Miracle-dz/UniFAR-FTUs huggingface dataset:
A flicker-free electrolytic capacitor-less ac-dc LED driver

Electrolytic capacitor is the key component that limits the lifetime of LED driver. When an ac-dc LED driver with the function of power factor correction (PFC) outputs a pulsating current to drive LEDs, electrolytic capacitor is not required any longer. However, the pulsating current brings flicker with twice the line frequency. In this paper, the concept of flicker-free electrolytic capacitor-less ac-dc driver for LED lighting is proposed, which consists of an electrolytic capacitor-less PFC converter and a bidirectional buck/boost converter. The bidirectional buck/boost converter provides the path for the ac component in the pulsating current of the PFC converter to flow through, leaving a pure dc current to drive the LEDs without flicker. The voltage of the output filter capacitor of the bidirectional converter is intentionally designed to have large ripple, and thus the capacitance can be greatly reduced. Consequently, the output filter capacitor can adopt film capacitor instead of electrolytic capacitor. So the ac-dc LED driver has no flicker and has a long lifetime. A 48 V, 0.7 A output prototype is built and tested in the lab, and the experimental results are presented to verify the effectiveness of the flicker-free electrolytic capacitor-less ac-dc LED driver.
An enhanced AES algorithm using cascading method on 400 bits key size used in enhancing the safety of next generation internet of things (IOT)

This paper of cascaded[4] AES [1][2] suggest symmetrical block encryption using 200 bit sequential plain text and 400 bit key. Algorithm uses 400 bit key which is divided into 2 parts of 200–200 bits providing different keys for each rounds of cascading which will increase the security. Here AES-AES cascading is done which consist of 5 rounds instead of 10, thus it will omit the mix column twice from the original AES Encryption technique. Omitting mix column [3] single time reduce the complexity from 248 to 216. Hence, it takes half time than simple AES algorithm to encrypt the block data. Since is AES is widely used international standard encryption method and is also used to provide security in area of wireless LAN's thus, it could be used to provide energy saving cryptographic technique for myriad devices that are connected to network in IoT [13], this result was announced in August 19, 2016 Conference on Cryptographic Hardware and Embedded Systems 2016(CHES 2016) Conference on Cryptographic Hardware and Embedded Systems 2016(CHES 2016).
[An experimental research on differentiation of mesenchymal stem cells derived from children with spinal muscular atrophy into neuron-like cells].

OBJECTIVE Spinal muscular atrophy (SMA) is an autosomal recessive neurodegenerative disease. It is characterized by selective loss of spinal cord motor neurons leading to muscle atrophy and is the result of mutation or deletion of the survival motor neuron (SMN) gene. Currently, there are no effective therapies for this disease. Stem cell therapy is a new prospect for SMA patients. This study aimed to investigate whether mesenchymal stem cells (MSCs) can be differentiated into neuron-like cells (NLCs) in SMA patients in order to provide a basis for stem cell therapy for SMA. METHODS SMA was definitively diagnosed using polymerase chain reaction-restriction fragment length polymerphhism (PCR-RFLP). Two children without SMN1 gene deletion were used as controls. MSCs were isolated and purified from SMA patients and controls, and induced into NLCs by bFGF and baicalin. The NLCs were identified by immunofluourescence staining with NSE and NF monoclonal antibodies. RESULTS SMA patients showed the deletion of SMN1 exon 7. The morphous and proliferative speed of MSCs between SMA patients and controls were similar. After 6-day induction, MSCs of the two groups displayed similar morphology to that of neurons, with long processes forming extensive networks. NSE and NF, the neuronal markers, were detected in the differentiated NLCs of the two groups. CONCLUSIONS SMN1 deletion appears not to affect the proliferation and differentiation of MSCs. MSCs of SMA patients can be differentiated into NLCs.
A study of supply chain management practices: an empirical investigation on consumer goods industry in Malaysia

The purpose of this research is to present the relationship between supply chain management (SCM) practices and supply chain responsiveness (SCR), and investigates its relationship with competitive advantage (CA). The data collection instrument used was a questionnaire which was administrated to a total sample of 200 managers. The response rate was 70% while 60% was usable questionnaires. Sample selection was based on convenience sampling. The analyses involved statistical methods such as reliability and validity tests and multiple regressions. The results indicated that SCM practices are related to SCR. The result also suggested that SCR is related to CA.
Scalable event-driven native parallel processing: the SpiNNaker neuromimetic system

