Miracle-dz/UniFAR-FTUs huggingface dataset:
Specificity of nerve growth factor signaling: Differential patterns of early tyrosine phosphorylation events induced by NGF, EGF, and bFGF

The specificity of nerve growth factor (NGF) action was examined by comparing early tyrosine phosphorylation events induced by NGF, epidermal growth factor (EGF), and basic fibroblast growth factor (bFGF). In PC12 cells, administration of either the differentiation factor NGF or the mitogenic factor EGF led to tyrosine phosphorylation of multiple polypeptides in the 100–110 kDa size range associated with PI‐3 kinase. However, NGF induced a more prolonged phosphorylation, relative to a transient EGF effect. In contrast, the differentiation factor bFGF failed to induce measurable tyrosine phosphorylation of PI‐3 kinase‐associated proteins. Similarly, NGF but not bFGF induced marked tyrosine phosphorylation of PLCγ, another early signaling molecule, suggesting that multiple pathways exist for promoting differentiation, and/or that these signaling molecules are not essential for differentiation. TrkA signaling was also compared between PC 12 cells and NIH‐3T3 cells heterologously expressing trkA, where receptor activation promotes mitogenesis. In this comparison, significant differences were observed in the tyrosine phosphorylation pattern of PI‐3 kinase‐associated polypeptides, suggesting the existence of cell type‐specific molecular interactions influencing trkA signaling. Mechanistically, NGF stimulation of PC12 cells resulted in a weak or possibly indirect association between trkA and PI‐3 kinase. Furthermore, NGF did not appear to activate or substantially alter the overall level of PI‐3 kinase activity, raising the possibility that ligand‐induced phosphorylation may serve instead to relocalize constitutively active PI‐3 kinase molecules within the cell. Taken together, data presented suggest that the temporal pattern of induced phosphorylation, the nature of induced associations with other phosphoproteins, and cell type‐specific components may all contribute to the generation of NGF signaling specificity. © 1995 Wiley‐Liss, Inc.
Global statistics on addictive behaviours: 2014 status report.

BACKGROUND AND AIMS Addictive behaviours are among the greatest scourges on humankind. It is important to estimate the extent of the problem globally and in different geographical regions. Such estimates are available, but there is a need to collate and evaluate these to arrive at the best available synthetic figures. Addiction has commissioned this paper as the first of a series attempting to do this. METHODS Online sources of global, regional and national information on prevalence and major harms relating to alcohol use, tobacco use, unsanctioned psychoactive drug use and gambling were identified through expert review and assessed. The primary data sources located were the websites of the World Health Organization (WHO), the United Nations Office on Drugs and Crime (UNODC) and the Alberta Gambling Research Institute. Summary statistics were compared with recent publications on the global epidemiology of addictive behaviours. RESULTS An estimated 4.9% of the world's adult population (240 million people) suffer from alcohol use disorder (7.8% of men and 1.5% of women), with alcohol causing an estimated 257 disability-adjusted life years lost per 100 000 population. An estimated 22.5% of adults in the world (1 billion people) smoke tobacco products (32.0% of men and 7.0% of women). It is estimated that 11% of deaths in males and 6% of deaths in females each year are due to tobacco. Of 'unsanctioned psychoactive drugs', cannabis is the most prevalent at 3.5% globally, with each of the others at < 1%; 0.3% of the world's adult population (15 million people) inject drugs. Use of unsanctioned psychoactive drugs accounts for an estimated 83 disability-adjusted life years lost per 100 000 population. Global estimates of problem gambling are not possible, but in countries where it has been assessed the prevalence is estimated at 1.5%. CONCLUSIONS Tobacco and alcohol use are by far the most prevalent addictive behaviours and cause the large majority of the harm. However, the quality of data on prevalence and addiction-related harms is mostly low, and comparisons between countries and regions must be viewed with caution. There is an urgent need to review the quality of data on which global estimates are made and coordinate efforts to arrive at a more consistent approach.
Affective networks: how WeChat enhances Tencent’s digital business governance

