Miracle-dz/UniFAR-FTUs huggingface dataset:
3D Geo-Information Innovation in Europe’s Public Mapping Agencies: A Public Value Perspective

Intensifying and increasingly complex physical developments under, on, and above ground, as well as the speed and accessibility of digital innovation, is resulting in growing interest in public sector investment in 3D geo-information. In Europe, a consortium of 11 public mapping agencies (PMAs) recently undertook a cost-benefit analysis for pursuing adoption of 3D geo-information. However, broader public management literature has shown that while economic value is vital for justifying public investment, it is not the only driving factor and that the creation of public value is crucially and equally significant as it conveys social and political legitimacy. Using a public value perspective, this paper aims to re-examine the data collected by the consortium of PMAs. Content analysis of the qualitative data provides strong examples of how 3D geo-information may potentially manifest as different types of public value across a broad public of stakeholders as well as providing evidence that such innovation would likely be politically as well as operationally viable. Nonetheless, the lack of a clear obvious need for 3D geo-information that responds to a specific societal challenge may pose an impediment to successful innovation.
Measuring the Efficiency in the Lithuanian Banking Sector: The DEA Application

The purpose of this study is to examine the efficiency of the banks in Lithuania by employing the DEA method and evaluate bank performance in a low interest rate environment. The efficiency scores were calculated with a non-parametric frontier input-oriented DEA technique with the variable returns to scale (VRS) and the constant returns to scale (CRS) assumptions. Five alternative models with different input-output combinations were developed, based on production, profitability and intermediation dimensions. The main bank profitability measure—the return on assets (ROA) ratio—was employed to validate the results obtained using the DEA method. The Lithuanian bank’s efficiency analysis based on the VRS assumption shows that better results are demonstrated by the local banks. The technical efficiency analysis based on the CRS assumption shows other results: the banks owned by the Nordic parent group and the branches have higher pure efficiency than local banks and have success at working at the right scale. Based on this, it stated that during the 2012–2016 period the larger Lithuanian banks (subsidiaries) applied a more appropriate business model than smaller (local) banks operating in Lithuania. Additionally, this research contributes to the scholarly literature in the field of determinants of bank business performance in concentrated markets dominated by foreign banks and, in particular, from one region.
Electrospinning of 100% Carboxymethyl Chitosan Nanofibers

Carboxymethyl chitosan (CMC), one of the most important chitosan derivatives, is synthesized by alkalization of chitosan, followed by carboxymethylation. CMC has higher moisture absorption and moisture retention, higher chelating and sorption abilities as well as better biological properties than chitosan. Polymeric nanofibrous mats produced through electrospinning have high specific surface area and high porosity which are beneficial for various applications. Up to present time, the electrospinning of CMC has only been possible by the addition of polymers such as polyvinyl alcohol or polyethylene oxide. The present study focuses on the electrospinning of 100% CMC. It was found that the solution of CMC (5–6%) in trifluoroacetic acid (TFA) was electrospinnable, producing nanofibers containing some beads. However, adding dichloromethane (DCM) to TFA made the electrospinning uniform, and bead-free CMC nanofibers with an average diameter of 260 nm was possible. This study shows that viscosity and surface tension of the electrospinning solution of CMC plays an important role in making CMC solution electrospinnable.
Medicinal plants for gingivitis: a review of clinical trials

