Miracle-dz/UniFAR-FTUs huggingface dataset:
Leptin Increases TNF-α Expression and Production through Phospholipase D1 in Raw 264.7 Cells

Epidemiological evidence suggests that obesity is associated with inflammation of the respiratory tract and the pathogenesis of asthma. The purpose of this study was to examine the role of phospholipase D1 (PLD1) in leptin-induced expression of the proinflammatory cytokine, tumor necrosis factor (TNF)-α, and to suggest a molecular link between obesity and respiratory tract inflammation. We investigated whether leptin, a typical adipocytokine, plays a role in the expression of TNF-α through increased PLD1 activity in Raw 264.7. Leptin enhanced the activity of PLD1 through activation of PLCγ and Src, while PLD1 siRNA decreased the leptin-induced expression and production of TNF-α. Leptin-induced PLD activation was also inhibited by a PLCγ inhibitor (PAO) and Src kinase inhibitor (PP2), indicating that PLCγ and Src kinase are upstream activators of PLD1. Down-regulation of PLD1 also completely blocked activation of p70S6K, an activator of JNK. Leptin-induced expression of TNF-α was also prevented by inhibition of p70S6K and JNK. Taken together, these results indicate that PLD1 acts as an important regulator of leptin-induced expression of TNF-α by participating in the PLCγ/Src/PLD1/PA/p70S6K/JNK pathway.
Biomaterials in orthopaedics

At present, strong requirements in orthopaedics are still to be met, both in bone and joint substitution and in the repair and regeneration of bone defects. In this framework, tremendous advances in the biomaterials field have been made in the last 50 years where materials intended for biomedical purposes have evolved through three different generations, namely first generation (bioinert materials), second generation (bioactive and biodegradable materials) and third generation (materials designed to stimulate specific responses at the molecular level). In this review, the evolution of different metals, ceramics and polymers most commonly used in orthopaedic applications is discussed, as well as the different approaches used to fulfil the challenges faced by this medical field.
Faster beam-search decoding for phrasal statistical machine translation

Pharaoh is a widely-used state-of-the-art decoder for phrasal statistical machine translation. In this paper, we present two modifications to the algorithm used by Pharaoh that together permit much faster decoding without losing translation quality as measured by B LEU score. The first modification improves the estimated translation model score used by Pharaoh to evaluate partial hypotheses, by incorporating an estimate of the distortion penalty to be incurred in translating the rest of the sentence. The second modification uses early pruning of possible next-phrase translations to cut down the overall size of the search space. These modifications enable decoding speed-ups of an order of magnitude or more, with no reduction in the B LEU score of the resulting translations.
Research and Design of RFID Data Processing Model Based on Complex Event Processing

Data processing is a key issue of the design of RFID middleware, and the general processing mode is based on Event. The data processed and output by this solution canpsilat really meet the needs of various application systems; nevertheless, the complex event processing technology can overcome the disadvantage effectively. According to the principles that can make it effective to manage RFID data, this paper proposes a RFID data processing model based on complex event processing (CEP) technique, provides the related definitions, elaborates the function modules involved (the event monitoring module, the buffer module, the event processing module and the event sending/subscribe module) and their solutions.
Sound Modeling of Javanese Traditional Music Instrument

A Gamelan set consists of several groups of different instruments. One of the groups is called Balungan. Gamelan is contructed manually by hand with simple tools so it is very hard to find two gamelan sets are totally identical. In this research we propose to construct gamelan models. The main target of this research is creating Gamelan Frequency Modeling. We propose two Frequency Balungan Models, the first model is using average value, and the other is using average value in the most dense area.
Tracking Temporal Community Strength in Dynamic Networks