An emerging body of literature has revealed that social media enhance digital business governance to facilitate Internet companies in generating profit throughout regulating the everyday lives of users. However, although existing debates are often contextualized in the West, little attention has been paid to China, where social media are widely used. To fill this knowledge gap, this article investigates the digital business governance practiced by Chinese Internet companies such as Tencent. Specifically, I employ an affective lens to analyze how WeChat, the most popular social media application launched by Tencent, allows this Internet company to influence users for its own business purposes. Chinese college students, which constitute a representative group of young people, were early adopters of WeChat, and they have led the trend of social media use in China. Based on a yearlong netnographic study of Chinese college students, the results reveal that the affective design of WeChat captured their attention and influenced their everyday practices. These results provide insight into how digital business governance operates in the Chinese context, in which authoritarianism and capitalism work closely together.
Methods for the analysis of histone H3 and H4 acetylation in blood

LBH589 is one of the many histone deacetylase inhibitors (HDACi) that are currently in clinical trial. Despite their wide-spread use, there is little literature available describing the typical levels of histone acetylation in untreated peripheral blood, the treatment and storage of samples to retain optimal measurement of histone acetylation nor methods by which histone acetylation analysis may be monitored and measured during the course of a patient’s treatment. In this study, we have used cord or peripheral blood as a source of human leukocytes, performed a comparative analysis of sample processing methods and developed a flow cytometric method suitable for monitoring histone acetylation in isolated lymphocytes and liquid tumors. Western blotting and immunohistochemistry techniques have also been addressed. We have tested these methods on blood samples collected from four patients treated with LBH589 as part of an Australian Children’s Cancer Clinical Trial (CLBH589AAU03T) and show comparable results when comparing in vitro and in vivo data. This paper does not seek to correlate histone acetylation levels in peripheral blood with clinical outcome but describes methods of analysis that will be of interest to clinicians and scientists monitoring the effects of HDACi on histone acetylation in blood samples in clinical trials or in related research studies.
Factors associated with bacteriological cure after dry cow treatment of subclinical staphylococcal mastitis with antibiotics.

Data from five dry cow antibiotic therapy trials were analyzed. Records were only included for cows with > or = 1 culture-positive quarters that were subclinically infected with Staphylococcus aureus. Data for 406 quarters affected with S. aureus from 283 cows on 73 farms were analyzed for quarters, cows, and herds. The probability of cure of an infected quarter decreased when SCC increased, when another quarter was infected in the same cow, when the infection was in a hind quarter, and when the percentage of samples that were positive for S. aureus was higher before drying off. Variables predicting complete bacteriological cure of a cow were log SCC, age of the cow, and the number of infected quarters. The probability of a cure decreased as SCC increased. The probability of cure decreased as age increased, and cows with more than one quarter infected were . 57 times less likely to be cured than cows with 1 infected quarter.
Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management

Purpose Despite the variety of supply chain management (SCM) research, little attention has been given to the use of Big Data Analytics for increased information exploitation in a supply chain. The purpose of this paper is to contribute to theory development in SCM by investigating the potential impacts of Big Data Analytics on information usage in a corporate and supply chain context. As it is imperative for companies in the supply chain to have access to up-to-date, accurate, and meaningful information, the exploratory research will provide insights into the opportunities and challenges emerging from the adoption of Big Data Analytics in SCM. Design/methodology/approach Although Big Data Analytics is gaining increasing attention in management, empirical research on the topic is still scarce. Due to the limited availability of comparable material at the intersection of Big Data Analytics and SCM, the authors apply the Delphi research technique. Findings Portraying the emerging transition trend from a digital business environment, the presented Delphi study findings contribute to extant knowledge by identifying 43 opportunities and challenges linked to the emergence of Big Data Analytics from a corporate and supply chain perspective. Research limitations/implications These constructs equip the research community with a first collection of aspects, which could provide the basis to tailor further research at the nexus of Big Data Analytics and SCM. Originality/value The research adds to the existing knowledge base as no empirical research has been presented so far specifically assessing opportunities and challenges on corporate and supply chain level with a special focus on the implications imposed through Big Data Analytics.
Modified DC-link voltage balancing algorithm for a 3-level neutral point clamped (NPC) traction inverter based electric vehicle PMSM drive