Objective(s): Periodontal diseases are among prevalent oral health problems which may ultimately lead to severe complications in oral cavity. Herbal products can be designed as single or multicomponent preparations for better oral health. This study aims to review current clinical trials on the effectiveness of herbal products in gingivitis. Materials and Methods: Electronic databases, including PubMed, Scopus, ScienceDirect and Cochrane library were searched with the keywords “gingivitis” in the title/abstract and “plant/ extract/ herb” in the whole text for clinical trials on herbal treatments for gingivitis. Data were collected from 2000 until January 2018. Only papers with English full-texts were included in our study. Results: Herbal medicines in the form of dentifrice, mouth rinse, gel, and gum were assessed in gingivitis via specific indices including plaque index, bleeding index, microbial count, and biomarkers of inflammation. Pomegranate, aloe, green tea, and miswak have a large body of evidence supporting their effectiveness in gingivitis. They could act via several mechanisms such as decrease in gingival inflammation and bleeding, inhibition of dental plaque formation, and improvement in different indices of oral hygiene. Some polyherbal formulations such as triphala were also significantly effective in managing gingivitis complications. Conclusion: Our study supports the efficacy and safety of several medicinal plants for gingivitis; however, some plants do not have enough evidence due to the few number of clinical trials. Thus, future studies are mandatory for further confirmation of the efficacy of these medicinal plants.
Applications of Nickel Nanoparticles for Control of Fusarium Wilt on Lettuce and Tomato

Fusarium wilt diseases of vegetable crops are the major challenges for vegetable production. To explore alternative control measure of Fusarium wilt, antifungal activities of nickel nanoparticles were investigated for controlling two forma specials of Fusarium oxysporum, F. oxysporum f. sp. lactucae and F. oxysporum f. sp. lycopersici, on lettuce and tomato under in vitro and greenhouse conditions. Under in vitro condition, nickel nanoparticles at the concentration of 100 ppm significantly inhibited the mycelial proliferation and sporulation activities of fungal pathogens. The inhibition of mycelial growth of F. oxysporum f. sp. lactucae and F. oxysporum f. sp. lycopersici was 60.23 and 59.77%, respectively. While under greenhouse condition, nickel nanoparticles at the concentration of 50 ppm caused the highest reduction in disease severity and the reduction was 58.4% and 57.0% on lettuce and tomato, respectively. However, when the plants were inoculated with fungal pathogens before application of nickel nanoparticles, the concentration of 50 ppm was found more effective than 100 ppm of NiNPs in relation to plant health. The application of nickel nanoparticles at 100 ppm significantly retarded the plant growth as compared to application of nickel nanoparticles at 50 ppm in all combinations of treatments. So, we conclude that the application of NiNPs as antifungal agents against Fusarium will be better with concentration of 50 ppm. This study suggests that nickel nanoparticles could be used to control Fusarium wilt. However, further field studies are needed to verify their disease control efficiency and effects on soil physicochemical properties and other beneficial soil microorganisms.
Inducing a lexicon of sociolinguistic variables from code-mixed text

Sociolinguistics is often concerned with how variants of a linguistic item (e.g., nothing vs. nothin’) are used by different groups or in different situations. We introduce the task of inducing lexical variables from code-mixed text: that is, identifying equivalence pairs such as (football, fitba) along with their linguistic code (football→British, fitba→Scottish). We adapt a framework for identifying gender-biased word pairs to this new task, and present results on three different pairs of English dialects, using tweets as the code-mixed text. Our system achieves precision of over 70% for two of these three datasets, and produces useful results even without extensive parameter tuning. Our success in adapting this framework from gender to language variety suggests that it could be used to discover other types of analogous pairs as well.
Subcutaneous Panniculitis-like T-cell Lymphoma: Review of Therapies

Subcutaneous Panniculitis-like T-cell Lymphoma (SPTCL) is a rare subtype of cutaneous T-cell lymphoma derived from alpha/beta cytotoxic T-cells. It is known to follow an indolent course with a favorable prognosis. We review current therapies used to treat this rare entity in order to increase awareness about possible options. No standardized therapy for SPTL currently exists. Local radiotherapy for indolent local disease has been found successful. For indolent disease with a more generalized distribution, immunosuppressive agents as well as lowdose chemotherapy may be used. For aggressive presentations, combination chemotherapy, anthracycline-based regimens, fludarabine-based regimens, and rarely high-dose chemotherapy followed by hematopoietic stem cell transplant (SCT) with moderate success. By being aware of possible therapeutic options, a physician can recommend the most appropriate treatment for the individual.
PASSIVITY AND DISSIPATIVITY IN RESILIENT CPS DESIGN Results of Antsaklis ’ group at the University of Notre Dame 2008-2018 ISIS-2018-001

