Miracle-dz/UniFAR-FTUs huggingface dataset:
ffi cient Data-Centric Routing in Wireless Sensor Networks ∗

Incorporating sensor nodes with data aggregation capability to transmit less data flow in wireless sensor networks could reduce the total energy consumption. This calls for the efficient and effective datacentric routing algorithm to facilitate this advantage. In the first part of this paper, we model the data-centric routing problem by rigorous mixed integer and linear mathematical formulation, where the objective function is to minimize the total transmission cost subject to multicast tree constraints. With the advancement of sensor network technology, sensor nodes with configurable transmission radius capability could further reduce energy consumption. The second part of this paper considers the transmission radius assignment of each sensor node and the data-centric routing assignment jointly. The objective function is to minimize the total power consumption together with consideration of construction of a data aggregation tree and sensor node transmission radius assignment. The solution approach is based on Lagrangean relaxation in conjunction with the novel optimization-based heuristics. From the computational experiments, it is shown that the proposed algorithms calculate better solution than other existing heuristics with improvement ratio up to 169% and 59% with respect to fixed transmission radius and configurable transmission radius for network with 300 random generated nodes. key words: energy saving, data aggregation, data-centric routing, Lagrangean relaxation, wireless sensor networks
Sorbitol and cellulose derivatives as gelling agents

Introduction Thickeners and gelling agents in the mixtures of organic solvents and water solutions are widely applied in many branches of industry thanks to their ability to provide the products with the desired utility features e.g. consistency, viscosity or adhesion. The selection of the substance which can guarantee the intended effect depends, first of all, on the character of the ingredients contained in the final product. The properties resulting directly from the chemical structure of the substance used are connected with the strength of interaction with other ingredients of the mixture and they are responsible for the creation and maintenance of the intended product consistence. This property becomes especially significant in the case of mixtures containing the ingredients which, to a large degree, do not blend with each other, and which are of both hydrophilic and hydrophobic type. A situation in which the ingredients vary so much from one another as far as their character is concerned, is frequent in the composition of cosmetic and household chemical products. Among other situations, this feature often concerns the preparations used for the removal of varnish coats. In the described systems, an appropriate form of the preparation may be obtained when sorbitol derivatives [1, 2] or cellulose derivatives are applied [3,4]. In the case of sorbitol derivatives, some beneficial properties are manifested by 1,3:2,4-di-Obenzylidene-D-sorbitol (D-DBS) in connection with organic solvents. The structure of gels obtained with this substance, varies depending on the polarity of the solvent used. This structure also depends on the solvent’s concentration in the system [5÷7]. Cellulose derivatives, in turn, create hydrogels in water solutions and systems containing sufficient quantity of the water phase. The gels obtained in such preparations are stable in the pH scope from 4 to 10. A characteristic property of such systems is that the presence of polyvalent cations enables cross-linkage and the creation of permanent gels [3].
Characterization of Graphene with the NanoWizard ® 3 AFM Introduction

Andre Geim, Konstantin Novoselov and collaborators were the first to publish the production and electrical characterization of single layer graphene, a discovery which was credited with the Nobel Prize in physics in 2010. They produced these 2D crystal structures by mechanical exfoliation of graphite with adhesive tape [1]. Single or few-layer sheets were then transferred onto oxidized silicon substrate for electrical investigation. In 2013, a group of researchers around Prof. Jari Kinaret were granted a one-billion-euro grant from the European Union for the research on graphene and related materials [2][3]. This large-scale project is aimed to develop new applications, foster scientific advance and lay the foundation for future innovations. Given this increased interest in graphene research we provide some of the measurement results on graphene that were produced with the JPK NanoWizard 3 AFM system. Graphene can be produced by micromechanical cleavage as used by Novoselov and Geim to produce graphene samples for fundamental research. Commercial graphene can be prepared by liquid phase exfoliation, mostly involving graphite oxide. Another common method is the epitaxial growth on silicon carbide or other materials. Further production techniques involve anodic bonding, photoexfoliation, chemical vapor deposition, molecular beam epitaxy and chemical synthesis. AFM is most suited for the characterization of graphene due to its high spatial resolution and the various modes that allow probing different physical properties. The height image gives an overview about the roughness of the graphene layers and the underlying substrate. The combination with Raman spectroscopy or tipenhanced Raman spectroscopy (TERS) allows the
Incomplete APOBEC 3 G / F Neutralization by HIV-1 Vif Mutants Facilitates the Genetic Evolution from CCR 5 to CXCR 4 Usage

