Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Fasting on the Effects of Ischemic Preconditioning in the Ischemic-Reperfused Rat Heart

The effects of fasting and ischemic preconditioning (IP) on heart function of Langendorff-perfused rat hearts exposed to 25min global ischemia plus 30min reperfusion (RP), were correlated with lactate release and tissue-levels of long-chain acyl carnitine (LCCa) and CoA (LCCoA). IP was achieved by a 3min ischemia plus a 5min reperfusion cycle. Creatine kinase leakage was measured to assess the extent of cardiac injury. Fasting reduced the ischemic-induced contracture, improved RP recovery of mechanical function, reduced lactate release and increased the end-ischemia LCCoA and LCCa levels. Both in the fed and the fasted rat hearts IP delayed the pacemaker depression, reduced the amplitude of ischemic contracture and improved the RP recovery of contraction. However, IP reduced creatine kinase and lactate release only in the fed rat hearts. IP had no effects on tissue LCCa and LCCoA in both groups. These data suggest that: 1) beneficial effects of fasting may be ascribed, at least in part, to a reduced lactate production which may attenuate ischemic myocyte acidification and to the accumulation of fatty acyl esters which would favour citric acid cycle replenishment during RP. 2) beneficial effects of IP could be in part explained by the reduction of lactate production in the fed group although data obtained with the fasted rat heart indicate that another mechanisms must also be involved in the effects of IP. 3) accumulation of LCCoA and LCCa is not involved in the noxious effects of ischemia as well as in the protection effected by IP.
Peningkatan Kinerja dalam Pengklasifikasian Menggunakan Deep Learning

Deep Learning is a new paradigm in machine learning area, one of its methodologies is Deep Neural Network. Deep neural network (DNN) is a method that can solve the problem such as classification. However, in solving classification problem using a standard deep neural network in some cases is still relatively slow. Therefore, we need additional scheme to optimize and improve the accuracy and performance for DNN data classification. One of the optimization techniques is adaptive learning rate. This study analyzed the method of deep neural network standard, and deep neural network with adaptive learning rate – RMSProp using mangrove classification data. The experimental result shows DNN with RMSProp produce an error value of 0.0824 and 98.30% accuracy in the 100th epoch, and data testing accuracy equal to 98.00% at 100th epoch. While the results of DNN get the lowest error of 0.1027 and 97.80% accuracy on the 1000th epoch, 97.70% accuracy result in the 1000th epoch.
CT-guided percutaneous needle biopsy of the chest: preprocedural evaluation and technique.

Indications Percutaneous needle biopsy of the lung is indicated for indeterminate pulmonary nodules or masses, particularly those that will likely require chemotherapy or radiation rather than surgery, and in patients with a history of extrapulmonary malignancy. Because targeted therapy has now become an important part of the armamentarium for treatment of lung cancer, percutaneous needle biopsy of the lung is also performed to obtain tissue for molecular testing. Recent studies have confirmed that epidermal growth factor receptor (EGFR) mutations seen in lung cancer patients can be detected from fine-needle aspiration specimens, thereby helping to identify patients who would benefit from EGFR tyrosine kinase inhibitors [6, 7]. Similarly, other information, such as estrogen and progesterone receptor status of breast cancer metastases, also can be ascertained by percutaneous needle biopsy of the lung. The procedure is also useful for obtaining samples for the diagnosis of focal pulmonary infection. Mediastinal, pleural, and chest wall lesions also are frequently accessible by needle biopsy.
Update on Diagnosis and Management of Early Stage Diabetic Kidney Disease

Diabetes mellitus is the most common cause of end stage kidney disease (ESKD) that needs renal replacement therapy (dialysis or kidney transplantation) to sustain life. There is also increased cardiovascular morbidity and mortality in patients with diabetic kidney disease (DKD). In this review article, the diagnosis and the updated different approaches used in the management of early stage DKD has been focused. Various international/ national guidelines and relevant literatures that were published through January 2001 to January 2019 for the recommendations on the diagnosis and management of DKD were reviewed. The benefits of multifactorial interventions in the management of people with early stage DKD to prevent and slow the progression to ESKD, has been clearly demonstrated. Recent studies reveal that some antidiabetic drugs have renoprotective effect evidenced by reduction in albuminuria and improvement in renal function; therefore, they are currently recommended in the management of DKD.
Comparison of SLA based Energy Efficient Dynamic Virtual Machine Consolidation Algorithms