Neural networks present a fundamentally different model of computation from the conventional sequential digital model. Modelling large networks on conventional hardware thus tends to be inefficient if not impossible. Neither dedicated neural chips, with model limitations, nor FPGA implementations, with scalability limitations, offer a satisfactory solution even though they have improved simulation performance dramatically. SpiNNaker introduces a different approach, the "neuromimetic" architecture, that maintains the neural optimisation of dedicated chips while offering FPGA-like universal configurability. Central to this parallel multiprocessor is an asynchronous event-driven model that uses interrupt-generating dedicated hardware on the chip to support real-time neural simulation. While this architecture is particularly suitable for spiking models, it can also implement "classical" neural models like the MLP efficiently. Nonetheless, event handling, particularly servicing incoming packets, requires careful and innovative design in order to avoid local processor congestion and possible deadlock. Using two exemplar models, a spiking network using Izhikevich neurons, and an MLP network, we illustrate how to implement efficient service routines to handle input events. These routines form the beginnings of a library of "drop-in" neural components. Ultimately, the goal is the creation of a library-based development system that allows the modeller to describe a model in a high-level neural description environment of his choice and use an automated tool chain to create the appropriate SpiNNaker instantiation. The complete system: universal hardware, automated tool chain, embedded system management, represents the "ideal" neural modelling environment: a general-purpose platform that can generate an arbitrary neural network and run it with hardware speed and scale.
A Call for Greater Consideration for the Role of Vaccines in National Strategies to Combat Antibiotic-Resistant Bacteria: Recommendations from the National Vaccine Advisory Committee

The emergence of a novel virus receives widespread attention in the news media and among the public. However, the greatest threat to public health in the United States is unlikely to be an exotic disease but, rather, the mounting threat of antibiotic resistance in commonly acquired bacterial infections. The human and economic costs of this growing crisis are notable.1,2 In the 2013 report by the Centers for Disease Control and Prevention (CDC), Antibiotic Resistance Threats in the United States, it is estimated that more than two million people contract an antibiotic-resistant infection each year in the United States, and approximately 23,000 die as a result of their infection.2 The escalating rate of resistance among bacterial pathogens is being facilitated by the abundant (and often inappropriate) use of antibiotics, and concern is rising that the arsenal of effective products to treat bacterial infections will soon run out.3 For example, it is now estimated that 6,700 (13%) of the 51,000 health-care–associated Pseudomonas aeruginosa infections that occur in the United States each year are resistant to at least three classes of antibiotics, and some strains show resistance to nearly all classes of antibiotics.2 The lack of effective antibiotic therapy will have a significant impact in nearly all areas of medicine, but especially in surgery, oncology, intensive care, and transplant medicine. In September 2014, the White House released the President’s National Strategy to Combat AntibioticResistant Bacteria4 concurrently with the President’s Council of Advisors on Science and Technology (PCAST) report and recommendations to the president on combating antibiotic resistance.5 Together, these reports identify priorities and guide coordination across U.S. government agencies to (1) better prevent and respond to the spread of antibiotic resistance through improved prevention and stewardship of antibiotic use; (2) increase surveillance of emerging antibiotic resistance in humans, animals, and the environment; (3) improve capabilities for detection and diagnostics; (4) accelerate development of new products, including new classes of antibiotics, therapeutics, and vaccines; and (5) enhance international collaboration.4 The federal commitment to addressing this issue was further emphasized by Presidential Executive Order 13676,6 which calls for the development of a five-year National Action Plan7 that proposes concrete activities and milestones for achieving the goals outlined in the National Strategy and a presidential budget request to Congress for $1.2 billion.8
Efficient evaluation of scaled proximal operators

Quadratic-support functions [Aravkin, Burke, and Pillonetto; J. Mach. Learn. Res. 14(1), 2013] constitute a parametric family of convex functions that includes a range of useful regularization terms found in applications of convex optimization. We show how an interior method can be used to efficiently compute the proximal operator of a quadratic-support function under different metrics. When the metric and the function have the right structure, the proximal map can be computed with cost nearly linear in the input size. We describe how to use this approach to implement quasi-Newton methods for a rich class of nonsmooth problems that arise, for example, in sparse optimization, image denoising, and sparse logistic regression.
The interface behavior of the Cu-Al bond system in high humidity conditions