Claudia Alteri, Matteo Surdo, Maria Concetta Bellocchi, Patrizia Saccomandi, Fabio Continenza, Daniele Armenia, Lucia Parrotta, Luca Carioti, Giosuè Costa, Slim Fourati, Fabiola Di Santo, Rossana Scutari, Silvia Barbaliscia, Valentina Fedele, Stefania Carta, Emanuela Balestra, Stefano Alcaro, Anne Genevieve Marcelin, Vincent Calvez, Francesca Ceccherini-Silberstein, Anna Artese, Carlo Federico Perno, Valentina Svicher University of Rome “Tor Vergata,” Department of Experimental Medicine and Surgery, Rome, Italy; INMI L. Spallanzani, Rome, Italy; Università Magna Graecia di Catanzaro, Dipartimento di Scienze della Salute, Campus Universitario, Catanzaro, Italy; Department of Virology, Hospital “Pitie Salpietrere,” Paris, France
Infants di ff erentially update their internal models of a dynamic environment

Unexpected events provide us with opportunities for learning about what to expect from the world around us. Using a saccadic-planning paradigm, we investigated whether and how infants and adults represent the statistics of a changing environment (i.e. build an internal model of the environment). Participants observed differently colored bees that appeared at an unexpected location every few trials. The color cues indicated whether the subsequent bees would appear at this new location (i.e. update trials) or at the same location as previously (i.e. no-update trials). Infants learned the predictive value of the color cues and updated their internal models when necessary. Unlike infants, adults had a tendency to update their models each time they observed a change in the structure. We argue that infants are open to learning from current evidence due to being less influenced by their prior knowledge. This is an advantageous learning strategy to form accurate representations in dynamic environments, which is fundamental for successful adaptation.
Infectious disease exposures and outbreaks at a South African neonatal unit with review of neonatal outbreak epidemiology in Africa

Background: Hospitalized neonates are vulnerable to infection, with pathogen exposures occurring in utero, intrapartum, and postnatally. African neonatal units are at high risk of outbreaks owing to overcrowding, understaffing, and shared equipment. Methods: Neonatal outbreaks attended by the paediatric infectious diseases and infection prevention (IP) teams at Tygerberg Children’s Hospital, Cape Town (May 1, 2008 to April 30, 2016) are described, pathogens, outbreak size, mortality, source, and outbreak control measures. Neonatal outbreaks reported from Africa (January 1, 1996 to January 1, 2016) were reviewed to contextualize the authors’ experience within the published literature from the region. Results: Thirteen outbreaks affecting 148 babies (11 deaths; 7% mortality) over an 8-year period were documented, with pathogens including rotavirus, influenza virus, measles virus, and multidrug-resistant bacteria (Serratia marcescens,Acinetobacter baumannii, methicillin-resistant Staphylococcus aureus, and vancomycin-resistant enterococci). Although the infection source was seldom identified, most outbreaks were associated with breaches in IP practices. Stringent transmission-based precautions, staff/parent education, and changes to clinical practices contained the outbreaks. From the African neonatal literature, 20 outbreaks affecting 524 babies (177 deaths; 34% mortality) were identified; 50% of outbreaks were caused by extended-spectrum b-lactamase-producing Klebsiella pneumoniae. Conclusions: Outbreaks in hospitalized African neonates are frequent but under-reported, with high mortality and a predominance of Gram-negative bacteria. Breaches in IP practice are commonly implicated, with the outbreak source confirmed in less than 50% of cases. Programmes to improve IP practice and address antimicrobial resistance in African neonatal units are urgently required. © 2017 The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).
EasyChair Preprint No 1331 An Investigation into Usability of Big Data Analytics in the Management of Type 2 Diabetes Mellitus