Cloud computing emerged as need for rapidly increasing computational power thus results in greater power consumption, increased operational costs and high carbon footprints to environment. A key issue for Cloud Providers is to maximize their profits by minimizing power consumption along with SLA considerations of hosted applications. Dynamic Virtual Machine (VM) consolidation is promising approach for reducing energy consumption by dynamically adjusting the number of active machines to match resource demands but it is one of the most important challenges in the cloud based distributed systems. In this work, the researchers tried to investigate “SLA and Energy-Efficient Dynamic Virtual Machine (VM) Consolidation” that meets Quality of Service expectations and Service Level Agreements (SLA) requirements. The analysis of VM consolidation algorithms based on various heuristics on legitimate host is presented as key contribution of this work. We also present a comparative analysis and results by conducting a performance evaluation study of various existing energy efficient VM consolidation techniques using real world workload traces from more than a thousand VMs using CloudSim toolkit. This paper is aimed at helping cloud providers analyze several power characteristics of their own technologies as well as pre-existing IT resources to identify their favorability in the migration to the new energy efficient cloud architectures. The results also helps in analyzing the existing frameworks and offers substantial energy savings while effectively dealing with firm QoS requirements negotiated by SLA. General Terms Cloud Computing, Cloud Provider, Energy Efficiency, SLA, Virtual Machine Consolidation,
Cytokine Release from Osteoblasts in Response to Different Intensities of Pulsed Electromagnetic Field Stimulation

We use an in-vitro osteoblast cell culture model to investigate the effects of low-frequency (7.5 Hz) pulsed electromagnetic field (PEMF) stimulation on osteoblast population, cytokines (prostaglandin E2 (PGE2), transforming growth factor β1(TGFβ1), and alkaline phosphatase (ALP) activity to find the optimal intensity of PEMF for osteoblast growth. The results demonstrate that PEMF can stimulate osteoblast growth, release of TGFβ1, and, in addition, an increase of ALP activity. The synthesis and release of PGE2 in the culture medium are reduced with increasing numbers of cells. Higher intensity does not necessarily mean increased osteoblast growth, and the most efficient intensity is about 2 mV/cm in this case. Although the lower intensities of the PEMF are yet to be determined, the results of this study can shed light on the mechanisms of PEMF stimulation on non union fracture therapy and osteoporosis prevention in the future.
Dependency relation analysis using case frame for encyclopedia question-answering system

One of the principal challenges of natural language processing is a natural language parsing. In this paper, we suggest a dependency parsing approach based on case frame with chunk, distance information, existence of case, and clausal information for encyclopedia QA system. Because we cannot construct case frames for all verbs, we use distance information, existence of case, and clausal information for the absence of case frame. In addition to dependency parsing, we use post-processing for applying to Korean encyclopedia QA system.
A Planarized Thermophotovoltaic Emitter With Idealized Selective Emission

Compared with conventional solar cells, thermophotovoltaics (TPV) can be more efficient and, thus, exceeds the detailed balance efficiency limit. In particular, the emitter of TPV is a critical design since it determines whether the thermalization loss can be reduced and whether the sub-band-gap radiation can be suppressed, as far as the photovoltaic (PV) process is concerned. In this paper, we propose a selective planar emitter composed of alternating ultrathin metal and dielectric layers. An aperiodic dielectric stacking is designed to tailor the emission spectrum by shaping the emission peak and by adjusting the emission wavelength. We show that the peak emission wavelength (λemission) is adjustable from λ = 1500 nm to λ = 2500 nm. Furthermore, the long-wavelength cutoff is very sharp for our proposed emitter structure, and the absorption is suppressed to 0.1 beyond the cutoff. The preliminary experiment is also conducted to fulfill the concept of a fully planar ultrathin refractory metal emitter design, and the result is similar to the calculated ones. We believe that the planar thermal emitter based on ultrathin metals and aperiodic dielectric stacking is very promising for future thermal emission applications since it requires no lithography and etching, provides strong peak emission power, and possesses wide wavelength scalability.
Effects of C-C motif chemokine receptor 2 on phenotypic transformation of cardiac fibroblasts after hypoxia