This paper presents a modified DC bus voltage balancing algorithm for a neutral-point clamped (NPC) three-level inverter based motor drives for permanent magnet synchronous machines (PMSM) used in electric vehicle applications. The topology used for DC bus voltage balancing is based on nearest three vectors (N3V) with a space vector pulse width modulation scheme (SV-PWM). In this scheme, the voltage space vectors are rearranged based on the four redundant small voltage vectors, to keep the two DC link capacitor voltages in their specific tolerance bands, even during fast transient conditions of the machine. This topology provides high stability and lower switching loss compared to the conventional N3V scheme. The performance of the proposed scheme is verified by simulation and hardware experimental tests.
STOCHASTIC PROGRAMMING MODEL FOR SUPPLY CHAIN DESIGN WITH SHORT RESPONSE TIME AND HEURISTIC

This research studies the impact of demand uncertainty to the supply chain design by using a stochastic programming approach. Each potential location has two modes of supply: long response time used before the demand is realized and short response lead time mode (with higher cost) used after the demand is realized. The capacity of each model will be optimally determined from the model. This means that each location allow the manufacturer to install machines to produce in a large quantity at low cost (due to economy of scale) and keep in the internal warehouse or to install flexible rapid response machines to produce with short lead time at high cost after the demand shortage is expected. Moreover, the model allows different production cost functions which the unit cost could be different when production quantity is different using piecewise function. A stochastic programming model is developed to handle the situation explained. We have conducted 4 experiments to test the model in different perspective; (1) Sampling test – to test the effect of the sample size to the result, (2) Parameter variation – to test how each variable affect the results, (3) Cost function testing – to reveal the property of different cost function and (4) Pair-T test to prove how short LT response facility could improve certain situation and mitigate the effect of demand uncertainty. Furthermore, for heuristic part, we applied linear relaxation and decomposition method on two binary variables to separate the model into two phases; (1) Location decision and (2) Segmentation decision. For the result, heuristic model affords to contribute the optimal result for about 26 out of 32 instances or 81.25% of the total number of computable instances deriving from every cost function. The average overall total profit gap is 0.32%. The average computational time reduction is 71.65%. Moreover, our heuristics model is able to solve big size problems which the optimal model failed to do within acceptable time.
Exchange Rate Risk, Political Environment and Chinese Outward FDI in Emerging Economies: A Panel Data Analysis

This study attempts to investigate the effect of financial and political risk on Chinese outward FDI activities in 56 emerging economies for a period from 2003 to 2013. Exchange rate is taken as a main indicator of financial risks and political risks are evaluated using ICRG (International Country Risk Guide) index. Generalized method of moments with panel data of Chinese outward FDI (foreign direct investment) in new emerging economies is used to find how Chinese firms intend to invest abroad with respect to exchange rate level, volatility, and expectation. The major findings show that RMB appreciation proved to have a positive effect on Chinese outward FDI in emerging economies. But Chinese OFDI (outward foreign direct investment) seems not to respond to exchange rate volatility. The expectation of RMB’s appreciation has positive effect on Chinese OFDI in emerging economies. Results also show that more political risk leads to more Chinese OFDI in emerging economies.
Antepartum and postpartum exposure to maternal depression: different effects on different adolescent outcomes.