The global prevalence of Type 2 Diabetes Mellitus (T2DM) has been on the rise over the last four decades and is expected to rise further in the future. Big Data applications such as Artificial Intelligence (AI) and Machine learning (ML) are increasingly being used in the healthcare industry to manage various aspects of patient care. Researchers have so far studied the adoption of technologies including AI and ML in various contexts using technology adoption frameworks in the information systems (IS) domain, where the usability of technology is just viewed as one factor. Although, researches on technology adoption models in the IS domain has indicated that usability has a significant influence on the adoption of a technology, it appears that there are limited attempts made to study the factors influencing the usability of big data applications such as AI and ML for the management of T2DM. Since usability not only a factor that impacts the adoption of a technology, but also determines the outcomes of the management process, there is a need to understand the factors that influence the usability of a big data analytics application for the management of T2DM, this research aims to identify and analyse the factors influencing the usability of big data applications such as AI and ML in management of T2DM. The research is designed as mixed method research with qualitative research undertaken first to confirm the conceptualised research model followed by quantitative research to genaralise the model. This research would contribute to the academic literature in the areas of Information Systems Quality, Human-Computer Interaction (HCI), design and development big data applications, usability engineering, user experience (UX), and usability measurement model. The contributions from this research would also benefit the healthcare industry, predominantly that part of an industry that is directly involved in the management of T2DM and indirectly involved in the management of comorbidities on T2DM. The learnings from this research can also be extended to the management of many other chronic conditions and many other contexts.
Building theory on the negotiation capability of the firm: evidence from Ryanair

Purpose In an attempt to build upon existing theory, this paper aims to investigate the potentially reciprocal relationship between negotiation and strategy, and strive to contribute toward a better understanding of the ways in which organizations negotiate. Design/methodology/approach Built upon the integration of two different bodies of literature, negotiation and strategy, and on the analysis of the case of Ryanair, this paper argues for an integrated approach to negotiation and organizational capabilities. Findings The case study allows for a clearer understanding of how negotiation capability can play a significant role in supporting the creation and sustainment of competitive advantage, even under unfavorable industry settings. Originality/value This paper contributes to theoretical development by offering new and insightful explanations of firms’ behavior, moving beyond the classic interpretation of industry dynamics, such as bargaining power. This study has implications for both practice and research, as it offers a better and more holistic understanding of the strategy-making process and the foundations of its success.
Two Step Joint Model for Drug Drug Interaction Extraction

When patients need to take medicine, particularly taking more than one kind of drug simultaneously, they should be alarmed that there possibly exists drug-drug interaction. Interaction between drugs may have a negative impact on patients or even cause death. Generally, drugs that conflict with a specific drug (or label drug) are usually described in its drug label or package insert. Since more and more new drug products come into the market, it is difficult to collect such information by manual. We take part in the Drug-Drug Interaction (DDI) Extraction from Drug Labels challenge of Text Analysis Conference (TAC) 2018, choosing task1 and task2 to automatically extract DDI related mentions and DDI relations respectively. Instead of regarding task1 as named entity recognition (NER) task and regarding task2 as relation extraction (RE) task then solving it in a pipeline, we propose a two step joint model to detect DDI and it's related mentions jointly. A sequence tagging system (CNN-GRU encoder-decoder) finds precipitants first and search its fine-grained Trigger and determine the DDI for each precipitant in the second step. Moreover, a rule based model is built to determine the sub-type for pharmacokinetic interation. Our system achieved best result in both task1 and task2. F-measure reaches 0.46 in task1 and 0.40 in task2.
Graduation Plan