Copper (Cu) wire has been highlighted as a low cost material for use in thermosonic ball bonding for various package (PKG) groups. This wire has already been applied in high-end PKGs such as BGA, QFP and QFN in mass production, and the volume is feasible. Not only the advantage of a low cost material, but Cu wire has other merits which include higher electrical conductivity and a much slower inter-metallic compound (IMC) growth rate than Gold (Au) wire.
Weight loss efficacy of a novel mobile Diabetes Prevention Program delivery platform with human coaching

Objective To evaluate the weight loss efficacy of a novel mobile platform delivering the Diabetes Prevention Program. Research Design and Methods 43 overweight or obese adult participants with a diagnosis of prediabetes signed-up to receive a 24-week virtual Diabetes Prevention Program with human coaching, through a mobile platform. Weight loss and engagement were the main outcomes, evaluated by repeated measures analysis of variance, backward regression, and mediation regression. Results Weight loss at 16 and 24 weeks was significant, with 56% of starters and 64% of completers losing over 5% body weight. Mean weight loss at 24 weeks was 6.58% in starters and 7.5% in completers. Participants were highly engaged, with 84% of the sample completing 9 lessons or more. In-app actions related to self-monitoring significantly predicted weight loss. Conclusions Our findings support the effectiveness of a uniquely mobile prediabetes intervention, producing weight loss comparable to studies with high engagement, with potential for scalable population health management.
Organismal complexity, cell differentiation and gene expression: human over mouse

We present a molecular and cellular phenomenon underlying the intriguing increase in phenotypic organizational complexity. For the same set of human–mouse orthologous genes (11 534 gene pairs) and homologous tissues (32 tissue pairs), human shows a greater fraction of tissue-specific genes and a greater ratio of the total expression of tissue-specific genes to housekeeping genes in each studied tissue, which suggests a generally higher level of evolutionary cell differentiation (specialization). This phenomenon is spectacularly more pronounced in those human tissues that are more directly involved in the increase of complexity, longevity and body size (i.e. it is reflected on the organismal level as well). Genes with a change in expression breadth show a greater human–mouse divergence of promoter regions and encoded proteins (i.e. the functional genomics data are supported by the structural analysis). Human also shows the higher expression of translation machinery. The upstream untranslated regions (5′UTRs) of human mRNAs are longer than mouse 5′UTRs (even after correction for the difference in genome sizes) and contain more uAUG codons, which suggest a more complex regulation at the translational level in human cells (and agrees well with the augmented cell specialization).
Identification of iron-activated and -repressed Fur-dependent genes by transcriptome analysis of Neisseria meningitidis group B

Iron is limiting in the human host, and bacterial pathogens respond to this environment by activating genes required for bacterial virulence. Transcriptional regulation in response to iron in Gram-negative bacteria is largely mediated by the ferric uptake regulator protein Fur, which in the presence of iron binds to a specific sequence in the promoter regions of genes under its control and acts as a repressor. Here we describe DNA microarray, computational and in vitro studies to define the Fur regulon in the human pathogen Neisseria meningitidis group B (strain MC58). After iron addition to an iron-depleted bacterial culture, 153 genes were up-regulated and 80 were down-regulated. Only 50% of the iron-regulated genes were found to contain Fur-binding consensus sequences in their promoter regions. Forty-two promoter regions were amplified and 32 of these were shown to bind Fur by gel-shift analysis. Among these genes, many of which had never been described before to be Fur-regulated, 10 were up-regulated on iron addition, demonstrating that Fur can also act as a transcriptional activator. Sequence alignment of the Fur-binding regions revealed that the N. meningitidis Fur-box encompasses the highly conserved (NATWAT)3 motif. Cluster analysis was effective in predicting Fur-regulated genes even if computer prediction failed to identify Fur-box-like sequences in their promoter regions. Microarray-generated gene expression profiling appears to be a very effective approach to define new regulons and regulatory pathways in pathogenic bacteria.
H5.2. Informat User Interfaces

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Turning a Dependency Treebank into a PSG-style Constituent Treebank

In this paper, we present and evaluate a new method to convert Constraint Grammar (CG) parses of running text into Constituent Treebanks. The conversion is two-step - first a grammar-based method is used to bridge the gap between raw CG annotation and full dependency structure, then phrase structure bracketing and non-terminal nodes are introduced by clustering sister dependents, effectively building one syntactic treebank on top of another. The method is compared with another approach (Bick 2003-2), where constituent structures are arrived at by employing a function-tag based Phrase Structure Grammar (PSG). Results are evaluated on a small reference corpus for both raw and revised CG input, with bracketing F-Scores of 87.5% for raw text and 97.1% for revised CG input, and a raw text edge label accuracy of 95.9% for forms and 86% for functions, or 99.7% and 99.4%, respectively, for revised CG. By applying the tools to the CG-only part of the Danish Arboretum treebank we were able to increase the size of the treebank by 86%, from 197.400 to 367.500 words.
The future of vitamin D analogs

