Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis and Structural Characterization of Pyridine-2,6-dicarboxamide and Furan-2,5-dicarboxamide Derivatives

Derivatives based on pyridine-2-6- and furan-2,5-dicarboxamide scaffolds reveal numerous chemical properties and biological activities. This fact makes them an exciting research topic in supramolecular and coordination chemistry and in discovering new pharmacologically-active compounds. This work aimed to obtain a series of symmetrical pyridine-2-6- and furan-2,5-dicarboxamides through a condensation reaction of the appropriate acyl chlorides and aromatic amides. Successful syntheses were confirmed with NMR spectroscopy. We solved their crystal structures for seven compounds; two pyridine and five furan derivatives. Based on our crystallographic studies, we were able to indicate supramolecular features of the crystals under investigation. Additionally, Hirshfeld surface analysis allowed us to calculate a distribution of intermolecular contacts in the dicarboxamide crystals.
A systematic analysis of learning analytics using multi-source data in the context of Spain

ABSTRACT Learning analytics (LA) employs educational data to improve the timeliness of support for learners. Apart from technical aspects, there is a need to understand social complexities brought about by different stakeholders, so as to systematise the adoption of LA in Higher Education (HE). We present an analysis of the situation, needs and challenges of LA in the context of Spanish HE, considering managers’, teachers’ and students’ perspectives. Qualitative research is employed using recursive abstraction. Results reveal that the level of institutional adoption is low and none of the analysed institutions had an LA policy. Furthermore, only two of these institutions had an initial LA strategy. While the institutions shared some commonalities in their objectives for LA, chosen tools and adoption challenges, the distinct differences in the political contexts and institutional practices among the institutions reaffirmed that LA solutions and services cannot be implemented in the same manner. Moreover, different needs for LA and concerns are identified about its adoption among managers, students and teachers. These observations lead to our conclusion that the main challenges to implement LA in Spain are not related to technological issues but to the social and cultural issues rooted in institutions and those associated with different stakeholders.
Eustachian Valve Infective Endocarditis: A Rare Consequence of Implanted Venous Access Ports

We present a case of eustachian valve endocarditis in an elderly male who presented after removal of a central venous access port. This case report also reviews the prevalence of right sided endocarditis, diagnosis, common microorganisms, predisposing risk factors and medical management. Eustachian valve endocarditis was first described in 1986 by Edwards and from 1986 to 2017, only 37 cases have been reported— 46% of which were caused by intravenous (IV) drug use and 24% by indwelling intravenous lines. Other risk factors for the development of eustachian valve endocarditis include rheumatic heart disease, pacemaker wires and immunologic compromise. This case illustrates the importance of recognizing risk factors other than IV drug use in the pathogenesis of right-sided endocarditis, especially in cases involving the eustachian valve
Cerebral sinus thrombosis as an initial symptom of acute promyelocytic leukemia: Case report and literature review

Background: Cerebral sinus thrombosis as presentation of acute promyelocytic leukemia (AMPL) is exceptional, with only three cases registered in the literature. Case Description: A 24-year-old female patient was transferred to our center after a car accident. The patient had a witnessed generalized seizure while driving. Computerized tomography (CT) demonstrated a temporal intraparenchymal hemorrhage and CT venogram diagnosed a cerebral sinus thrombosis on the left transverse and sigmoid sinus. The patient underwent surgical evacuation of the hematoma and was treated with anticoagulation 48 h after surgery. Pancytopenia alerted of a possible hematological disorder. The patient was subsequently diagnosed with AMPL and treated with arsenic trioxide. The patient had a complete neurological recovery with no postoperative complications. Conclusion: The management of cerebral sinus thrombosis in patients with AMPL remains controversial. The previous reported cases of cerebral sinus thrombosis preceding the diagnosis of AMPL are reviewed and treatment of cerebral sinus thrombosis with anticoagulation in the setting of intraparenchymal hemorrhage and bleeding disorders is also discussed.
Compatibility and challenges in machine learning approach for structural crack assessment

Structural health monitoring and assessment (SHMA) is exceptionally essential for preserving and sustaining any mechanical structure’s service life. A successful assessment should provide reliable and resolute information to maintain the continuous performance of the structure. This information can effectively determine crack progression and its overall impact on the structural operation. However, the available sensing techniques and methods for performing SHMA generate raw measurements that require significant data processing before making any valuable predictions. Machine learning (ML) algorithms (supervised and unsupervised learning) have been extensively used for such data processing. These algorithms extract damage-sensitive features from the raw data to identify structural conditions and performance. As per the available published literature, the extraction of these features has been quite random and used by academic researchers without a suitability justification. In this paper, a comprehensive literature review is performed to emphasise the influence of damage-sensitive features on ML algorithms. The selection and suitability of these features are critically reviewed while processing raw data obtained from different materials (metals, composites and polymers). It has been found that an accurate crack prediction is only possible if the selection of damage-sensitive features and ML algorithms is performed based on available raw data and structure material type. This paper also highlights the current challenges and limitations during the mentioned sections.
Healthcare-related infections within nursing homes (NHS): A qualitative study of care practices based on a systemic approach