e ? Study human beings in their context. Focus on the details of everyday life to make a qualified design. Living in an elderly home (‘t Nieuwe Kampje in Loenen aan de Vecht) for one week. Participation, observations, conversations and interviews with residents, caregivers, fammily and other users. The observations are illustrated in sketches and storytelling, inspired by the artist Jan Rothuizen. Life in the building reminds me of a factory, the ‘ e l d e r l y f a c t o r y ’ produces passive elderly. The factory is designed as a building and runned by the factory workers, such as the garegivers and volunteers. To keep production going, fuel (food) is served at fixed times. Besides general ingredients, like walkers and wheelchairs, also ingredients with a personal touch are added. At the end of the production process, all the products will have the same daily routines, passive attitude and lifestyle. and because I not in the position think for the target group. I will use the outcomes (opinions and ideas) as a base for the design.
An Efficient Adaptive Architecture for Multi-pattern Matching

Multi-pattern matching is a core technique of many applications. However, many of the existing algorithms cannot efficiently deal with large pattern sets or pattern sets with very short patterns. To address these issues, in this paper, an adaptive architecture for multi-pattern matching (AAMPM), which is based on a new data structure called adaptive matching tree (AMT), is proposed. In particular, each tree node in AMT saves only some pattern fragments of the whole pattern set, and the inner data structure of each tree node is adaptively chosen according to the features of those pattern fragments. Due to this adaptivity, each tree node can take as little memory as possible, additionally, matching the text fragments with the pattern fragments in the tree nodes can be very efficient. Based on AMT, AAMPM adopts an effective approach to search patterns in the text string. The experimental results show that, AAMPM has a strong robustness on pattern sets with short patterns. Moreover, due to the good scalability of AMT, AAMPM offers an excellent support for large pattern sets.
carcinogen benzo [ a ] pyrene : effects in Trp 53 ( + / + ) , Trp 53 ( + /-) and Trp 53 (-/-) mice

The tumour suppressor p53 is one of the most important cancer genes. Previous findings have shown that p53 expression can influence DNA adduct formation of the environmental carcinogen benzo[a]pyrene (BaP) in human cells, indicating a role for p53 in the cytochrome P450 (CYP) 1A1-mediated biotransformation of BaP in vitro. We investigated the potential role of p53 in xenobiotic metabolism in vivo by treating Trp53(+/+), Trp53(+/-) and Trp53(/-) mice with BaP. BaP-DNA adduct levels, as measured by 32 P-postlabelling analysis, were significantly higher in liver and kidney of Trp53(-/-) mice than Trp53(+/+) mice. Complementarily, significantly higher amounts of BaP metabolites were also formed ex vivo in hepatic microsomes from BaP-pretreated Trp53(-/-) mice. Bypass of the need for metabolic activation by treating mice with BaP-7,8-dihydrodiol-9,10-epoxide (BPDE) resulted in similar adduct levels in liver and kidney in all mouse lines confirming that the influence of p53 is on the biotransformation of the parent compound. Higher BaP-DNA adduct levels in the livers of Trp53(-/-) mice correlated with higher Cyp1a protein levels and increased Cyp1a enzyme activity in these animals. Our study demonstrates a role for p53 in the metabolism of BaP in vivo confirming previous in-vitro results on a novel role for p53 in CYP1A1-mediated BaP metabolism. However, our results also suggest that the mechanisms involved in the altered expression and activity of the CYP1A1 enzyme by p53 in vitro and in vivo are different.
The Psychotherapeutic Alliance and Change : A discussion on the healing aspects in a psychotherapeutic relationship