Community formation analysis of dynamic networks has been a hot topic in data mining which has attracted much attention. Recently, there are many studies which focus on discovering communities successively from consecutive snapshots by considering both the current and historical information. However, these methods cannot provide us with much historical or successive information related to the detected communities. Different from previous studies which focus on community detection in dynamic networks, we define a new problem of tracking the progression of the community strength-a novel measure that reflects the community robustness and coherence throughout the entire observation period. To achieve this goal, we propose a novel framework which formulates the problem as an optimization task. The proposed community strength analysis also provides foundation for a wide variety of related applications such as discovering how the strength of each detected community changes over the entire observation period. To demonstrate that the proposed method provides precise and meaningful evolutionary patterns of communities which are not directly obtainable from traditional methods, we perform extensive experimental studies on one synthetic and five real datasets: Social evolution, tweeting interaction, actor relationships, bibliography, and biological datasets. Experimental results show that the proposed approach is highly effective in discovering the progression of community strengths and detecting interesting communities.
Designing Regenerative Biomaterial Therapies for the Clinic

Several academic, regulatory, and clinical aspects should be considered when moving biomaterials from the lab to the patient. The ability to regenerate damaged tissue is one of the great challenges in biomaterials and medicine. Successful treatments will require advances in areas ranging from basic cell biology to materials synthesis, but there have been major hurdles in translating the biomedical advances, such as scaffolds that direct stem cell differentiation, into marketed products. Careful consideration of the challenges going from bench to bedside is paramount in maximizing the chances that a good idea becomes a good treatment. We look at a variety of material-based platforms that have made it into the clinic, from biodegradable polymers for wound healing to organs grown ex vivo, and how they have been able to navigate the scientific, regulatory, and business hurdles into the market place.
A study of network stack latency for game servers

Latency has a high impact on the user satisfaction in real-time multiplayer games. The network between the client and server is, in most cases, the main cause for latency and out of the scope of the game's developer. But the developer should avoid introducing unnecessary delays within his responsibility; i.e. with respect to development and operating costs he should wisely choose a network stack and deployment model for the server in order to reduce latency. In this paper we present latency measurements of the Linux network stack and effects of virtualization. We show that a worst-case scenario can cause a latency in the millisecond range when running a game server. We discuss how latencies can be reduced by using the packet processing framework DPDK to replace the operating system's network stack.
Mitochondrial DNA Replication: What We Know

Since the isolation and physical characterization of mammalian mitochondrial DNA (mtDNA) over 35 years ago, numerous works have been published that have examined its physical structure and properties, including its mode of replication and transcription. The established replication model posits that leading‐strand replication of mammalian mtDNA begins at closely spaced, defined sites located downstream from a major transcription promoter and proceeds unidirectionally with displacement of the parental leading strand until approximately two‐thirds of the closed circular mtDNA has been copied. As a consequence, the replication fork passes a major origin for lagging‐strand synthesis, exposing it in single‐stranded form. Displacement as a single‐strand is thought to allow the characteristic secondary structure of this origin to occur, thereby permitting initiation of lagging‐strand synthesis. A natural consequence of the separate and distinct locations of the two origins is that the two segregated progeny mtDNA circles are of two types: one a duplex circle with a newly synthesized leading strand and the other a gapped circle with a partial newly synthesized lagging strand. In each case, the final steps of synthesis and ligation result in closed circular mtDNA products. Recently, mammalian mtDNA isolates have been subjected to 2D‐gel electrophoretic analysis in attempts to assign features to mtDNA molecules that, by virtue of their anomalous migration behavior, could infer them to be candidates for replication intermediates. This review will describe the essential features of the historical findings of mammalian mtDNA replication studies and integrate the more recent observations in developing a current model for this process. IUBMB Life, 55: 213‐217, 2003
Unsupervised Nosologic Imaging for Glioma Diagnosis

In this letter a novel approach to create nosologic images of the brain using magnetic resonance spectroscopic imaging (MRSI) data in an unsupervised way is presented. Different tissue patterns are identified from the MRSI data using nonnegative matrix factorization and are then coded as different primary colors (i.e. red, green, and blue) in an RGB image, so that mixed tissue regions are automatically visualized as mixtures of primary colors. The approach is useful in assisting glioma diagnosis, where several tissue patterns such as normal, tumor, and necrotic tissue can be present in the same voxel/spectrum. Error-maps based on linear least squares estimation are computed for each nosologic image to provide additional reliability information, which may help clinicians in decision making. Tests on in vivo MRSI data show the potential of this new approach.
On learning multiple descriptions of a concept