Background Infectious events, often related to healthcare practice, occur frequently within Nursing Homes (NHs), representing one of the main causes for morbidity, hospital admissions and mortality. The aims of this study are the analysis of care delivery problems and contributory factors of healthcare-related infections in a sample of NHs. This research could help identify organizational, technological and behavioural aspects, to implement improvement actions and reduce the impact of infections in long-term care. Methods The study is a qualitative research with a systemic approach, based on the analysis of interactions in real practice between human factors, technologies and organizational structure and processes in 7 NHs in Tuscany (Italy), through extensive and structured observations of daily practices. The collected data were analyzed by applying clinical and ergonomic competences, comparing the data collected with established safe practices. The study was conducted by a nurse and a psychologist Results From the data several problems related to infection control emerge. Buildings are often not suitable for confined spaces, room ventilation, natural light and rapid emergency response. Hand washing is not sufficient, use of antibiotics is usually not adequate. The microclimate is often not adequate, hygienic procedures are not always flawless. Staff members are in small numbers. Discussions This study highlights high risk of contracting infections related to NHs. The study shows that dedicated infection prevention guidance are needed, to develop a local plan integrated with hospital setting, customized to needs of guests and characteristics of long-term care facilities, supported by a deep understanding of daily practices.
Numerical Modeling for the Effect of Soil Type on Stability of Embankment

Dike construction has been widely used because of its potential to protect people and properties from overtopping flows. Water levels may exceed a dike crest and cause overtopping flow during high river discharge. This phenomenon has caused serious damage to the dike body due to the reduction of soil shear strength. The increase of water content within particles and its relationship with the development of breach channel failure in downstream and upstream slopes are affected by a series of geotechnical and hydraulic aspects. Transient seepage and slope stability analyses (FOS) were performed in this study using 2D finite element methods and time-history measurements under the effect of sandy and very silty sand soils. The numerical model of SLIDE 2018 was limited by its inability to incorporate all physical processes governing an overtopping breach failure. Numerical analyses were performed to simulate the development of pore pressures and water content at six positions in the dike’s upstream and downstream slopes in physical experimental tests using the van Genuchten Equation and the limit equilibrium method. The numerical results revealed that fine particles increase the pore water pressure and reduce the FOS. Appropriate dike design and maintenance are dependent on surrounding hydraulic conditions, dimensions, and soil types. Non-cohesive materials with fine particles were preferable. Doi: 10.28991/CEJ-SP2021-07-04 Full Text: PDF
Finding Stars From Fireworks: Improving Non-Cooperative Iris Tracking

We revisit the problem of iris tracking with RGB cameras, aiming to obtain iris contours from captured images of eyes. We find the reason that limits the performance of the state-of-the-art method in more general non-cooperative environments, which prohibits a wider adoption of this useful technique in practice. We believe that because the iris boundary could be inherently unclear and blocked, as its pixels occupy only an extremely limited percentage of those on the entire image of the eye, similar to the stars hidden in fireworks, we should not treat the boundary pixels as one class to conduct end-to-end recognition directly. Thus, we propose to learn features from iris and sclera regions first, and then leverage entropy to sketch the thin and sharp iris boundary pixels, where we can trace more precise parameterized iris contours. In this work, we also collect a new dataset by smartphone with 22 K images of eyes from video clips. We annotate a subset of 2 K images, so that label propagation can be applied to further enhance the system performance. Extensive experiments over both public and our own datasets show that our method outperforms the state-of-the-art method. The results also indicate that our method can improve the coarsely labeled data to enhance the iris contour’s accuracy and support the downstream application better than the prior method.
A Hybrid Microfluidic Electronic Sensing Platform for Life Science Applications

This paper presents a novel hybrid microfluidic electronic sensing platform, featuring an electronic sensor incorporated with a microfluidic structure for life science applications. This sensor with a large sensing area of 0.7 mm2 is implemented through a foundry process called Open-Gate Junction FET (OG-JFET). The proposed OG-JFET sensor with a back gate enables the charge by directly introducing the biological and chemical samples on the top of the device. This paper puts forward the design and implementation of a PDMS microfluidic structure integrated with an OG-JFET chip to direct the samples toward the sensing site. At the same time, the sensor’s gain is controlled with a back gate electrical voltage. Herein, we demonstrate and discuss the functionality and applicability of the proposed sensing platform using a chemical solution with different pH values. Additionally, we introduce a mathematical model to describe the charge sensitivity of the OG-JFET sensor. Based on the results, the maximum value of transconductance gain of the sensor is ~1 mA/V at Vgs = 0, which is decreased to ~0.42 mA/V at Vgs = 1, all in Vds = 5. Furthermore, the variation of the back-gate voltage from 1.0 V to 0.0 V increases the sensitivity from ~40 mV/pH to ~55 mV/pH. As per the experimental and simulation results and discussions in this paper, the proposed hybrid microfluidic OG-JFET sensor is a reliable and high-precision measurement platform for various life science and industrial applications.
Exogenous Nitric Oxide Promotes Growth and Enhances Tolerance against Drought Stress in Banana

