Miracle-dz/UniFAR-FTUs huggingface dataset:
Random Forest Algorithm of Classification in Prediction of Diabetes

Random Forests are nothing but a cluster of various decision trees in which each tree depends on the values of a random vector sampled independently. Generally, random forests are the combination of several decision trees which are used in prediction of different consequences using machine learning algorithms and techniques. Generally, these are used in internet security, medicine, weather prediction etc. The structure of random forest is complex but it is an efficient algorithm. In this paper, application of the concept of random forest in medical industry is explained. Presently, the most troubling disorder in medical world is diabetes. So, now we use this random forest algorithm in stating whether a person is affected from diabetes or not. The reason behind checking the level of diabetes using an algorithm though having the best medical facilities is due to more population. Handling each and every case and getting the results is bit of time taking task. Using an classification algorithm makes the work much simpler and quicker. Even though there are many algorithms and implementations, still a problem arises. The problem is unstructured data. The data provided may be incomplete, inappropriate, irrelevant, etc. So, first we need to make that data proper and complete. With that proper data, we implement our algorithm. And there are many algorithms to be implemented based on classification like Decision-trees, Naïve-Baye’s, KNN, etc. But, random forest is something which is better than most of the classification algorithm present. It is fast and accurate. With this algorithm we input the health records of several patients and construct a decision tree based on parameters like blood levels, insulin production levels, RBC, WBC count, etc. So, our model understands on what basis a particular patient is suffers from diabetes. This method of
Industry-specific learning and specialization in venture capitalists’ internationalization decisions

: This study considers the impact of venture capitalists’ industry specialization on cross-border investment decisions. Drawing on learning theory, the article argues that specialized venture capitalists’ liability of foreignness is lower in specific international markets, as the assessment of the market and the behavior of the market participants is facilitated through industry-specific learning effects. This leads to a lower risk in cross-border investments from venture capitalists’ point of view, as with increasing deal-specificity, the support and value enhancement of a foreign portfolio company are still ensured in international markets due to the investor’s specialization. A multilevel investigation of 61,933 worldwide venture capital deals from 2001 to 2019 into 72 countries shows a positive relationship between venture capitalists’ industry specialization and internationality. The results are in line with learning theory and show that the likelihood of a cross-border deal increases with higher industry specialization. Furthermore, this effect is negatively moderated by determinants at the institutional and portfolio company levels, reducing the importance of venture capitalists’ own capabilities in international investment decisions.
Senescence-associated morphological profiles (SAMPs): an image-based phenotypic profiling method for evaluating the inter and intra model heterogeneity of senescence

Senescence occurs in response to a number of damaging stimuli to limit oncogenic transformation and cancer development. As no single, universal senescence marker has been discovered, the confident classification of senescence induction requires the parallel assessment of a series of hallmarks. Therefore, there is a growing need for “first-pass” tools of senescence identification to streamline experimental workflows and complement conventional markers. Here, we utilise a high content, multidimensional phenotypic profiling-based approach, to assess the morphological profiles of senescent cells induced via a range of stimuli. In the context of senescence, we refer to these as senescence-associated morphological profiles (SAMPs), as they facilitate distinction between senescent and proliferating cells. The complexity of the profiles generated also allows exploration of the heterogeneity both between models of senescence and within an individual senescence model, providing a level of insight at the single cell level. Furthermore, we also demonstrate that these models are applicable to the assessment of senescence in vivo, which remains a key challenge for the field. Therefore, we believe SAMPs has the potential to serve as a useful addition in the repertoire of senescence researchers, either as a first-pass tool or as part of the established senescence hallmarks.
Case Report Rapunzel Syndrome: An Uncommon Cause of Gastric Perforation

Bezoars are due to the accumulation of indigestible substances in the digestive tract. In the case of trichobezoar, it is an accumulation of ingested hair fold. Rapunzel syndrome is a very rare variant where the trichobezoar developed in the stomach, extends the intestine. Reported for the first time in 1968 and since then, less than 70 cases are reported worldwide. We report a case of Rapunzel syndrome, a complicated by a gastric perforation, in a 17-year-old patient presented for acute peritonitis. The trichobezoar was discovered operatively and the patient was treated successfully with open surgery (gastrectomy).
Solid propellant binders