Around 2008, the Antsaklis’ research group at Notre Dame started using the energy like concept of passivity as the central concept in the design of Cyber-Physical Systems (CPS). CPS are large interconnected heterogeneous systems that may change dynamically. Using passivity and its generalization of dissipativity, the group was able to address compositionality and resilience in CPS that make it possible to preserve important properties under feedback interconnections and uncertainties quite effectively. This report is a summary of the results on Passivity and Dissipativity covering approximately the years 2008-2018. The collected results have been derived by the following PhD students and collaborators. PhD students Etika Agarwal Yang Yan Hasan Zakeri (Current student) (Current student) (Current student) Arash Rahnama Vahideh Ghanbari Meng Xia (PhD May 2018) (PhD May 2017) (PhD May 2015) Feng Zhu Michael McCourt Po Wu (PhD May 2014) (PhD May 2013) (PhD May 2013) Han Yu Eloy Garcia Tomas Estrada (PhD May 2013) (PhD May 2012) (PhD May 2009) Nicholas Kottenstette Luis Montestruque (PhD May 2007) (PhD May 2005) Collaborators Sivaranjani S. Sravan Sajja Vijay Gupta Yue Wang Shige Wang Getachew Befekadu
Multidrug resistant and most virulent Enterococcus faecium ( strain 2653 ) , isolated from hospitalized patient wound in Iran

Enterococci are parts of human normal flora and the microbial association of a variety of fermented foods and probiotics but it also cause a wide variety of diseases in human including urinary tract infection, bacteremia, endocarditis, peritonitis and wound infections. Different factors causes pathogenesis of Enterococci. In this study we aimed to describe pathogenic properties of a multidrug resistance strain of Enterococci isolated from wound of auricle and upper lip of a hospitalized female patient. Antibiotic resistant properties of this strain described by kerby-bauer and E. test method. The presence of 23srRNA, ddlE, ddlF, VanA, VanB, Esp, As, Efa, Gel, Ebp, Hyl, Ace, Cyl gene were studied by PCR.This strain had extreme resistance to all common antibiotics which are using in hospital and community acquired infections and it was completely resistance to P, AMX, A, VA, TEC, E, TE, TGC, CIP, NI, RI, C, Imp, GM antibiotics and it was just sensitive to LZD. Our isolates Enterococcus faecium (2653) also was resistant to nitrofurantoin and tigecycline. This strain harbored vanA gene and interestingly had all virulence factors including colonization and secretary factors. Our study showed this strain is a suitable model for mechanism of pathogenesis and drug resistance studies of Enterococci.
Studies on Therapeutic Value of Naturally Flavored Papaya-Mango Blended Ready-To-Serve (RTS) Beverage

Consumption of fruit and vegetables is recommended as part of a healthy diet once these are rich sources of phytochemicals as carotenoids, polyphenols, vitamins and minerals, besides presenting complex carbohydrates and fibers (Heber, 2004). Moreover, epidemiological studies have established a relationship between fruit and vegetable consumption and prevention of human diseases (Kaisoon et al., 2012). However, changes in modern life-style led consumers to decrease the intake of fresh produce (Zhou et al., 2015).
Periodic patterning using aerial image modulation with optical lithography

Abstract. Photolithography for patterns with periodicity in the illumination plane (2.5-D lithography) has seen rapid advances over the past decade, with the introduction of holographic lithography and the further development of phase-contrast and grayscale photolithography methods. However, each of these techniques suffers from substantial difficulties preventing further integration into device fabrication: a lack of parallel processing capabilities and dimension limitations. Here, we present a demonstration of controlled layer topography through modulation of both the exposure dose and exposure focal plane yielding reproducible 2.5-D patterns which are applied to the further development of plasmonic gratings. This process is entirely compatible with commercially available i-line photolithography and etch hardware, enabling a path to ready integration.
Prediction of Customer Movements in Large Tourism Industries by the Means of Process Mining

