from the documentation, we found a matching library usage in a corpus of GitHub projects. These results suggest that our clusters represent library features, which paves the way to better tool support for documenting software libraries and for selecting a library in an ecosystem.
A Trio Model for Network Performance Evaluation

Performance evaluation is used in computer network communication as a means of assessing the performance of computer networks. Increase in large networks increases routed traffic and reduces the stability of the network. Other factors that lead to the degradation of service performance in networks are network congestion, link failures, and routing instabilities. Literature also has it that most of these disruptions occur during routing changes and a few hundred milliseconds of disruption are enough to cause a disturbance in voice and video. To effectively and efficiently distribute data, the choice of routing protocol becomes a very critical factor in determining the performance of a network over time. This study through an online survey, determined some of the most popular protocols currently being deployed such as the Routing Information Protocol (RIP), the Enhanced Interior Gateway Routing Protocol (EIGRP) and the Open Shortest Path First (OSPF) and standard metrics (throughput, jitter and latency). The Optimized Network Engineering Tool (OPNET) simulation environment was utilized for this study. The study tested the model by varying the traffic of real time applications such as video streaming, electronic mail, database application, Remote Login application, Hypertext Transfer Protocol (HTTP), File Transfer Protocol (FTP), email application and voice conferencing. The evaluation was based on the network topology employed by the Integrated Services Unit of the Afe Babalola University as well as the external communication links and nodes. The study concluded that OSPF is better suited for high load Networks, while RIP is better suited for low load networks. Consequently, EIGRP generally performed well for both low and high load networks and should be used as an effective tradeoff between the two other routing protocols.
Development of Local Feature Models for Accurate Detection and Classification of Medical Images

The effectiveness of local or global features has recently attracted growing attention in the field of texture image classification and retrieval. The features of the local binary pattern (LBP) for instance, usually lack global spatial information while global descriptors would provide very little local information. This paper proposes two different descriptors to circumvent these shortcomings by providing more information to describe different textural structures of the Emphysema computed tomography (CT) images. The proposed LBP+Multi-fractal Images (LMI) and the rotational invariant LBP+Multi-fractal Images (RLMI) can provide more accurate classification results by using a hybrid concatenation of the local and global features. The experimental approaches are validated for different scales of Emphysema images during the classification process in order to determine the appropriate image size that could yield the maximum classification accuracy. The experimental results show that the descriptors extracted from the combined features considerably improve the performance of the classifiers. The results also indicate that the LMI descriptor outperforms the earlier approaches and demonstrate the discriminating power and robustness of the combined features for accurate classification of Emphysema CT images.
Ethosomes: A Novel Tool for Transdermal Drug Delivery

The vesicles have been well known for their importance in cellular communication and particle transportation for many years. Ethosomes are soft vesicles made of phospholipids and ethanol (in higher quantity) and water. Ethosomes can be prepared by two very simple and convenient methods that is hot method and cold method. The uses of ethosomes as carrier system for transdermal/topical drug delivery.
Study of Fourier series of user defined waveforms using ExpEYES−17 kit

This article presents the study of Fourier series experimentally, using the ExpEYES−17 kit in a different way. This familiar undergraduate experiment has been performed for teaching online laboratory classes when face-to-face classes were not possible, due to the COVID − 19 pandemic. We chose parabolic and sawtooth waveforms, which are not generally considered for this experiment. The amplitudes A n of different harmonics were measured to compare with the theoretical predictions and the ratios An/A1 were found to agree well.
Intelligent Blockchain System Based on Differential Privacy

Due to the advantages of decentralization, traceability and non deletion, blockchain technology can be well combined with differential privacy algorithm to protect data privacy. Therefore, it effectively ensures the privacy security of data stored in the system in terms of technical structure and algorithm. This paper proposes a micro service system architecture based on super ledger fabric, which carries out data privacy noise processing combined with smart contract, and carries out different noise processing according to the security level recognized by the system at the time of user registration. The implementation and test results of the system show that the system architecture has good scalability, traceability and security, can meet the query control of users for data privacy, and effectively prevent the tampering and destruction of data by malicious attackers.
MASSIVELY PARALLEL ARCHITECTURE FOR AN UNSUPERVISED SEGMENTATION MODEL

- In this paper we propose the structure of a novel massively parallel system-on-chip (SoC) architecture for a state-of-the-art probabilistic image segmentation model. This probabilistic model is formulated on a regular Markovian pixel grid. The unique combination of algorithmic robustness, SoC and real-time processing capabilities provides a new type of image processing systems in real-world applications. The model and the SoC architecture are extensively tested by natural images. Some chip design examples are also included to (cid:12)-nalize the contribution.
Effectiveness of augmented reality implementation methods in teaching Science to middle school students

The aim of this study was to determine the effectiveness of the Science teaching process to middle school students using teaching materials prepared via augmented reality (AR) technology. In the experimental study, 61 sixth grade students at a middle school in Antalya in the 2019-2020 academic year were selected randomly, and the mixed research design was utilized to understand the academic achievements of students and their' opinion about the augmented reality implementations in Science classes. In the study, the control group were taught through the science curriculum prescribed methods, and the experimental group were taught using augmented reality implementations, and these groups were compared in terms of their achievement. The quantitative data were collected via an achievement test, and the qualitative data were collected via an interview form. The quantitative and qualitative data were analyzed using t-test and descriptive data analyses methods. As a result of the study, it was revealed that AR implementations contributed positively to students' science learning processes, and it increased their academic achievement. It was also shown that AR implementation contributed to students' meaningful learning by making abstract subjects concretized, and at the same time it increased students' interest and motivation in Science lessons. ©
A qualitative study to identify the factors that influence the acquisition of Enterprise Resource Planning Systems by Small and Medium Enterprises

Enterprise Systems (ES) have been known to enable strategic decision-making in addition to improving operational efficiency. Large enterprises the world over have benefitted from these systems. Over the last several years, there has been an increase in the number of ESs implementations in Small and Medium Enterprises (SME). This is due to several factors including that the large enterprise segment is saturated with most companies having already implemented an ES. An ES acquisition is a strategic decision that can significantly affect future competitiveness and performance of a SME. While it is well documented that large enterprises use a structured approach to ERP evaluation and selection, the same is not true in the case of SMEs. In this paper, the author elucidates the factors that influence the acquisition decision. This is based on the insights gained from a study carried out at 6 SMEs who have acquired an ES.