Solid, propellants are widely used in modern rockets and missiles. Although the history of solid rockets could be traced to the discovery of gunpowder over a thousand years ago, the technology could be perfected only by the later half of the 20(th) century. The failure of gunpowder rockets was largely due to the unknown consolidating technique of the powder composition. The emergence of large solid propellant motors had, to await the dawn of polymer. science and technology(S&T). Specific syntheses of functionally terminated polymers having cross-linking capability led to the emergence of casting technology of solid composite propellants. This review describes the various polymeric fuel/binder systems used or considered for use in solid,propellants. It includes a brief background, advantages, and shortcomings of the various systems, an account of the currently used binders and a critical survey of the advanced polymers envisaged for future usage. Special emphasis has been laid on recently synthesized polymers having N-N bonds in their structures, and-on the feasibility of developing smokeless propellants based on ammonium nitrate.
Improvement of Pedestrian Detection Algorithm Based on YOLO

: The non-maximum suppression algorithm is usually used in the post-position of deep learning object detection algorithm. It suppresses the detection boxes with high overlap rate while using the algorithm. In order to avoid the missed and false detection caused by non-maximum suppression algorithm, an improved maximum value suppression algorithm is proposed. When the IOU of the suppression window and the suppressed window is greater than the given threshold, the confidence multiply by the penalty factor instead of discarding it directly. After multiple iterations, we need to remove the lower scores detection boxes. Experiments show that the YOLO V2 deep learning model with improved algorithm has improved accuracy on different data sets as well as strong versatility and robustness.
Management of paradoxes through merger process

L’objet de cette recherche tend à démontrer comment la tension paradoxale entre autonomie organisationnelle (AO) et interdépendance stratégique (IS) est gérée au cours d’un processus de fusion-acquisition. Nous soutenons que dans le but de créer une intégration post-fusion réussie, la gestion de la tension paradoxale entre AO et SI est essentielle. Nous avons effectué une étude de cas longitudinale en temps réel sur deux ans d'une fusion-acquisition entre deux sociétés françaises cotées. Notre étude met en évidence le processus multi-étapes de l'intégration postfusion, en analysant comment la nouvelle organisation est passée d’une phase d'absorption à une symbiose pendant la phase d’intégration post-fusion. Nous soulignons que l'intégration symbiotique n'a pas été choisie au cours de la période de pré-fusion, mais est devenue nécessaire, compte tenu de l'interdépendance croissante entre les deux organisations.
FACTORS INFLUENCING ADOPTION OF E-PROCUREMENT IN HUMANITARIAN ORGANIZATIONS IN KENYA: A CASE OF NORWEGIAN REFUGEE COUNCIL – KAKUMA REFUGEE CAMP

: Traditionally businesses used paper based systems but now this is being surpassed by automated systems. Businesses processes are evolving with the acceptance of e-commerce concepts that applies ICT to expedite business processes. This has led to emergence of e-procurement as part of the innovations providing solutions through the internet platform and over time it has been widely accepted by diverse sectors globally. From the earlier years since the introduction of computers, the objective of procurement has not been achieved though. Several studies have been conducted out on e-procurement in their study of factors affecting performance of procurement in humanitarian relief organization’ information technology, which have recognized there is a need to invest in information systems specifically e-procurement in their purchasing units to ensure that the purchasing processes are enhanced towards assisting service delivery in those organization. This study sought to understand why the degree of adopting e-procurement systems has stood considerably lesser than the opportunity offered by the market especially in humanitarian organizations. Previous studies have revealed that there has been insufficient proof on the recognition of e-procurement economic benefits. This study examined the factors influencing the implementation of e-procurement within the humanitarian organizations in Kenya. The study sought to examine the effect of organizational factors, environmental factors, technological factors and management support factors on the adoption of e-procurement. Random sampling was engaged as a survey approach ensuring representativeness. Data analysis through both quantitative and qualitative techniques were applied on data collected To facilitate examining of correlation/relationships among variables of interest regressive analysis was used as well as descriptive statistics. The major findings of the study indicated that management factors had the most influence on the e-procurement implementation, followed by environmental factors, technological factors then organizational factors respectively. The study showed that, budget allocation, staff training & development, vendors support and organization policy reinforcement in ICT application, are essential to effective e-procurement adoption and therefore should be given due consideration. The study findings will assist Humanitarian aid managers to understand and appreciate the importance of e-procurement in organization
Disentangeling Political Instability: Concepts and Measurement