Objective To investigate the effect of C-C motif chemokine receptor 2 (CCR2) on phenotypic transformation of cardiac fibroblasts after hypoxia. Methods The mouse myocardium primary fibroblasts were extracted by collagenase digestion. Cells were divided into control, hypoxia-24h and hypoxia-48h, the mRNA and protein expression of CCR2 was examined by real-time PCR and Western blotting. CCR2 low expression cell (si-CCR2) was established using by small interfering RNA. Cells were divided into four groups including si-control, si-CCR2, si-control+hypoxia, si-CCR2+hypoxia. The mRNA and protein expressions of CCR2, α smooth muscle actin (α-SMA) and Collagen 1A (Col 1A) were detected by real-time PCR and Western blotting, cell proliferation was detected by Cell Counting Kit-8 (CCK8) and Bromodeoxyuridine (BrdU). Results Compared with control, the mRNA and protein levels of CCR2 significantly increased in hypoxia-24h and hypoxia-48h group (P<0.01), however, no significance was found in these two time points. Compared with si-control group, the mRNA and protein expressions of CCR2, α-SMA and Col 1A not significantly changed in si-CCR2 group. Compared with si-control group, the mRNA and protein levels of CCR2, α-SMA and Col 1A significantly increased in si-control+hypoxia group (P<0.01 or P<0.05), and cell proliferation increased (P<0.01). Compared with si-control+hypoxia group, the protein expression of α-SMA and Col 1A decreased in si-CCR2+hypoxia group (P<0.05), and cell proliferation also decreased in si-CCR2+hypoxia group (P<0.05). Conclusions CCR2 could affect the phenotypic transformation of cardiac fibroblasts after hypoxia. DOI: 10.11855/j.issn. 0577-7402.2019. 01.01
The Metabuffer: A Scalable Multiresolution Multidisplay 3-D Graphics System Using Commodity Rendering Engines

Many computer graphics applications require multiple visu al displays that are rendered in real time. However, dividing and b alancing the rendering workload among a number of CPUs and then sending it to the individual displays efficiently is a difficu lt task. This report details the design and software prototype for a n ovel new type of graphics framebuffer that takes in RGB color, Z or der, and alpha information from multiple COTS rendering eng ines, collages them, and then outputs composited images to multip le displays in a tiled configuration. The individual COTS renderin g engines define their image data as viewports that can be located anywhere in the display space and be of any size/resolution. For example, one graphics board could generate a low-resolution b ackground image spanning multiple displays while other render i g engines could concentrate on more detailed images in the foreg r und. This flexibility lends itself to multiple display virtual re ality arrangements and foveated vision systems. This report detail s the architecture of the Metabuffer and the results from a multit hreaded software prototype written in C++. It shows that the Metabuf fer provides a simple framework to its host PCs for effective uti lization of multiple visual displays using COTS rendering engin es and produces constant time image collaging with a minimum of lat ency regardless of geometry or number of image viewports.
Uncertainty-based Sensor Fusion of Range Data for Real-time Digital Elevation Mapping (RTDEM)

This paper introduces a new computationally inexpensive approach to perception and modeling of the environment that allows fusion of sensory range data of various types and fidelities while explicitly taking into account a complete description of uncertainty of the range measure- ments. This approach makes use of known sensor uncertainty models to create a single 2.5D digital elevation map whose accuracy is robust to sensor noise and spurious data. This approach is particularly suitable for real-time application in high speed and highly unstructured outdoor environments for which reasonably accurate and timely vehicle state es- timates are available. Experimental results are presented in which LADAR range measurements and state estimates are combined according to this approach. We provide qualitative comparison to other classes of environment modeling.
Patterning and cell fate in the inner ear: a case for Notch in the chicken embryo