In sparse data environments, greater classification accuracy can be achieved by learning several concept descriptions of the data and combining their classifications. Stochastic searching can be used to generate many concept descriptions (rule sets) for each class in the data. We use a tractable approximation to the optimal Bayesian method for combining classifications from such descriptions. The primary result of this paper is that multiple concept descriptions are particularly helpful in "flat" hypothesis spaces in which there are many equally good ways to grow a rule, each having similar gain. Another result is experimental evidence that learning multiple rule sets yields more accurate classifications than learning multiple rules for some domains. <<ETX>>
Melatonin prevents cell death and mitochondrial dysfunction via a SIRT1‐dependent mechanism during ischemic‐stroke in mice

Silent information regulator 1 (SIRT1), a type of histone deacetylase, is a highly effective therapeutic target for protection against ischemia reperfusion (IR) injury (IRI). Previous studies showed that melatonin preserves SIRT1 expression in neuronal cells of newborn rats after hypoxia–ischemia. However, the definite role of SIRT1 in the protective effect of melatonin against cerebral IRI in adult has not been explored. In this study, the brain of adult mice was subjected to IRI. Prior to this procedure, the mice were given intraperitoneal with or without the SIRT1 inhibitor, EX527. Melatonin conferred a cerebral‐protective effect, as shown by reduced infarct volume, lowered brain edema, and increased neurological scores. The melatonin‐induced upregulation of SIRT1 was also associated with an increase in the anti‐apoptotic factor, Bcl2, and a reduction in the pro‐apoptotic factor Bax. Moreover, melatonin resulted in a well‐preserved mitochondrial membrane potential, mitochondrial Complex I activity, and mitochondrial cytochrome c level while it reduced cytosolic cytochrome c level. However, the melatonin‐elevated mitochondrial function was reversed by EX527 treatment. In summary, our results demonstrate that melatonin treatment attenuates cerebral IRI by reducing IR‐induced mitochondrial dysfunction through the activation of SIRT1 signaling.
Passiflora cincinnata Extract Delays the Development of Motor Signs and Prevents Dopaminergic Loss in a Mice Model of Parkinson's Disease

Passiflora cincinnata Masters is a Brazilian native species of passionflower. This genus is known in the American continent folk medicine for its diuretic and analgesic properties. Nevertheless, few studies investigated possible biological effects of P. cincinnata extracts. Further, evidence of antioxidant actions encourages the investigation of possible neuroprotective effects in animal models of neurodegenerative diseases. This study investigates the effect of the P. cincinnata ethanolic extract (PAS) on mice submitted to a progressive model of Parkinson's disease (PD) induced by reserpine. Male (6-month-old) mice received reserpine (0.1 mg/kg, s.c.), every other day, for 40 days, with or without a concomitant treatment with daily injections of PAS (25 mg/kg, i.p.). Catalepsy, open field, oral movements, and plus-maze discriminative avoidance evaluations were performed across treatment, and immunohistochemistry for tyrosine hydroxylase was conducted at the end. The results showed that PAS treatment delayed the onset of motor impairments and prevented the occurrence of increased catalepsy behavior in the premotor phase. However, PAS administration did not modify reserpine-induced cognitive impairments. Moreover, PAS prevented the decrease in tyrosine hydroxylase immunostaining in the substantia nigra pars compacta (SNpc) induced by reserpine. Taken together, our results suggested that PAS exerted a neuroprotective effect in a progressive model of PD.
Using graph partitioning to discover regions of correlated spatio-temporal change in evolving graphs