Existing measures of political instability focus on a myriad of indicators ranging from number of coups or assassination attempts, leadership changes, government duration, and outright regime changes. These substantial discrepancies are sometimes due to diﬀering understandings of the concept of instability, but also to periodic concept-measure inconsistency. Moreover, there has not been a substantial debate in the literature on what the concept of political instability should really entail. In this paper, I survey the typical understandings represented in the literature, and thereafter propose a two-dimensional structure of political instability to systematize our understanding of what that concept entails. The two dimensions put forth are i) the minimalist-maximalist continuum, capturing the extent of the concept deﬁnitions, and ii) the leader centric-regime centric continuum, capturing whether the focal point of a given understanding of instability is based on leadership or complete regimes. Thereafter, I propose a four-ﬁeld typology to guide measurement choices. The central idea guid-ing this piece is that a clear typology of political instability is a valuable tool for making informed conceptual choices on which understanding of the term to use, and thereby an equally valuable tool for making both informed and consistent measurement choices. We cannot be judges of good measurement, without knowing on which concept’s grounds to base that judgement. After classifying some prominent studies’ conceptualizations in the proposed typology, I use a construct-validation framework to assess the consistency of the measures and conclude that a call for better and more concept-speciﬁc measurement is in order.
Complexities Associated with User-generated Book Reviews in Digital Libraries: Temporal, Cultural, and Political Case Studies

While digital libraries (DL) have made large-scale collections of digitized books increasingly available to researchers [31, 67], there remains a dearth of similar data provisions or infrastructure for computational studies of the consumption and reception of books. In the last two decades, user-generated book reviews on social media have opened up unprecedented research possibilities for humanities and social sciences (HSS) scholars who are interested in book reception. However, limitations and gaps have emerged from existing DH research which utilize social media data for answering HSS questions. To shed light on the under-investigated features of user-generated book reviews and the challenges they might pose to scholarly research, we conducted three exemplar cases studies: (1) a longitudinal analysis for profiling the temporal changes of ratings and popularity of 552 books across ten years; (2) a cross-cultural comparison of book ratings of the same 538 books across two platforms; and, (3) a classification experiment on 20,000 sponsored and non-sponsored books reviews. Correspondingly, our research reveals the real-world complexities and under-investigated features of user-generated book reviews in three dimensions: the transience of book ratings and popularity (temporal dimension), the cross-cultural differences in reading interests and book reception (cultural dimension), and the user power dynamics behind the publicly accessible reviews (“political” dimension). Our case studies also demonstrate the challenges posed by user-generated book reviews’ real-world complexities to their scholarly usage and propose solutions to these challenges. We conclude that DL stakeholders and scholars working with user-generated book reviews should look into these under-investigated features and real-world challenges to evaluate and improve the scholarly usability and interpretability of their data. CCS CONCEPTS • Information systems $\rightarrow$ Digital libraries and archives;. Applied computing $\rightarrow$ Digital libraries and archives.
Evolving Neural Networks in NPCs in Video Games

This paper will look at how evolving artiﬁcial neural networks can be used to advance and enhance game play. We will look at neuroevolution in recent video games and how it can be applied to video games from the past. Also, we discuss expanded concepts of Neuroevolution of Augmenting Topologies (NEAT) and how evolving neural networks are applied to video games.
4.0. A Review on the properties and applications of biodegradable

https://doi.org/10.30574/gscarr.2021. 9.1. 0218 Abstract Biodegradable polymers have become one of the major discussable matters and considered as the most viable alternative to the traditional plastic materials among the researchers in the modern world. To keep the environmental issues in mind, innovation of environment-friendly products for our daily usage the utilization of degradable materials is increasing at a high rate. The modern world wants sustainable products which will not bring about any harm to the environment. Most of the common sustainable products are made from plastics but the main drawback of using these products is they are resistant to degradation which is a great threat to our environment. After the end of our usage, this material can sustain for a long time without any degradation which causes a supreme level of loss to our environment. The materials which are not biodegradable cause great pollution especially soil pollution. So, to protect the environment from the ruthless ridicule of pollution it has become a crying need for us to use biodegradable materials as a viable alternative to plastics. As a result, researchers are investing their time into modifying the biodegradable materials incorporated with the most common being starch and fiber extracted from various types of plants that can be easily degraded in the environment. Biodegradable materials contain almost all the properties which are suitable for our environment. Already these materials have been using in several sectors and showing their applications for their friendly properties. This paper focused on the properties and application area of biodegradable properties in
Increase in severe acute hepatitis cases of unknown aetiology in children