Customer movements in large tourism industries (such as public transport systems, attraction parks or ski resorts) can be understood as business processes. Their processes describe the flow of persons through the networked systems, while Information Systems log the different steps. The prediction of how large numbers of customers will behave in the near future is a complex and yet unsolved challenge. However, the possible business benefits of predictive analytics in the tourism industry are manifold. We propose to approach this task with the yet unexploited application of predictive process mining. In a prototypical use case, we work together with two major European ski resorts. We implement a predictive process mining algorithm towards the goal of predicting near future lift arrivals of skiers within the ski resort in real-time. Furthermore, we present the results of our prototypical implementation and draw conclusions for future research in the area.
A novel wireless mobile platform integrated with optical fibre sensors

This paper presents a novel design of wireless mobile platform which enables effective integration of a number of optical fibre sensors with an advanced mobile wireless sensor network (WSN) and allows for potential applications such as monitoring in remote and harsh environments and tracking, exploiting fully the advantages offered both by mobile WSN and by advanced optical fibre sensing technologies. The platform which was designed and implemented consists of an optical fibre sensor module and a smart mobile WSN module, which shows important advantages for mobile sensing and tracking and mesh networking. In this study, a fibre Bragg grating (FBG)-based temperature sensor was specially designed and integrated successfully into the optical fibre sensor module as an exemplar to investigate the performance of the integrated system based on the mobile WSN platform. The positive experimental results obtained have confirmed the functionality of the platform designed and demonstrated its capacity for real-time optical fibre sensor data monitoring, processing and wireless transmission. The successful creation of this type of wireless mobile platform with optical fibre sensors would be expected to make an important impact on many sectors, where either conventional optical sensor designs or WSNs alone cannot meet the systems requirements.
Difference in Breastfeeding Practices among Urban and Rural Mothers in Lahore , Pakistan

The objective of the study was to assess the breastfeeding practices in rural and urban nursing mothers and to evaluate the determinants of selected key indicators of breastfeeding practices in both rural and urban setting in Lahore, Pakistan. There was a need to assess the breastfeeding practices, so that the appropriate measure could be taken in order to lessen the number of the children experiencing these illnesses. A cross-sectional descriptive study was carried out on 370 mothers having up to one year old children Frequencies and percentages were computed. Exclusive breastfeeding was reported by about 40.8% of the mothers. Mostly of them were self motivated. Most of them started breastfeeding on first day. Majority of the females (59.8%) were not giving breastfeeding, mostly of them belong to urban areas and were working females. As per the analysis, it has been found that 98.6% females were from their professional and marital life. Large number of females, living in the urban areas, working for 6-8 hours a day cannot manage breastfeeding along with the work. There is a strong need for the development of policies by the government agencies to allow mothers with infants avail maternity leaves in order to provide exclusive breastfeeding to the children. Since some private organizations do not allow for long maternity leaves. Awareness campaigns should be initiated to provide necessary information about the advantages of breastfeeding and effects of not breastfeeding to the children. Breastfeeding is the process of feeding the infant with mother’s milk, either by direct nipple-baby mouth contact or by expressed breast milk. During the first two or three days watery and yellowish fluid that comes from the mammary gland differs from the regular milk and is called Colostrum. It is secreted in small amount and rich in proteins and having less fat content. And the Mature milk is whitish milk that is effectively produced from about 10 Introduction
Taming the Killer Microsecond