The development of the inner ear provides a beautiful example of one basic problem in development, that is, to understand how different cell types are generated at specific times and domains throughout embryonic life. The functional unit of the inner ear consists of hair cells, supporting cells and neurons, all deriving from progenitor cells located in the neurosensory competent domain of the otic placode. Throughout development, the otic placode resolves into the complex inner ear labyrinth, which holds the auditory and vestibular sensory organs that are innervated in a highly specific manner. How does the early competent domain of the otic placode give rise to the diverse specialized cell types of the different sensory organs of the inner ear? We review here our current understanding on the role of Notch signaling in coupling patterning and cell fate determination during inner ear development, with a particular emphasis on contributions from the chicken embryo as a model organism. We discuss further the question of how these two processes rely on two modes of operation of the Notch signaling pathway named lateral induction and lateral inhibition.
Efficacy of tranexamic acid in traumatic brain injury: Updated systematic review and meta-analysis

Background and objectives There is weak evidence for the efficacy of tranexamic acid in decreasing traumatic brain injury complications or improving clinical and radiological outcomes. We conducted a systematic review and meta-analysis to update the current evidence and to assess the efficacy of tranexamic acid in different outcomes. Methods A computer literature search of Medline, Web of Science, Scopus, and Cochrane central register of controlled trials was performed to identify relevant articles including only randomized-controlled trials. RevMan 5.3 software was used for data analysis. Results Four randomized-controlled trials were included. All studies were included in the quantitative and qualitative analysis. The analysis showed significant reduction of intracranial hemorrhage growth (progression) events (risk ratio = 0.77; 95% confidence interval 0.61 to 0.98), with no significant difference in reduction of total (volumetric) hemorrhage growth (mean difference = −2.46; 95% confidence interval −6.53 to 1.60; p = 0.23). There was no difference in risk between tranexamic acid and placebo for mortality (risk ratio = 0.64; 95% confidence interval 0.41 to 1), need for neurosurgical intervention (risk ratio = 0.96; 95% confidence interval 0.61 to 1.51), re-bleed (new hemorrhage) (risk ratio = 0.90; 95% confidence interval 0.57 to 1.41), hemorrhagic mass pressure effect on brain tissue (risk ratio = 0.81; 95% confidence interval 0.65 to 1.01), or unfavorable functional status at discharge (risk ratio = 0.78; 95% confidence interval 0.57 to 1.06). Conclusions Tranexamic acid significantly reduced intracranial hemorrhage growth events. There were non-significant results for all other included radiological and clinical outcomes. Large trials are needed for further exploration of the efficacy and proper dosing.
Modelización de la cadena de suministro desde un punto de vista de agente

La tendencia actual hacia la competencia en mercados globales hace cada vez mas necesario sistemas de integracion de la empresa que permitan satisfacer las demandas cambiantes de la forma mas eficiente. Una de las posibles vias es a traves de la cadena de suministro, que agrupa las actividades que van desde las adquisicion de materias primas hasta la distribucion. Esto lleva a tratar de forma integrada la gestion de los procesos de planificacion del conjunto de empresas que constituyen la cadena de suministro. La complejidad que esto tiene hace necesaria la automatizacion de dichos procesos de gestion. Para ello, una de las posibles alternativas es la utilizacion de sistemas multiagente que, por sus propias caracteristicas, nos permiten modelizar de forma natural los procesos generados a lo largo de la cadena de suministro. Se senalan ademas, alguno de los proyectos desarrollados en este campo
Clopidogrel Response Variability and Future Therapies: Clopidogrel: Does One Size Fit All?

