Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative inquiry into the axiom of business relationship management: insights from Japanese and Australian manufacturers

The Industrial Marketing and Purchasing (IMP) Group researchers have generated rich account of an evolution of business relationship and a co-evolution of organisations through the relationship. One of their research foci has been on inter-firm adaptation-making as the driver of the evolution and co-evolution. Explicit in this research perspective is a view that a business relationship is an evolving pair of relationship commitment of those involved. This paper aims to generate cross-country, comparative insights into the axiom of business relationships based on data collected from 118 Japanese and 123 Australian leading manufacturers. It investigates the relationship between a supplier’s relationship commitment as perceived by the customer between the customer’s relationship commitment, with customer relationship satisfaction and trust as mediating variables in a multiple-group structural equation modeling framework. For the purpose, the study reported in this paper adopted the following three unique research design features. First as opposed to the conventional quantitative empirical research in the field, the study focused on business relationships in the multiple sourcing context. It examined business relationships which sample manufacturing firms had with their second or third preferred insuppliers for one of their key outsourced inputs. Second, the study modeled trust as a secondorder factor construct building on Sako’s (1992) conceptualization of trust with contractual, competence and goodwill trust. Lastly, it employed multiple-group confirmatory factor analysis (MGCFA) to compare Australian manufacturer-supplier relationship management practice with the so-called best practitioners of supplier relationship management, Japanese manufacturers. In so doing, the study explores the metric and factor variance/covariance invariance between the two sample data and tests a proposed structural model under the invariance constraints. While supporting importance of perceived supplier relationship commitment for a further evolution of the relationship from a customer manufacturer’s perspective, the study findings also shed valuable comparative insight into different structural patterns of the model constructs across the two sample groups in the multiple-sourcing context.
Original Contribution Associations of Biomarker-Calibrated Sodium and Potassium Intakes With Cardiovascular Disease Risk Among PostmenopausalWomen

Studies of the associations of sodium and potassium intakes with cardiovascular disease incidence often rely on self-reported dietary data. In the present study, self-reported intakes from postmenopausal women at 40 participating US clinical centers are calibrated using 24-hour urinary excretion measures in cohorts from the Women’s Health Initiative, with follow-up from 1993 to 2010. The incidence of hypertension was positively related to (calibrated) sodium intake and to the ratio of sodium to potassium. The sodium-to-potassium ratio was associated with cardiovascular disease incidence during an average follow-up period of 12 years. The estimated hazard ratio for a 20% increase in the sodium-to-potassium ratio was 1.13 (95% confidence interval (CI): 1.04, 1.22) for coronary heart disease, 1.20 (95% CI: 1.01, 1.42) for heart failure, and 1.11 (95% CI: 1.04, 1.19) for a composite cardiovascular disease outcome. The association with total stroke was not significant, but it was positive for ischemic stroke and inverse for hemorrhagic stroke. Aside from hemorrhagic stroke, corresponding associations of cardiovascular disease with sodium and potassium jointly were positive for sodium and inverse for potassium, although some were not statistically significant. Specifically, for coronary heart disease, the hazard ratios for 20% increases were 1.11 (95% CI: 0.95, 1.30) for sodium and 0.85 (95% CI: 0.73, 0.99) for potassium; and corresponding values for heart failure were 1.36 (95%CI: 1.02, 1.82) for sodium and 0.90 (95%CI: 0.69, 1.18) for potassium.
TheyddV-dosoperon controls bio¢lmformation through the regulationofgenes encoding curli¢bers’subunits inaerobically growingEscherichia coli