BACKGROUND Postpartum depression (PPD) is considered a major public health problem that conveys risk to mothers and offspring. Yet PPD typically occurs in the context of a lifelong episodic illness, and its putative effects might derive from the child's exposure to other episodes, in pregnancy or later childhood. The aim of the study is to test two hypotheses: (1) that the effects of PPD on adolescent outcomes are partly explained by antepartum depression (APD) and (2) that the effects of APD and PPD are both explained by later exposure to the mother's depression. METHOD A random sample of 178 antenatal patients was drawn from two general medical practices in South London; 171 gave birth to live infants, and 150 (88%) were assessed at 3 months post partum, with 121 of their offspring (81%) assessed for emotional disorders (ED), disruptive behaviour disorders (DBD) and IQ, at 11 and 16 years of age. RESULTS When APD and subsequent episodes of depression were taken into account, PPD had a significant effect on adolescent IQ, especially for boys, but did not predict psychopathology. ED and DBD in adolescence were predicted by the extent of exposure to maternal depression after 3 months post partum; a significant effect of APD on ED in girls was accounted for by later exposure to the mother's illness. Mothers' symptoms of anxiety, smoking and alcohol use in pregnancy did not predict adolescent outcomes, once maternal depression was taken into account. CONCLUSIONS Some effects attributed to mothers' mental health problems in pregnancy or post partum may be mediated by cumulative exposure to maternal illness, probably reflecting genetic influence and gene-environment correlation. However, PPD has a direct effect on cognition. Clinicians should endeavour to identify women with depression in pregnancy (31% of this sample) and help them to manage their lifelong illness.
Radiolabeled antibodies directed at CD45 for conditioning prior to allogeneic transplantation in acute myeloid leukemia and myelodysplastic syndrome

While allogeneic hematopoietic cell transplantation (HCT) may offer the best chance of cure for patients suffering from aggressive hematological malignancies such as acute myeloid leukemia, acute lymphoblastic leukemia, and myelodysplastic syndrome, successful outcomes for the subgroup of patients with high-risk disease remain disappointing and lag behind those of lower-risk patients. Because relatively high rates of relapse are an important contributor to these poor outcomes, efforts have explored approaches to increase the cytotoxic effects of treatment. Relapse rates have been shown to improve with the addition of increased doses of total body irradiation (TBI) and/or the introduction of additional chemotherapy to a HCT conditioning regimen. However, the increase in TBI dose and/or additional chemotherapy has also been associated with a significant increase in life-threatening toxicities, resulting in no change in overall survival. Radioimmunotherapy (RIT) has been employed as an adjunct to HCT where targeted delivery of radiation may allow for further escalation of therapy to reduce relapse with minimal toxicity. In this review we describe these efforts, including the benefits of escalating the dose of radiation to sites of hematologic disease prior to HCT, the various cellular targets for antibody-mediated delivery of radiation, as well as the rationale for incorporation of various radionuclides such as alpha emitters and beta emitters into the preparative regimen prior to HCT. Lastly, newer novel approaches such as pretargeted RIT (PRIT) are described as a method to further increase delivery of targeted radiation to hematological tissues while sparing noninvolved organs.
Survey design for precise fire management conservation targets.

Common goals of ecological fire management are to sustain biodiversity and minimize extinction risk. A novel approach to achieving these goals determines the relative proportions of vegetation growth stages (equivalent to successional stages, which are categorical representations of time since fire) that maximize a biodiversity index. The method combines data describing species abundances in each growth stage with numerical optimization to define an optimal growth-stage structure that provides a conservation-based operational target for managers. However, conservation targets derived from growth-stage optimization are likely to depend critically on choices regarding input data. There is growing interest in the use of growth-stage optimization as a basis for fire management, thus understanding of how input data influence the outputs is crucial. Simulated data sets provide a flexible platform for systematically varying aspects of survey design and species inclusions. We used artificial data with known properties, and a case-study data set from southeastern Australia, to examine the influence of (1) survey design (total number of sites and their distribution among growth stages) and (2) species inclusions (total number of species and their level of specialization) on the precision of conservation targets. Based on our findings, we recommend that survey designs for precise estimates would ideally involve at least 80 sites, and include at least 80 species. Greater numbers of sites and species will yield increasingly reliable results, but fewer might be sufficient in some circumstances. An even distribution of sites among growth stages was less important than the total number of sites, and omission of species is unlikely to have a major influence on results as long as several species specialize on each growth stage. We highlight the importance of examining the responses of individual species to growth stage before feeding survey data into the growth-stage optimization black box, and advocate use of a resampling procedure to determine the precision of results. Collectively, our findings form a reproducible guide to designing ecological surveys that yield precise conservation targets through growth-stage optimization, and ultimately help sustain biodiversity in fire-prone systems.
Resistance Drift Model for Conductive-Bridge (CB) RAM by Filament Surface Relaxation