Case Presentation: A 75-year-old woman presents to the hospital with a non–ST-elevation myocardial infarction (MI) and is found to have a subtotal occlusion of the proximal left anterior descending coronary artery. A drug-eluting stent is successfully deployed without complication, and the patient is given a 300-mg loading dose of clopidogrel. She is started on a treatment regimen that includes aspirin 325 mg daily and clopidogrel 75 mg daily. On hospital day 4, she develops recurrent chest pain and is found to have ST-segment elevation on ECG. She is taken to coronary angiography, where she is found to have an occlusive thrombus within a well-deployed stent. After percutaneous coronary intervention (PCI), how should this patient be managed? Platelets play a central role in initiating and propagating pathological thrombosis after spontaneous or mechanical plaque rupture. Antiplatelet therapies, including aspirin and thienopyridines, are key components of pharmacotherapy in acute coronary syndromes (ACS) and PCI.1,2 As monotherapy, treatment with clopidogrel modestly reduces cardiovascular (CV) events in patients with established atherosclerotic disease compared with aspirin treatment.3 When combined with aspirin, clopidogrel provides additive reduction in the risk of ischemic events in patients with non–ST-elevation ACS and in patients undergoing PCI.4,5 In addition, clopidogrel helps to maintain infarct-related artery patency and clinical outcomes in patients with ST-elevation MI receiving fibrinolytic therapy.6,7 Clopidogrel, a prodrug, relies on cytochrome P450–dependent pathways to form its active metabolite and inhibits platelet aggregation through irreversible blockade of the platelet P2Y12 receptor (Figure 1). When a 300-mg loading dose is used, clopidogrel requires at least 4 to 6 hours to achieve its maximal effect.8 Analyses from the Clopidogrel for the Reduction of Events During Observation (CREDO) trial suggest that clopidogrel pretreatment 6 to 15 hours before PCI is necessary to significantly reduce CV events.5,9 Clinicians …
Estimating Occupancy from Measurements and Knowledge Using the Bayesian Network for Energy Management

A general approach is proposed to determine occupant behavior (occupancy and activity) in offices and residential buildings in order to use these estimates for improved energy management. Occupant behavior is modelled with a Bayesian network in an unsupervised manner. This algorithm makes use of domain knowledge gathered via questionnaires and recorded sensor data for motion detection, power, and hot water consumption as well as indoor CO2 concentration. Different case studies have been investigated with diversity according to their context (available sensors, occupancy or activity feedback, complexity of the environment, etc.). Furthermore, experiments integrating occupancy estimation and hot water production control show that energy efficiency can be increased by roughly 5% over known optimal control techniques and more than 25% over rule-based control while maintaining the same occupant comfort.
A multi-agent model of human mind based on mental image directed semantic theory for comprehensible communication between humans and robots

Development of robots for practical use has brought the need for more-human friendly intelligent systems. Such an intelligent system should be equipped with a certain model of human mind in order to realize comprehensible communication with humans. Mental image directed semantic theory (MIDST) has proposed a methodology for integrated multimedia information understanding, for example, cross-media translation. This paper describes a multiagent model of human mind based on MIDST and its computer implementation.
Lower-Limb Prostheses and Exoskeletons With Energy Regeneration: Mechatronic Design and Optimization Review

Lower-limb biomechatronic devices (i.e., prostheses and exoskeletons) depend upon onboard batteries to power wearable sensors, actuators, and microprocessors, therein inherently limiting their operating durations. Regenerative braking, also termed electrical energy regeneration, represents a promising solution to the aforementioned shortcomings. Regenerative braking converts the otherwise dissipated mechanical energy during locomotion into electrical energy for recharging the onboard batteries, while simultaneously providing negative mechanical work for controlled system deceleration. This paper reviewed the electromechanical design and optimization of lower-limb biomechatronic devices with electrical energy regeneration. The technical review starts by examining human walking biomechanics (i.e., mechanical work, power, and torque about the hip, knee, and ankle joints) and proposes general design principles for regenerative braking prostheses and exoskeletons. Analogous to electric and hybrid electric vehicle powertrains, there are numerous mechatronic design components that could be optimized to maximize electrical energy regeneration, including the mechanical power transmission, electromagnetic machine, electrical drive, device mass and moment of inertia, and energy storage devices. Design optimization of these system components is individually discussed while referencing the latest advancements in robotics and automotive engineering. The technical review demonstrated that existing systems (1) are limited to level-ground walking applications and (2) have maximum energy regeneration efficiencies between 30% and 37%. Accordingly, potential future directions for research and innovation include (1) regenerative braking during dynamic movements like sitting down and slope and staircase descent and (2) utilizing high-torque-density electromagnetic machines and low-impedance mechanical power transmissions to maximize energy regeneration efficiencies.