In bacteria, intracellular amounts of the signal molecule cyclic di-GMP (c-diGMP) are determined by biosynthetic enzymes, or diguanylate cyclases (DGCs), and degradative enzymes, or c-di-GMP phosphodiesterases (c-PDEs). In Escherichia coli, the production of curli fibers, an important adhesion factor, responds to c-di-GMP. The yddV-dos operon, which encodes a DGC and a c-PDE acting as a protein complex, is highly expressed at a low growth temperature and in the stationary phase, i.e. conditions that also stimulate curli production. We show that perturbations in the balance between YddV and Dos, obtained either through inactivation of the yddV gene or through overproduction of either YddV or Dos, strongly affect curli production. Both YddV and Dos proteins regulate the transcription of the csgBAC operon, which encodes curli structural subunits, while not affecting the expression of the regulatory operon csgDEFG. Consistent with the role of both YddV and Dos proteins as oxygen sensors, their effects on csgBAC gene expression were dramatically reduced in cells grown under anoxic conditions. Our results show that the yddV-dos operon plays an important role in the expression of curli-encoding genes in aerobically growing E. coli, and suggest that YddV and Dos, through their opposite activities, might finely tune curli production in response to oxygen availability.
Application to Cyber-Physical systems

Over the past several years, UAVs (unmanned aerial vehicles) and autonomous systems in general, have become hot topics, both in academia and in industry. Indeed, the opportunities for the application of such technologies are vast, with the military and the infrastructure industry being the two most eminent cases. Up until recently, autonomous systems showed quite little flexibility, their actions originating in well defined programs that executed and replicated a given task, without much ability to adapt to new conditions in the surrounding environment. However, recent advances in AI and Machine Learning have made it possible to train computer algorithms with unprecedented effectiveness, which opened the door to having cyber-physical systems that can show intelligent behaviour and decision-making capabilities. Using simulated environments, one is now able to train such systems to exhibit decent performance in tasks whose complexity stumped state-of-the-art algorithms less than a decade ago. An approach that has proved extremely successful is Reinforcement Learning (RL). In this thesis, we used it (along with other AI techniques) to train a virtual flying drone to perform two different tasks. The first one consists in having the drone fly towards a predefined object, no matter where it is placed. The second one is to have it fly in a manner that would allow for the exploration of an unknown environment. We were able to combine both tasks: to find and head towards a specific target within an unknown environment, by using only the relative position of the drone to its taking off point and its camera, therefore without any environment specific information. After a process of trial and error, we developed a framework for exploration on a plane, excluding the movement on the yaw axis. In order to perform such tasks with a deep Q network model we had to retrieve a depth image, the relative position of the drone and a segmented image. The results presented herein demonstrate that a drone can be trained to be reasonably performant in the aforementioned tasks. It was achieved up to 81% accuracy on an unknown test environment for the first task while achieving 98% accuracy for the training environment
University of Southern Denmark Using the Case-Crossover Design to Assess Short-Term Risks of Bleeding and Arterial Thromboembolism After Switching Between Oral Anticoagulants in a Population-Based Cohort of Patients With Atrial Fibrillation

Using nationwide Danish registries, we conducted a population-based case-crossover study evaluating the association between switching from a vitamin K antagonist (VKA) to a direct oral anticoagulant (DOAC), and vice-versa, and 30-day risks of bleeding and arterial thromboembolism in atrial fibrillation (AF) patients. The case-crossover population was identified among oral anticoagulant users during 2011-2018 (n=123,217), as AF patients with (a) a case-defining outcome and (b) an anticoagulant switch during the 180 days preceding the outcome. Odds Ratios were estimated using conditional logistic regression by comparing the occurrence of switching during the 30-day window immediately preceding the outcome to that in reference windows in the same individual 60-180 days before the outcome. The case-crossover populations for switching from VKA to DOAC and DOAC to VKA counted 1,382 and 287 cases, respectively. Switching from VKA to DOAC, but not from DOAC to VKA, was associated with an increased short-term risk of bleeding (Odds Ratio 1.42; 95%CI 1.13-1.79 and 1.06; 95%CI 0.64-1.75, respectively) and ischemic stroke (Odds Ratio 1.74; 95%CI 1.21-2.51 and 0.92; 95%CI 0.46-1.83, respectively). Our findings suggest that switching from VKA to DOAC is an intermittent risk factor of bleeding and ischemic stroke in AF patients. OR IG IN AL U NE DI TE D MA NU SC RI PT D ow naded rom http/academ ic.p.com /aje/advance/doi/10.1093/aje/kw aa135868706 by U niersity of Sothern D nm rk user on 14 Sptem er 2020
A Software Framework for Visual Analytics of Time-Oriented Data