3 Introduction . 5 The many levels in a psychotherapeutic relationship . 5 Therapist-client power differences in the therapeut ic alliance . 6 Breuer & Freud’s pioneering of the concept of the p sychotherapeutic alliance . 9 What lies within the therapist-client alliance? 12 Relationship between making analysis and contacting . 13 Analysis-making is subject to the therapist’s own e xperience. 13 Contact & inter-subjectivity & the definition of th e self through relationships . 15 Internalization of the social environment and defen ce . 18 Working through client’s defense mechanisms . 19 Freud’s theory of repression . 20 The present moment in the therapeutic alliance . 21 Process vs. content in the psychotherapeutic dialog ue . 22 Reich’s case examples . 24 Reich’s advice on avoiding “chaotic situations” . 28 Unconscious feelings and countertransference within the alliance . 29 Awareness of therapist’s countertransference as sup port to the alliance . 30 Self-awareness & the phenomenological attitude . 33 Understanding vs. analyzing in psychotherapy . 34 Consequence of not understanding . 34 Hermeneutic circle of understanding . 36 The psychotherapeutic dialogue . 38 What’s behind the transforming power of dialogue . 39 What empathy may not be . 40 The I-Thou moment in practice . 42 Recent Significant Literature on Psychotherapeutic Process Change . 43 Back to the case of Anna O. 45 The alliance and professional ethics . 46 The client’s responsibility . 47 Conclusion. 4 9 Bibliography . 5 1
Potential for PRIM based classification: A literature review

(12 font) This paper provides a critical review of Patient Rule Induction Method (PRIM) and other bump hunting algorithms and their applications. We also give an overview about interpretability in several key supervised data mining algorithms. This allows for exploring the potential for using PRIM, with its interpretation capability, as a core technology towards building a highly accurate and interpretable classifier in a mixed data space.
PRODUCTION OF TRANSGENIC BRASSICA JUNCEA WITH THE SYNTHETIC CHITINASE GENE ( NIC ) CONFERRING RESISTANCE TO ALTERNARIA BRASSICICOLA

Brassica juncea is an important oil seed crop throughout the world. The demand and cultivation of oil seed crops has gained importance due to rapid increase in world population and industrialization. Fungal diseases pose a great threat to Brassica productivity worldwide. Absence of resistance genes against fungal infection within crossable germplasms of this crop necessitates deployment of genetic engineering approaches to produce transgenic plants with resistance against fungal infections. In the current study, hypocotyls and cotyledons of Brassica juncea, used as explants, were transformed with Agrobacterium tumefacien strain EHA101 harboring binary vector pEKB/NIC containing synthetic chitinase gene (NIC), an antifungal gene under the control of cauliflower mosaic virus promoter (CaMV35S). Bar genes and nptII gene were used as selectable markers. Presence of chitinase gene in trangenic lines was confirmed by PCR and southern blotting analysis. Effect of the extracted proteins from non-transgenic and transgenic lines was observed on the growth of Alternaria brassicicola, a common disease causing pathogen in brassica crop. In comparison to non-transgenic control lines, the leaf tissue extracts of the transgenic lines showed considerable resistance and antifungal activity against A. brassicicola. The antifungal activity in transgenic lines was observed as corresponding to the transgene copy number.
2 Routes of Transmission of Primary EBV Infection

Infectious mononucleosis is a clinical entity characterized by sore throat, cervical lymph node enlargement, fatigue and fever most often seen in adolescents and young adults and lasting several weeks. It can be caused by a number of pathogens, but this chapter only discusses infectious mononucleosis due to primary Epstein-Barr virus (EBV) infection. EBV is a γ-herpesvirus that infects at least 90% of the population worldwide. The virus is spread by intimate oral contact among teenagers and young adults. How preadolescents acquire the virus is not known. A typical clinical picture with a positive heterophile test is usually sufficient to make the diagnosis, but heterophile antibodies are not specific and do not develop in some patients. EBV-specific antibody profiles are the best choice for staging EBV infection. In addition to causing acute illness, there can also be long-term consequences as the result of acquisition of the virus. Several EBV related illnesses occur including certain cancers and autoimmune diseases, as well as complications of primary immunodeficiency in persons with the certain genetic mutations. A major obstacle to understanding these sequelae has been the lack of an efficient animal model for EBV infection, although progress in primate and mouse models has recently been made. Key future challenges are to develop protective vaccines and effective treatment regimens.