: Drought stress is a major factor limiting crop yield. Nitric oxide (NO) is an important signal molecule that plays diverse roles in plant growth and defensive responses. However, little is known about the role of NO produced by plants under drought stress. In this study, we investigated the effects of sodium nitroprusside (SNP), an NO donor, on root growth and polyethylene glycol (PEG)-induced drought stress in bananas. Exogenous supply of NO improved root growth. We then applied a gel-based proteomic approach to investigate the root responses of bananas to deﬁne the role of NO. Ten proteins from 26 protein spots were identiﬁed using mass spectrometry. The majority of these proteins were stress-response and carbohydrate and energy metabolism-related proteins. An exposure to PEG led to a signiﬁcant reduction in plant growth. However, the application of SNP signiﬁcantly alleviated the inhibiting effect of the drought stress in a dose-dependent manner. In contrast, the cPTIO (an NO scavenger) at a concentration equimolar to the SNP reversed the effect, suggesting that the promotive effects may be due to NO itself. These ﬁndings suggest that exogenously applied NO can appreciably improve drought tolerance in bananas, afﬁrming its role in this stress-survival mechanism. gaps in our knowledge on the molecular identities and biosynthetic mechanisms of NO in plants, the determination of optimal NO dosage is indispensable. The purpose of this study was to determine the impacts of SNP on polyethylene glycol (PEG)-induced drought stress in bananas. We hypothesized that exogenous NO im- proves drought stress tolerance in bananas by promoting their root growth. To test our
Deep Learning Assist IoT Search Engine for Disaster Damage Assessment

ABSTRACT In this paper, we address the issue of disaster damage assessments using deep learning (DL) techniques. Specifically, we propose integrating DL techniques into the Internet of Things Search Engine (IoTSE) system to carry out disaster damage assessment. Our approach is to design two scenarios, Single and Complex Event Settings, to complete performance validation using four Convolutional Neural Network (CNN) models. These two scenarios are designed with three possible network services. Our experimental results confirm that all four CNN models can learn each label during the single event setting well. Whereas, with complex event settings, the CNN models have learning difficulty because multiple events have closely related labels.
Simulation and Identification of Organized Structures in Flows. Edited by J. N. SORENSEN, E. J. HOPFINGER & N. AUBRY. Kluwer, 1999. 515 pp. ISBN 0 7923 56039. NLG 395 or US$237 or £104.

This book is the Proceedings of the IUTAM Symposium on ‘‘Simulation and Identification of Organised Structures in Flows,’’ held in Lyngby, Denmark, May 25‐29, 1997. The symposium was one of those specialized symposia in the field of mechanics that the International Union of Theoretical and Applied Mechanics (IUTAM) organizes every year. The IUTAM Symposia are normally reserved to invited participants, and usually provide the state-of-the-art assessment of a particular problem by leading professionals. This book is no exception. It presents a useful overview of organized structures in fluid mechanical applications. It covers a wider range of issues than did a previous Symposium on a similar topic held in October 1992 in Poitiers, France. Selected papers from that Symposium—‘‘Eddy Structure Identification in Free Turbulent Shear Flows’’—were published in a Proceedings edited by J. P. Bonnet and M. N. Glauser (1993). Information on organized structures in flows and their interactions with flow boundaries is of considerable hydraulic engineering importance. For instance, work underway at New Zealand’s National Institute of Water and Atmospheric Research (NIWA) on periphyton (attached aquatic microalgae) interactions with turbulence is revealing significant mechanisms of mass transfer in the near-bed region. Such mechanisms appear to influence periphyton growth and losses. ADV measurements of turbulence in the NIWA outdoor ecohydraulics flume (Fig. 1) show that the appearance of periphyton on a cobble bed does not change appreciably the velocity spectra above the cobble. However, its appearance reduces the total spectral energy and generates a wide spectral peak in the region below cobble tops. Most probably, this peak is formed by penetration of sweep events into that region, ‘‘filtered’’ by the periphyton tufts. Thus, organized structures may be the main mechanism responsible for the delivery of nutrients from the outer region to the biologically active near-bed layer.
Hydroxyapatite thin films doped with Cu ions by pulsed laser deposition for application in the biomedical field