Visual Analytics is one effective way to improve the understanding of large and complex datasets through the systematic combination of interactive visualizations and automated analysis techniques. Time-oriented data are highly relevant to many application fields of Visual Analytics but time and time-oriented data do also have a complex semantic structure involving design aspects such as granularities of time, different time primitives, and indeterminacy. Still, most existing software frameworks for visualization and Visual Analytics support only a subset of these design aspects to satisfy concrete application demands. However, for prototyping in basic research on Visual Analytics methods, a software framework is needed that supports the design aspects of time-oriented data in a systematic, theory-driven way. Tackling such need, this work investigates how a software framework can support Visual Analytics of time-oriented data in an expressive and efficient way. Its outcomes comprise substantial parts of the conceptual software architecture and the prototypical implementation of TimeBench. In particular, this work focuses on TimeBench’s data structures and import/export functions. Development was guided by three desiderata on expressiveness regarding design aspects of time-oriented data and three desiderata regarding efficiency for software developers. The software architecture and implementation were designed based on established software design patterns for visualization such as the Proxy Tuple pattern. The resulting data structures are conceptually based on two interlinked direct acyclic graphs and implemented on top of the relational data tables provided by the prefuse framework. For evaluation regarding its desiderata, the work presents the reimplementation of two complex visualization techniques and two development case studies. These results demonstrate that TimeBench is useful for Visual Analytics prototyping with a focus on time-oriented data well.
Bacteria from the citrus phylloplane can disrupt cell–cell signalling in Xanthomonas citri and reduce citrus canker disease severity

Xanthomonas citri subsp. citri (Xcc) is the causal agent of citrus canker, a disease that affects almost all types of citrus crops. Production of particular Xcc pathogenicity factors is controlled by a gene cluster rpf, which encodes elements of a cell–cell communication system called quorum sensing (QS), mediated by molecules of the diffusible signal factor (DSF) family. Interference with cell–cell signalling, also termed quorum quenching, either by signal degradation or over-production, has been suggested as a strategy to control bacterial disease. In this study, three bacterial strains were isolated from citrus leaves that displayed the ability to disrupt QS signalling in Xcc. Pathogenicity assays in sweet orange (Citrus sinensis) showed that bacteria of the genera Pseudomonas and Bacillus also have a strong ability to reduce the severity of citrus canker disease. These effects were associated with alteration in bacterial attachment and biofilm formation, factors that are known to contribute to Xcc virulence. These quorum-quenching bacteria may represent a highly valuable tool in the process of biological control and offer an alternative to the traditional copper treatment currently used to treat citrus canker disease.
Exploring the Influence of Power in the Dynamics of Customer-Supplier Coopetition in the Case of Supplier Dominance

Coopetition combines paradoxical forces: competition and cooperation. Many previous works have examined the forces driving competitors to cooperate. Little research investigates the factors driving competition, in particular the influence of power in the case of client-supplier coopetition. To fill this gap, a longitudinal case study is being conducted in the telecom sector. It concerns the coopetition between the French operator Orange and Apple its device supplier. The study shows that supplier dominance combined with low trust fosters competition in customer-supplier coopetition.
TranscriptionRequired for TLR2-Mediated Gene Are z and Atypical Protein Kinase C The Low Molecular Weight GTPase RhoA

