The Effect of Consumer Behaviour on the Life Cycle Assessment of Energy Efficient Lighting Technologies

AbstractEnergy efficient lamps offer significant energy savings throughout their life. However, there is a variety of energy saving lamps available and it is unclear which impacts the environment least throughout the lifecycle under different use patterns. Different use patterns have a significant impact on the lifetime of each light globe alternative and therefore affect the life cycle impact of each globe.This paper undertakes a series of Life Cycle Assessments on two alternative lighting choices (Light Emitting Diodes and Compact Florescent Lamps) under a range of use conditions. It was found that the environmental impacts were comparable for CFLs and LEDs, though significantly less than traditional incandescent, for a range of different use cases. The sensitivity analysis carried out shows that the variation in lamp parameters has a far greater effect on the lifecycle impact rather than the use patterns

Germline-Competent Mouse-Induced Pluripotent Stem Cell Lines Generated on Human Fibroblasts without Exogenous Leukemia Inhibitory Factor

Induced pluripotent stem (iPS) cells have attracted enormous attention due to their vast potential in regenerative medicine, pharmaceutical screening and basic research. Most prior established iPS cell lines were derived and maintained on mouse embryonic fibroblast (MEF) cells supplemented with exogenous leukemia inhibitory factor (LIF). Drawbacks of MEF cells impede optimization as well as dissection of reprogramming events and limit the usage of iPS cell derivatives in therapeutic applications. In this study, we develop a reproducible protocol for efficient reprogramming mouse neural progenitor cells (NPCs) on human foreskin fibroblast (HFF) cells via retroviral transfer of human transcriptional factors OCT4/SOX2/KLF4/C-MYC. Two independent iPS cell lines are derived without exogenous LIF. They display typical undifferentiated morphology and express pluripotency markers Oct4 and Sox2. Transgenes are inactivated and the endogenous Oct4 promoter is completely demethylated in the established iPS cell lines, indicating a fully reprogrammed state. Moreover, the iPS cells can spontaneously differentiate or be induced into various cell types of three embryonic germ layers in vitro and in vivo when they are injected into immunodeficient mice for teratoma formation. Importantly, iPS cells extensively integrate with various host tissues and contribute to the germline when injected into the blastocysts. Interestingly, these two iPS cell lines, while both pluripotent, exhibit distinctive differentiation tendencies towards different lineages. Taken together, the data describe the first genuine mouse iPS cell lines generated on human feeder cells without exogenous LIF, providing a reliable tool for understanding the molecular mechanisms of nuclear reprogramming

Thymopentin (TP5), an immunomodulatory peptide, suppresses proliferation and induces differentiation in HL-60 cells

AbstractThymopentin (Arg–Lys–Asp–Val–Tyr, TP5) has shown immuno-regulatory activities in humans. In the present study, we investigated the effects of TP5 on the proliferation and differentiation of a human promyelocyte leukemia cell line, HL-60. It is noteworthy that TP5 displayed concentration-dependent inhibitory effects on the proliferation and colony formation of HL-60 cells. Furthermore, the decrease or even disappearance of AgNORs from nucleoli was observed in HL-60 cells after the treatment with TP5. The suppression induced by TP5 was accompanied by an accumulation of cell cycle in the G0/G1 phase. Moreover, TP5 significantly increased the NBT-reduction activity of HL-60 cells. Cytofluorometric and morphologic analysis indicated that TP5 had induced differentiation along the granulocytes lineage in HL-60 cells. d-tubocurarine (TUB) significantly antagonized the inhibitory effects induced by TP5, whereas atropine did not exhibit such effect. All the results indicated that TP5 was able to significantly inhibit proliferation and induce differentiation in HL-60 cells. Our observations also implied that TP5 not only acted as an immunomodulatory factor in cancer chemotherapy, but is also a potential chemotherapeutic agent in the human leukemia therapy

The Effects of Modified Simiao Decoction in the Treatment of Gouty Arthritis: A Systematic Review and Meta-Analysis

The modified Simiao decoctions (MSD) have been wildly applied in the treatment of gouty arthritis in China. However, the evidence needs to be evaluated by a systematic review and meta-analysis. After filtering, twenty-four randomised, controlled trials (RCTs) comparing the effects of MSD and anti-inflammation medications and/or urate-lowering therapies in patients with gouty arthritis were included. In comparison with anti-inflammation medications, urate-lowering therapies, or coadministration of anti-inflammation medications and urate-lowering therapies, MSD monotherapy significantly lowered serum uric acid (p<0.00001, mean difference = −90.62, and 95% CI [−128.38, −52.86]; p<0.00001, mean difference = −91.43, and 95% CI [−122.38, −60.49]; p=0.02, mean difference = −40.30, and 95% CI [−74.24, −6.36], resp.). Compared with anti-inflammation medications and/or urate-lowering therapies, MSD monotherapy significantly decreased ESR (p<0.00001; mean difference = −8.11; 95% CI [−12.53, −3.69]) and CRP (p=0.03; mean difference = −3.21; 95% CI [−6.07, −0.36]). Additionally, the adverse effects (AEs) of MSD were fewer (p<0.00001; OR = 0.08; 95% CI [0.05, 0.16]). MSD are effective in the treatment of gouty arthritis through anti-inflammation and lowering urate. However, the efficacy of MSD should be estimated with more RCTs

The role of the transcription factor Rbpj in the development of dorsal root ganglia