There is growing interest in studying dynamic graphs, or graphs that evolve with time. In this work, we investigate a new type of dynamic graph analysis - finding regions of a graph that are evolving in a similar manner and are topologically similar over a period of time. For example, these regions can be used to group a set of changes having a common cause in event detection and fault diagnosis. Prior work [6] has proposed a greedy framework called cSTAG to find these regions. It was accurate in datasets where the regions are temporally and spatially well separated. However, in cases where the regions are not well separated, cSTAG produces incorrect groupings. In this paper, we propose a new algorithm called regHunter. It treats the region discovery problem as a multi-objective optimisation problem, and it uses a multi-level graph partitioning algorithm to discover the regions of correlated change. In addition, we propose an external clustering validation technique, and use several existing internal measures to evaluate the accuracy of regHunter. Using synthetic datasets, we found regHunter is significantly more accurate than cSTAG in dynamic graphs that have regions with small separation. Using two real datasets - the access graph of the 1998 World Cup website, and the BGP connectivity graph during the landfall of Hurricane Katrina - we found regHunter obtained more accurate results than cSTAG. Furthermore, regHunter was able to discover two interesting regions for the World Cup access graph that CSTAG was not able to find.
Flood risk awareness and preparedness: The role of trust in information sources

A realistic and scientific risks communication system is inevitable for better risk awareness and improved disaster preparedness. Conventional disaster management studies paid much attention on the contents of the information, and ignored the importance of information source. Since natural disasters are uncertain and complex, individuals decisions on disaster issues depend much on their trust in risk information source. This study systematically examines the role of trust in risk awareness and preparedness. The study is based on field surveys conducted in two flood affected slum communities in Mumbai, India. The study has revealed that higher trust leads to higher risk awareness and better acceptance of perusing preventive action. To take decision on impending risk or early warning, individuals depend most on the local city authority because the community believes the city authority is having better flood management skill and knowledge. The degree of acceptance of flood preventive measure depends on how much risk communicating agency cares and concerns about community's interest. In this study, responded reported mass media is the one who cares most about community's interest. The role of local leaders is negligible in entire risk communication process, because the local community does not have much trust in local leaders. The study reestablished that trust in risk communication sources is inevitable for improved disaster risks communication.
Genome-Wide SNP Discovery, Genotyping and Their Preliminary Applications for Population Genetic Inference in Spotted Sea Bass (Lateolabrax maculatus)

Next-generation sequencing and the collection of genome-wide single-nucleotide polymorphisms (SNPs) allow identifying fine-scale population genetic structure and genomic regions under selection. The spotted sea bass (Lateolabrax maculatus) is a non-model species of ecological and commercial importance and widely distributed in northwestern Pacific. A total of 22 648 SNPs was discovered across the genome of L. maculatus by paired-end sequencing of restriction-site associated DNA (RAD-PE) for 30 individuals from two populations. The nucleotide diversity (π) for each population was 0.0028±0.0001 in Dandong and 0.0018±0.0001 in Beihai, respectively. Shallow but significant genetic differentiation was detected between the two populations analyzed by using both the whole data set (FST = 0.0550, P < 0.001) and the putatively neutral SNPs (FST = 0.0347, P < 0.001). However, the two populations were highly differentiated based on the putatively adaptive SNPs (FST = 0.6929, P < 0.001). Moreover, a total of 356 SNPs representing 298 unique loci were detected as outliers putatively under divergent selection by FST-based outlier tests as implemented in BAYESCAN and LOSITAN. Functional annotation of the contigs containing putatively adaptive SNPs yielded hits for 22 of 55 (40%) significant BLASTX matches. Candidate genes for local selection constituted a wide array of functions, including binding, catalytic and metabolic activities, etc. The analyses with the SNPs developed in the present study highlighted the importance of genome-wide genetic variation for inference of population structure and local adaptation in L. maculatus.
Highly sensitive targeted methylome sequencing by post-bisulfite adaptor tagging