Modern applications require access to vast datasets at low latencies. Emerging memory technologies can enable faster access to significantly larger volumes of data than what is possible today. However, these memory technologies have a significant caveat: their random access latency falls in a range that cannot be effectively hidden using current hardware and software latency-hiding techniques–namely, the microsecond range. Finding the root cause of this "Killer Microsecond" problem, is the subject of this work. Our goal is to answer the critical question of why existing hardware and software cannot hide microsecond-level latencies, and whether drastic changes to existing platforms are necessary to utilize microsecond-latency devices effectively. We use an FPGA-based microsecond-latency device emulator, a carefully-crafted microbenchmark, and three open-source data-intensive applications to show that existing systems are indeed incapable of effectively hiding such latencies. However, after uncovering the root causes of the problem, we show that simple changes to existing systems are sufficient to support microsecond-latency devices. In particular, we show that by replacing on-demand memory accesses with prefetch requests followed by fast user-mode context switches (to increase access-level parallelism) and enlarging hardware queues that track in-flight accesses (to accommodate many parallel accesses), conventional architectures can effectively hide microsecond-level latencies, and approach the performance of DRAM-based implementations of the same applications. In other words, we show that successful usage of microsecond-level devices is not predicated on drastically new hardware and software architectures.
Time taken to write data in parallel on Lustre follows extreme statistics

In both high-performance computing (HPC) environments and the public cloud, the duration of time to retrieve or save your results is simultaneously unpredictable and important to your over all resource budget. It is generally accepted (“Google: Taming the Long Latency Tail When More Machines Equals Worse Results”, Todd Hoff, highscalability.com 2012) , but without a robust explanation, that identical parallel tasks do take different durations to complete – a phenomena known as variability. This paper advances understanding of this topic. We carefully choose a model from which system-level complexity emerges that can be studied directly. We find that a generalized extreme value (GEV) model for variability naturally emerges. Using the public cloud, we find real-world observations have excellent agreement with our model. Since the GEV distribution is a limit distribution this suggests a universal property of parallel systems gated by the slowest communication element of some sort. Hence, this model is applicable to a variety of processing and IO tasks in parallel environments. These findings have important implications, ranging from idealized performance characteristics for parallel codes to detecting degraded behaviour at extreme scales.
18 Neural Networks in Bioinformatics

Over the last two decades, neural networks (NNs) gradually became one of the indispensable tools in bioinformatics. This was fueled by the development and rapid growth of numerous biological databases that store data concerning DNA and RNA sequences, protein sequences and structures, and other macromolecular structures. The size and complexity of these data require the use of advanced computational tools. Computational analysis of these databases aims at exposing hidden information that provides insights which help with understanding the underlying biological principles. The most commonly explored capability of neural networks that is exploited in the context of bioinformatics is prediction. This is due to the existence of a large body of raw data and the availability of a limited amount of data that are annotated and can be used to derive the prediction model. In this chapter we discuss and summarize applications of neural networks in bioinformatics, with a particular focus on applications in protein bioinformatics. We summarize the most often used neural network architectures, and discuss several specific applications including prediction of protein secondary structure, solvent accessibility, and binding residues.
Coupling and uncoupling between nitrate uptake and growth rate in Prorocentrum minimum (Dinophyceae) under different frequencies of pulsed nitrate supply

Nitrate uptake and growth rates of the red-tide dinoflagellate Prorocentrum minimum were measured in a chemostat culture system in which nitrate was added in the same total amounts every 1, 2 or 3 d In comparison with continuous nitrate supply, the rate of cell division was not affected by the 1 or 2 d pulse treatments, whereas it fell drastically when a nitrogen source was added only every 3 d. Delayed steady uptake rates were reached during the 1 or 2 d pulse phases, which reflected a mid-term adaptation of the cell uptake process under discontinuous nutrient supply. This adaptation permitted P. minimun~ to maintain a steady growth rate under these regimes. During the 3 d pulse treatment, the maximal uptake rate measured during each pulse experiment increased considerably. which reflected a long-term adaptation, but was not sufficient to maintain the initlal growth rate. For low frequencies of nitrate supply, uptake and growth rate became largely uncoupled. It is concluded that P. minimum is a species able to form a large internal pool of nitrogen which constitutes a competitive advantage. This is discussed in the light of in situ observations.