<p>Abstract</p> <p>Background</p> <p>The dorsal root ganglion (DRG) is composed of well-characterized populations of sensory neurons and glia derived from a common pool of neural crest stem cells (NCCs), and is a good system to study the mechanisms of neurogenesis and gliogenesis. Notch signaling is known to play important roles in DRG development, but the full scope of Notch functions in mammalian DRG development remains poorly understood.</p> <p>Results</p> <p>In the present study, we used <it>Wnt1-Cre </it>to conditionally inactivate the transcription factor Rbpj, a critical integrator of activation signals from all Notch receptors, in NCCs and their derived cells. Deletion of <it>Rbpj </it>caused the up-regulation of <it>NeuroD1 </it>and precocious neurogenesis in DRG early development but led to an eventual deficit of sensory neurons at later stages, due to reduced cell proliferation and abnormal cell death. In addition, gliogenesis was delayed initially, but a near-complete loss of glia was observed finally in <it>Rbpj</it>-deficient DRG. Furthermore, we found P75 and Sox10, which are normally expressed exclusively in neuronal and glial progenitors of the DRG after the NCCs have completed their migration, were co-expressed in many cells of the DRG of <it>Rbpj </it>conditional knock-out mice.</p> <p>Conclusions</p> <p>Our data indicate that Rbpj-mediated canonical Notch signaling inhibits DRG neuronal differentiation, possibly by regulating <it>NeuroD1 </it>expression, and is required for DRG gliogenesis <it>in vivo</it>.</p

An integrated hydrodynamics and control model of a tethered underwater robot

An integrated hydrodynamics and control model to simulate tethered underwater robot system is proposed. The governing equation of the umbilical cable is based on a finite difference method, the hydrodynamic behaviors of the underwater robot are described by the six-degrees-of-freedom equations of motion for submarine simulations, and a controller based on the fuzzy sliding mode control (FSMC) algorithm is also incorporated. Fluid motion around the main body of moving robot with running control ducted propellers is governed by the Navier–Stokes equations and these nonlinear differential equations are solved numerically via computational fluid dynamics (CFD) technique. The hydrodynamics and control behaviors of the tethered underwater robot under certain designated trajectory and attitude control manipulation are then investigated based on the established hydrodynamics and control model. The results indicate that satisfactory control effect can be achieved and hydrodynamic behavior under the control operation can be observed with the model; much kinematic and dynamic information about tethered underwater robot system can be forecasted, including translational and angular motions of the robot, hydrodynamic loading on the robot, manipulation actions produced by the control propellers, the kinematic and dynamic behaviors of the umbilical cable. Since these hydrodynamic effects are fed into the proposed coupled model, the mutual hydrodynamic influences of different portions of the robot system as well as the hydrological factors of the undersea environment for the robot operation are incorporated in the model

On the Complexity of Bayesian Generalization

We consider concept generalization at a large scale in the diverse and natural visual spectrum. Established computational modes (i.e., rule-based or similarity-based) are primarily studied isolated and focus on confined and abstract problem spaces. In this work, we study these two modes when the problem space scales up, and the $complexity$ of concepts becomes diverse. Specifically, at the $representational \ level$, we seek to answer how the complexity varies when a visual concept is mapped to the representation space. Prior psychology literature has shown that two types of complexities (i.e., subjective complexity and visual complexity) (Griffiths and Tenenbaum, 2003) build an inverted-U relation (Donderi, 2006; Sun and Firestone, 2021). Leveraging Representativeness of Attribute (RoA), we computationally confirm the following observation: Models use attributes with high RoA to describe visual concepts, and the description length falls in an inverted-U relation with the increment in visual complexity. At the $computational \ level$, we aim to answer how the complexity of representation affects the shift between the rule- and similarity-based generalization. We hypothesize that category-conditioned visual modeling estimates the co-occurrence frequency between visual and categorical attributes, thus potentially serving as the prior for the natural visual world. Experimental results show that representations with relatively high subjective complexity outperform those with relatively low subjective complexity in the rule-based generalization, while the trend is the opposite in the similarity-based generalization

Industrial Internet of Learning (IIoL): IIoT based Pervasive Knowledge Network for LPWAN – concept, framework and case studies

Industrial Internet of Things (IIoT) is performed based on the multiple sourced data collection, communication, management and analysis from the industrial environment. The data can be generated at every point in the manufacturing production process by real-time monitoring, connection and interaction in the industrial field through various data sensing devices, which creates a big data environment for the industry. To collect, transfer, store and analyse such a big data efficiently and economically, several challenges have imposed to the conventional big data solution, such as high unreliable latency, massive energy consumption, and inadequate security. In order to address these issues, edge computing, as an emerging technique, has been researched and developed in different industries. This paper aims to propose a novel framework for the intelligent IIoT, named Industrial Internet of Learning (IIoL). It is built using an industrial wireless communication network called Low-power wide-area network (LPWAN). By applying edge computing technologies in the LPWAN, the high-intensity computing load is distributed to edge sides, which integrates the computing resource of edge devices to lighten the computational complexity in the central. It cannot only reduce the energy consumption of processing and storing big data but also low the risk of cyber-attacks. Additionally, in the proposed framework, the information and knowledge are discovered and generated from different parts of the system, including smart sensors, smart gateways and cloud. Under this framework, a pervasive knowledge network can be established to improve all the devices in the system. Finally, the proposed concept and framework were validated by two real industrial cases, which were the health prognosis and management of a water plant and asset monitoring and management of an automobile factory