The Rho GTPases are molecular switches that regulate many essential cellular processes, including actin dynamics, gene transcription, cell cycle progression, cell adhesion, and motility. In this study, we report that stimulation of TLR2 in human epithelial and monocytic cells leads to rapid and transient activation of RhoA. RhoA cooperated with the canonical I- (cid:2) B kinase-mediated pathway that induces the release of NF- (cid:2) B, in regulating the trans activation of the NF- (cid:2) B subunit p65/RelA by affecting Ser 311 phosphorylation, and subsequent cytokine production. Another consequence of TLR2 stimulation by bacterial derived products was the activation of atypical protein kinase C (PKC) (cid:1) and association of this protein kinase with RhoA. Inhibition of PKC (cid:1) decreased NF- (cid:2) B activation and p65/RelA trans activation without affecting I- (cid:2) B (cid:3) degradation. The observation of a transient, stimulus-dependent association of RhoA with PKC (cid:1) suggests that RhoA mediates at least partially its effect on gene transcription through atypical PKC. In contrast to previous studies, identifying Rac1-PI3K as an upstream element in TLR2-initiated response to NF- (cid:2) B, PI3K signaling was not required for RhoA or PKC (cid:1) activity. These results indicate that multiple GTPase-regulated pathways emerge from stimulated Toll receptors, controlling different aspects of NF- (cid:2) B-mediated gene transcription. The Journal of Immunology, 2004, 173: 507–514.
PHARMACOGNOSTIC STUDIES ON THE WHOLE PLANTS OF Ageratum conyzoides Linn. (ASTERACEAE)

Objective: To study detailed pharmacognostic profile of whole plant of Ageratum conyzoides Linn. (Asteraceae), known as appa grass and an important medicinal plant in the traditional medicinal system of India. Methods: Whole plants of Ageratum conyzoides Linn. were studied by macroscopy, pharmacognostic anatomy, powder analysis, quantitative microscopy, histo-chemical characters and physico-chemical standards and other methods for standardization were performed by WHO and pharmacopeia recommended methods. Results: Macroscopically, the leaves are stalked ovate, subacute, crenate with ciliate margins and 4-10cm long and 1-5cm wide, the stem are pink or greenish yellow covered with fine white hairs and flowers are purple to white, arranged in close terminal inflorescences. Fruits (achene) are easily dispersed. Roots are yellowish brown and root base nodes and internodes. Transverse section of leaf showed the presence of spongy mesophyll, vascular bundles, multicellular glandular trichomes and diacytic stomata, pericyclic fibres and calcium oxalate crystals in stem, Phelloderm and granular secretion staining pink with iodine in the Pholem parenchyma are some of the diagnostic features noted from anatomical study. Powder microscopy of whole plant revealed the presence of parenchyma with oil cells, glandular trichome, fibres and diacytic stomata. The investigations also included leaf surface data, quantitative leaf microscopy and physico chemical parameters such as ash values, extractive values, crude fibre content and loss on drying. Conclusions: The results of the study can serve as a valuable source of information and provide suitable standards for identification of A.conyzoides in future investigations and applications.
Women in Local Politics: Experiences in Mainstream Governance

There is a growing global presence of women in politics because of synergized international effort to empower women. In the Philippines, women enjoy a more-friendly political culture compared to other neighboring countries. However, women remain a minority in influencing policy and decision making as legislators and chief executives. This research focused on women political participation in male-dominated mainstream governance. Using interpretative phenomenology, the political experiences of six local women politicians (LWPs) were analyzed vis-à-vis their political history and political challenges. Based on the results, the political history of LWPs is underscored by kinship politics. Their experience as lawmakers and chief executives provide evidence that women remain a minority in political decision-making bodies, despite a womenfriendly political culture. In terms of political challenges, LWPs reveal that barriers for women participation are ideological factors, political culture, economic constraints, and inexperience. Therefore, there is a need for local initiatives (a) capacitating women who are not from political families but who have potential in political leadership, (b) intensive training for aspiring and incumbent women political leaders, and (c) strengthening women-friendly political culture to reduce gender stereotypes through awareness and sensitivity workshops. Keywords— Gender and governance, local Philippine politic, women empowerment, women political participation.
Integrated metabolic pro ling and transcriptome analysis of pigment accumulation in Lonicera japonica ower petals during colour-transition