Summary An increase in severe acute hepatitis cases of unknown aetiology among previously healthy children was first reported by the United Kingdom (UK) to the World Health Organization’s International Health Regulations (IHR) notification system on 5 April 2022 (testing had excluded viral hepatitis types A, B, C, D and E and other known causes of acute hepatitis). Following this alert, the United States and several European Union, European Economic Area (EU/EEA) and other countries have reported suspected cases. As of 20 April 2022, 111 cases had been reported from the UK, and as of 27 April 2022 approximately 55 probable and confirmed cases have been reported from 12 EU/EEA countries. An additional 12 cases have been reported from the United States (US), 12 from Israel, and one from Japan. The clinical picture is of severe acute hepatitis requiring hospitalisation with jaundice and markedly elevated liver transaminases. In most cases to date, the onset of jaundice was preceded by a gastrointestinal illness with vomiting, diarrhoea, and nausea. Information on the outcome of the cases is still being collected. So far, most patients for whom information is available have recovered, but a number have progressed to acute liver failure and required liver transplantation. Detailed epidemiological and laboratory investigations of the cases are still ongoing to help determine the underlying aetiology. Cases have been tested for a range of different infectious causes, and the most common pathogens found were adenovirus and SARS-CoV-2. In England and Scotland, 75.5% and 50% of cases respectively tested positive for adenovirus. Subtyping of 11 cases from the UK investigation found that these were all type 41F, which is the same subtype identified among several of the cases reported from the US. subtle, especially in infants. Bone marrow failure occurs in a few children with ALF, ranging from mild pancytopenia to aplastic anaemia [16]. Without liver transplantation, mortality in children with ALF is very high. In up to 50% of ALF cases in children, the cause cannot be identified, and they are classified as indeterminate [17]. The treatment of indeterminate ALF cases is general supportive measures and liver transplantation.
REDUCED CONVOLUTIONAL NEURAL NETWORKS FOR IMAGE RECOGNITION AND OBJECT DETECTION

Computer Vision is a thriving field increasingly exploited in several scientific and engineering contexts in order to solve complex tasks such as the recognition and detection of objects inside pictures. A possible approach to deal with these problems is represented by Convolutional Neural Networks (CNNs), a deep learning algorithm which is able to distinguish the different features of objects thanks to its deep architecture. If on the one hand this deep and complex structure manages to solve difficult tasks, on the other it leads to a highly number of parameters that needs to be calibrated during the training phase. When it comes to practical applications, especially in industries, several issues may arise, since the aforementioned networks may need to operate in embedded systems with limited hardware. The resulting memory constraints have led to the creation of a reduction strategy for the development of a reduced version of an Artificial Neural Network and in particular of a Convolutional Neural Network. In our work [2] we propose an extension of [1] for dimensionality reduction of CNNs by developing a reduction technique based on methods widely used in the context of Reduced Order Modeling, as Proper Orthogonal Decomposition (POD) and Active Subspaces (AS). The reduced network is obtained by splitting the original one in two different nets connected by the reduction technique: the first one obtained by retaining a certain number of layers of the original CNN and a second one that deals with the classification of the features extracted by the previous part. We finally provide the numerical results obtained by applying such method to VGG-16 for the problem of image recognition and to SSD-300 for the problem of object detection. In particular we compare the final outcome of the original net with that of its reduced version in terms of final accuracy, memory allocation, speed of the procedure.
Managing the Electronic Government: From Vision to Practice

This book provides an insight into the possibilities that so-called "Electronic Government" has to offer. It demonstrates the elements belonging to the concept of E-Government and acts as a point of reference for those aiming to implement it. Checklists and lists of questions enable self-assessment at local, state and federal levels, highlighting opportunities for further development. The book cannot be described as technical- programmers will not find any instructions. Instead, it is designed to act as a point of orientation for decision makers in the field of government and politics, without the need to get bogged down in technical details. Central to the book are the following questions: what is Electronic Government, what advantages does it bring to those involved with it, and how can it be introduced?
A cuboid detection algorithm with computer vision methods

In robotics and Virtual Reality, there’s a need to detect and understand the structure of the scene. And a cuboid is a regular shape containing geometry information about the scene. With the cuboid detection results, the robot can better interact with the scene environment, even calibrate the camera. Recently, computer vision methods make it possible to have an accurate detection via end to end pipeline. In this project, we take a two-stages process: ﬁrst localizing the object and detecting vertex within the localization area.
Social Network Analysis for Consumer Behavior Prediction

This paper examines the structural qualities of Social Networks towards the identification of trends. We consider a collection of Twitter messages towards the trending of technologically-related topics. For each individual topic, network cohesiveness is explored over time. We demonstrate that structural qualities reflecting community dynamics can provide insight to the prediction of long term trends. The goal of this work is to lend insight to the characterization of consumer behavior, particularly in the area of technology forecasting.