ABSTRACT Crystalline Hydroxyapatite(HA) thin films are ideal bioactive coatings that have been widely used as a coating on orthopedic metal implants. In this study, pure HA and Cu-doped HA coatings were fabricated on a steel substrate by using pulsed laser deposition. It is observed that HA doped with different concentrations of Cu ions enhanced the antibacterial properties of the Hydroxyapatite thin films. The bioactivity study showed the growth of apatite on the surface of a thin film in simulated body fluid solution (SBF) after 14 and 28 days of incubation. Characterization of the samples was performed by field emission scanning electron microscope (FESEM), energy dispersive X-ray analysis (EDX), X-ray diffraction (XRD) and Raman spectroscopy. Finally, it is suggested that the irregular and crystalline structure of fabricated films lead to the extent of the surface and enhance the cells proliferation in medical uses and biomedical applications.
A bibliometric analysis of the structure and trends of customer engagement in the context of international marketing

PurposeResearch in customer engagement (CE) has gained momentum in the last decade, thanks to its growing popularity among scholars and practitioners. The Marketing Science Institute (MSI), for instance, has been continually listing CE as part of its Tier I research priorities since 2010. CE scholars have also studied the construct in the international marketing context. Hofstede's characterization of cultures as either individualist or collectivist helped scholars explain the need for different CE strategies across countries, and the domain seems to be evolving ever since. The ever-growing interest of CE scholars in the international market and cross-cultural scenarios requires a comprehensive and scientific review of the literature. Using bibliometric analysis, this study fills this critical gap by mapping the intellectual structure of CE research in the context of international marketing and provides future research directions to scholars in this domain.Design/methodology/approachThe authors have used VOSviewer and Biblioshiny software packages to conduct a bibliometric analysis of 109 articles in the domain.FindingsThe major findings include the most influential countries, journals, articles and authors, the different research streams and their development and the future research directions in the domain. When CE is considered in an international marketing context, four broad themes emerged. The first theme is about differences in customer engagement behaviors across cultures. The second theme is about the development of CE and related constructs. The third theme relates to how brands have used CE and CBE (customer brand engagement) across different international contexts. The fourth theme is all about the conceptual and methodological support for the study of CE.Originality/valueThis study is a novel attempt at providing a comprehensive bibliometric analysis of CE research in the international marketing context, using a combination of VOSviewer and Biblioshiny software packages.
Offshoring Strategies & Governance of Global Value Chains

This paper aims to analyze the extent to which exercising offshoring options could still continue to be appropriate, given a great deal of renewed talk of economic sovereignty. To answer this question, we first look at the sources of a firm's value creation and the strategic governance of its value chain. Secondly, we examine the key success factors in offshoring strategies and their implications in terms of organization, coordination and control, as well as in terms of how expertise is transferred between partners to cope with an increasingly hostile and uncertain environment.
Components Optimization Design for Remanufacturing Based on Residual Strength

(cid:0)Currently, since the method to optimize the parameters and variables in design for remanufacturing is an issue, the concept of residual strength is given as the mapping factor in optimization design for remanufacturing. With considering the strength curve in “design, service and remanufacture” phases, and based on failure analysis, the hierarchical structure of residual strength, which consists of strength index level, strength & damage level and design information level, and the mathematics expression of residual strength are put forward. The calculation method of residual strength factor is presented. The requirement of residual strength for remanufacturing is analyzed. Meanwhile, taking residual strength factor as the remanufacturing feasibility index, the design method for remanufacturing, which has three phases “analysis, optimization and verification”, is established. An engine crankshaft is given as an instance to validate the design method, and its initial design scheme is optimized for remanufacturing.
Extended framework for Sindhi numerals OCR using gradient orientation histograms

The accuracy on MINST dataset for roman numerals is already 99.65% . However, same models showed low accuracy on Sindhi numerals. It is because Sindhi numerals have high correlation between the shapes of the numerals. In this paper, correlation based template matching is used to analyze the shape ambiguity by identifying the dominant false positives (FP) and false negatives (FN) for every numeral. Furthermore, the Gradients Histogram Orientation (GOH) features are used to improve the accuracy of existing classifiers by image-to-image matching. The classical OCR using simple binary features are not sufficient to address the problems of shape ambiguity in Sindhi numerals, i.e., the shape of digits 2, , and 3, , are very similar. The raw pixel values are used as features for the classification in the first stage. In second stage, the input image is matched with the dominant FP and FN of the predicted class, and the final decision is made by the image-to-image matching based on GOH features. Decision based on image to image matching with dominant FP and FN increase the accuracy of the classifier. Support vector machine (SVM), K-nearest neighbor, and template based matching classifiers are used. The proposed extension substantially improves the accuracy of all mentioned classifiers.