Yan Xia Southwest University https://orcid.org/0000-0001-8239-8099 Weiwei Chen Southwest University Weibo Xiang China Three Gorges Corporation Dan Wang Southwest University Baogui Xue Southwest University Xinya Liu Southwest University Lehua Xing Southwest University Di Wu Southwest University Shuming Wang Southwest University Qigao Guo (  qgguo@126.com ) Southwest University https://orcid.org/0000-0001-9452-3483 Guolu Liang Southwest University
Actor-Resource-Activity (ARA) Model for Studying Interactive Network Branding in Business Relationships

Purpose - The purpose of this paper is to present and discuss the main constituents of Interactive Branding through the actor-resource-activity (ARA) model of business networks. Furthermore, the paper aims to add to the current business market management literature by introducing corporate branding to business network research. Design/methodology/approach - As a theoretical background the paper presents traditional ARA model of the Industrial Marketing and Purchasing (IMP) Group, with its roots in the business network studies. In the same manner, the importance of Interactive Branding for business relationship development is elaborated. Finally, ARA model has been re-introduced and conceptually discussed through the lens of Interactive Branding. Findings - The Pyramid of Interactive Branding, as a new theoretical framework, advocates the merge between business network and corporate branding literature. The actor layer of Interactive Branding pyramid is presented by individual human actors, the resource layer through their social network relationships, while activity layer is acknowledged through interactions, as strategic activities of individual actors. Originality/value - This paper is the first attempt to link one of the business network models with corporate branding. It builds understanding of the key concepts and mutuality of two distant but important business paradigms, and thus provides unique conceptual and managerial implications. Keywords Interactive Branding, human actors, social network connections, corporate branding, resources, interactions. Paper type Conceptual paper
Girma, Sourafel and Yundan, Gong and Holger, Görg and Sandra, Lancheros (2014) Estimating direct and indirect effects of foreign direct investment on firm productivity in the presence of interactions

We implement a method to estimate the direct effects of foreign-ownership on foreign firms' productivity and the indirect effects (or spillovers) from the presence of foreign-owned firms on other foreign and domestic firms' productivity in a unifying framework, taking interactions between firms into account. To do so, we relax a fundamental assumption made in empirical studies examining a direct causal effect of foreign ownership on firm productivity, namely that of no interactions between firms. Based on our approach, we are able to combine direct and indirect effects of foreign ownership and calculate the total effect of foreign firms on local productivity. Our results show that all these effects vary with the level of foreign presence within a cluster, an important finding for the academic literature and policy debate on the benefits of attracting foreign owned firms.
A MACHINE LEARNING MODEL FOR NETWORK INTRUSION DETECTION SYSTEM USING HIDDEN MARKOV MODEL.

Cyberattacks are becoming more sophisticated as attackers continuously use diverse strategies and tactics to attack target systems. To avert this impending threat, various possible solutions have been implemented and a variety of security systems keeps emerging. One of these solutions is intrusion detection systems (IDS). The challenge in developing a model that is efficient to detect intrusion is directly dependent on the features selected during the training process and also to detect known and unknown attacks. In this thesis a machine learning model is proposed based on a Hidden Markov Model. The model was trained and tested with data from the NSL KDD dataset, which was selected based on four categories of attacks. The relevant features for training were selected from the dataset based on the scores evaluated from a Laplacian model. New features were extracted from the selected features based on variance from a Principal Component Analysis to decrease the dimensionality of the dataset. K-Means Algorithm was utilized in mapping the extracted data into a new feature space for training. The proposed model produced an accuracy of 83.85% which outperformed the accuracies of the existing models built with the Support Vector Machine (SVM), Random Forest (RF), Deep Belief Network (DBN), and the Convolutional Neural Networks (CNN) which had 71.30%, 74.18%, 71.91% and 80.13% respectively.