The conductive-bridge random access memory (CBRAM) appears as one of the most promising emerging device due to its remarkable low-power programming, extremely fast switching and scalability. The large resistance window and programmed state controllability may allow for efficient multilevel cell (MLC) operation. However, physical models for CBRAM switching and reliability need to be developed for MLC operation and scaling. This work addresses switching and reliability characteristics of CBRAM. Characterization by two different techniques evidences a size-dependent drift of the resistance of the conductive filament (CF) in the set state. Resistance drift is interpreted in terms of surface relaxation due to charged-defect rearrangement. An analytical model for CBRAM drift is thus developed, allowing for state-dependent drift prediction in CBRAM.
[The tinnitus questionnaire. A standard instrument for grading the degree of tinnitus. Results of a multicenter study with the tinnitus questionnaire].

The clinical examination of patients with severe and chronic tinnitus must include associated psychological disturbances. The present paper describes traditional diagnostic methods of ENT practice as well as the Tinnitus Questionnaire (TQ) which has been evaluated in a number of studies. This instrument differentiates between emotional and cognitive distress, auditory perceptual difficulties and self-experienced intrusiveness produced by the tinnitus. The results of a German multicenter study are presented which show that the TQ can be used to demonstrate differences of tinnitus distress under different clinical conditions (e.g., ENT clinic vs psychosomatic clinic and in- vs out-patient care). The TQ can be employed for comparative studies in different tinnitus-related institutions and for the evaluation of the relative effects of different treatment approaches.
Response of wheat growth characteristics to various tillage practices and sowing methods under semi arid environment

Field experiments were conduct ed at the research farm of TheUniversity of Agriculture Peshawar, Khyber Pakhtunkhwa,Pakistanduring 2009 -2010 and 2010-2011, to study the effect of tillage practices and sowing methods on emergence, number of tillers, plant height,spike length ,and harvest index of wheat under Randomize Complete Block Design (RCBD) with split plot arrangement replicated fourtimes.Tillage practices consistedofTine Cultivator twice (TC-2), Chisel plow followed by rotavator (CR), Mouldboard plow followed by rotavator (MR), Dis c plow followed by rotavator (DR) and Tine Cultivator followed by rotavator(TCR) assigned to main plots, while sowing methods included broadcast (BC) and drilling, (Single box seed drill (SD) and Combined drill (CD) assigned to sub plots. Statistical analysis of the two year data revealed that tillage practices had significant effect on number of tillers, and non significant effect on emergence, plant height, spikelengthand harvest index. Similarly the effect of sowing methods was significant for emergence, number of tillers, spike length and harvest index. The data revealed that maximum emergence m -2 number of tillersm -2 and harvest index was recorded in the plots tilled with tillage implements followed by rotavator as compared to the sole used of tine culti vator twice (TC-2). Similarly sowing by drills produced maximum emergence m -2 , number of tillers m -2 , spike length and harvest index (%) as compared to broadcasting. It is concluded from the results that tillage implements followed by rotavator combination performed well and should be used for tillage practices and sowing by drill method should be used to improve emergence, number of tillers, spike length and harvest index of wheat in arid environment .