The current gold standard method for methylome analysis is whole-genome bisulfite sequencing (WGBS), but its cost is substantial, especially for the purpose of multi-sample comparison of large methylomes. Shotgun bisulfite sequencing of target-enriched DNA, or targeted methylome sequencing (TMS), can be a flexible, cost-effective alternative to WGBS. However, the current TMS protocol requires a considerable amount of input DNA and hence is hardly applicable to samples of limited quantity. Here we report a method to overcome this limitation by using post-bisulfite adaptor tagging (PBAT), in which adaptor tagging is conducted after bisulfite treatment to circumvent bisulfite-induced loss of intact sequencing templates, thereby enabling TMS of a 100-fold smaller amount of input DNA with far fewer cycles of polymerase chain reaction than in the current protocol. We thus expect that the PBAT-mediated TMS will serve as an invaluable method in epigenomics.
Spontaneous Quinolone Resistance in the Zoonotic Serovar of Vibrio vulnificus

ABSTRACT This work demonstrates that Vibrio vulnificus biotype 2, serovar E, an eel pathogen able to infect humans, can become resistant to quinolone by specific mutations in gyrA (substitution of isoleucine for serine at position 83) and to some fluoroquinolones by additional mutations in parC (substitution of lysine for serine at position 85). Thus, to avoid the selection of resistant strains that are potentially pathogenic for humans, antibiotics other than quinolones must be used to treat vibriosis on farms.
Freeform 3D printing: Towards a sustainable approach to additive manufacturing

: Most additive manufacturing technologies, such as 3D printing, utilize support materials in the fabrication process. Beyond the technical challenges of support removal, these materials are wasteful – increasing fabrication and processing time while impacting quality. This paper presents “Freeform Printing”, a novel design approach for 3D printing without additional auxiliary structures. A 6-axis KUKA robotic arm is repurposed as a 3D printing platform onto which custom-designed thermoplastic extruders are attached. We demonstrate freeform extrusion using a round nozzle attached to an active air-cooling unit, which solidifies the material upon extrusion. In addition, we present a method for printing geometrically complex structures using a multi-strand extrusion nozzle. The experiments presented in this paper, combined with their evaluation and analysis, provide proof-of-concept for Freeform Printing without support materials. They represent a sustainable approach to additive manufacturing and digital fabrication at large, and point towards new possible directions in sustainable manufacturing.
The complete chloroplast genome sequence of desert poplar (Populus euphratica)

Abstract The complete chloroplast sequence of the desert poplar (Populus euphratica), a plant well-adapted to salt stress, was determined in this study. The genome consists of 156,766 bp containing a pair of inverted repeats (IRs) of 16,591 bp separated by a large single-copy region and a small single-copy region of 84,888 bp and 27,646 bp, respectively. The chloroplast genome contains 130 known genes, including 89 protein-coding genes, 8 ribosomal RNA genes, and 37 tRNA genes; 18 of these are located in the inverted repeat region.
Performance analysis of multi‐input multi‐output systems with maximum likelihood detection over shadowed fading channels

Multiple‐input multiple‐output (MIMO) transmission techniques constitute an important technology in modern wireless communication. Hence, performance analysis methods for such systems are of considerable interest. This paper considers first the average pairwise error probability for uncoded MIMO systems employing maximum likelihood detection over a composite Rayleigh‐Lognormal fading channel with spatial correlation. It provides general results, applicable also to a wider class of shadowing models, concerning asymptotical diversity gains and shows that they are not changed by such shadowing. Then, analytical evaluation techniques for bit‐error‐rate (BER) over composite Rayleigh‐Lognormal fading channels, based on the truncated union bound and the transfer function, are considered. Furthermore, these techniques are modified for applications over spatially correlated channels. This paper shows that such performance evaluation techniques provide good approximations to BER of spatially uncorrelated MIMO systems and also in the presence of moderate spatial correlation, over Rayleigh‐Lognormal fading channels. Copyright © 2013 John Wiley & Sons, Ltd.