The active form of vitamin D3, 1,25-dihydroxyvitamin D3, is a major regulator of bone and calcium homeostasis. In addition, this hormone also inhibits the proliferation and stimulates the differentiation of normal as well as malignant cells. Supraphysiological doses of 1,25-dihydroxyvitamin D3 are required to reduce cancer cell proliferation. However, these doses will lead in vivo to calcemic side effects such as hypercalcemia and hypercalciuria. During the last 25 years, many structural analogs of 1,25-dihydroxyvitamin D3 have been synthesized by the introduction of chemical modifications in the A-ring, central CD-ring region or side chain of 1,25-dihydroxyvitamin D3 in the hope to find molecules with a clear dissociation between the beneficial antiproliferative effects and adverse calcemic side effects. One example of such an analog with a good dissociation ratio is calcipotriol (Daivonex®), which is clinically used to treat the hyperproliferative skin disease psoriasis. Other vitamin D analogs were clinically approved for the treatment of osteoporosis or secondary hyperparathyroidism. No vitamin D analog is currently used in the clinic for the treatment of cancer although several analogs have been shown to be potent drugs in animal models of cancer. Transcriptomics studies as well as in vitro cell biological experiments unraveled basic mechanisms involved in the antineoplastic effects of vitamin D and its analogs. 1,25-dihydroxyvitamin D3 and analogs act in a cell type- and tissue-specific manner. Moreover, a blockade in the transition of the G0/1 toward S phase of the cell cycle, induction of apoptosis, inhibition of migration and invasion of tumor cells together with effects on angiogenesis and inflammation have been implicated in the pleiotropic effects of 1,25-dihydroxyvitamin D3 and its analogs. In this review we will give an overview of the action of vitamin D analogs in tumor cells and look forward how these compounds could be introduced in the clinical practice.
Citrus Water Use

Citrus is grown in semi-arid regions or subtropical regions in large parts of the world, where rainfall is seasonal and irrigation a necessity. Water is a vitally important element in all ecosystems and as agriculture is the largest user of fresh water resources, it needs to be efficient in the use of water. This is particularly true for the citrus industry, as it has a significant irrigation requirement. Good irrigation scheduling practices rely on accurate estimates of plant water-use (transpiration) for different climatic regions, citrus varieties, tree and canopy size, and choice of rootstock. This usually requires the use of a model, where a thorough understanding of the regulation of transpiration will improve the estimation capabilities of such a model. Results from our study (Quantifying citrus water use and water stress at tree and orchard scale, Water Research Commission Project K5/2275//4) showed that transpiration (T) follows diurnal and seasonal trends and is influenced by stomatal conductance (g s ) and leaf water potentials (Ѱl). Good correlations between T and temperature, vapour pressure deficit (VPD) and solar radiation (SR) were found, indicating the importance of the environment in supplying the energy to drive transpiration. There was also a good relationship between canopy size and T, with larger canopies having higher T.
Single-channel signal separation using time-domain basis functions

We present a new technique for achieving blind source separation when given only a single-channel recording. The main idea is based on exploiting the inherent time structure of sound sources by learning a priori sets of time-domain basis functions that encode the sources in a statistically efficient manner. We derive a learning algorithm using a maximum likelihood approach given the observed single-channel data and sets of basis functions. For each time point, we infer the source parameters and their contribution factors using a flexible but simple density model. We show the separation results of two music signals as well as the separation of two voice signals.
Spatial Cognition of Residents towards the Conservation Area of Upo Wetland

Wetlands are being negatively affected by various human activities such as reclamation, construction of levees, and conventional agricultural activities. Upo Wetland is the largest inland wetland in the Republic of Korea (hereinafter Korea). It has not only been designated as a wetland protection area by the Wetland Conservation Act of Korea but also registered as a Ramsar Site in 1998. In this study, cognitive mapping of the Upo Wetland and surrounding areas was applied to identify sensitive and vulnerable areas that should be carefully managed. The results of the cognitive mapping were compared with existing land-use zones of the wetland conservation area. Furthermore, this paper discusses the advantages of resident participation in cognitive mapping over conventional social and environmental analysis for landscape planning on other conservation areas.