Miracle-dz/UniFAR-FTUs huggingface dataset:
LSPI-CAS: Least-Squares Policy Iteration for Compact Action Set MDPs

Simulation-based, model-free solutions to Markov Decision Processes (MDPs) using the algorithm Least Squares Policy Iteration (LSPI) have been applied to multiple practical settings and in several variants. An optimal policy in an MDP is that policy, or a description of which action to take in a state of the MDP, which performs best according to a given metric such as infinite-horizon d iscounted c ost. A s imulation-based a lgorithm f or a n M DP o btains the optimal policy for an MDP in a model-free manner, i.e. without requiring to know apriori any transition probabilities of the MDP under any policy. This work proposes LSPI-CAS, a version of LSPI for compact action-sets, thus avoiding the discretization of the available action set in a state and thereby improving control over the system. Regular LSPI works by repeatedly picking the current best action in a state x from a finite feasible set of actions Ax, requiring finding a minimum over |Ax| values. Our variant uses two kinds of parametrization, a feature vector f(x) for the state called the actor, and ? (x, a) for the state-action pair which is the critic. LSPI-CAS employs a stochastic gradient algorithm called Simultaneous Perturbation Stochastic Approximation (SPSA) to update the actor in each iteration. Regular LSPI has a module named Least-Squares Q-Value (LSQ) which we employ as critic to evaluate perturbed policy iterates, and further update the policy iterate in direction of improving performance. Our algorithm is for infinite-horizon discounted-cost/reward MDPs, the case of finite-horizon compact-action set MDPs having been solved in an earlier work. Numerical results on three settings, a. control of an inverted pendulum, b. Exercise Policy calculation for an American Put option, and c. M/ M/1/K queue control problem are provided for the algorithm, alongside comparison with LSPI. Improvements in both performance and run-time to find an optimal policy are demonstrated.
Aseptic Rearing and Infection with Gut Bacteria Improve the Fitness of Transgenic Diamondback Moth, Plutella xylostella

Mass insect rearing can have a range of applications, for example in biological control of pests. The competitive fitness of released insects is extremely important in a number of applications. Here, we investigated how to improve the fitness of a transgenic diamondback moth, which has shown variation in mating ability when reared in different insectaries. Specifically we tested whether infection with a gut bacteria, Enterobacter cloacae, and aseptic rearing of larvae could improve insect growth and male performance. All larvae were readily infected with E. cloacae. Under aseptic rearing, pupal weights were reduced and there was a marginal reduction in larval survival. However, aseptic rearing substantially improved the fitness of transgenic males. In addition, under aseptic rearing, inoculation with E. cloacae increased pupal weights and male fitness, increasing the proportion of transgenic progeny from 20% to 30% relative to uninfected insects. Aseptic conditions may improve the fitness of transgenic males by excluding microbial contaminants, while symbiont inoculation could further improve fitness by providing additional protection against infection, or by normalizing insect physiology. The simple innovation of incorporating antibiotic into diet, and inoculating insects with symbiotic bacteria that are resistant to that antibiotic, could provide a readily transferable tool for other insect rearing systems.
A novel method of gene regulatory network structure inference from gene knock-out expression data

Inferring Gene Regulatory Networks (GRNs) structure from gene expression data has been a challenging problem in systems biology. It is critical to identify complicated regulatory relationships among genes for understanding regulatory mechanisms in cells. Various methods based on information theory have been developed to infer GRNs. However, these methods introduce many redundant regulatory relationships in the network inference process due to external noise in the original data, topology sparseness in the network structure, and non-linear dependency among genes. Especially as the network size increases, the performance of these methods decreases dramatically. In this paper, a novel network structure inference method named Loc-PCA-CMI is proposed that first identifies local overlapped gene clusters, and then infers the local network structure for each cluster by a Path Consistency Algorithm based on Conditional Mutual Information (PCA-CMI). The final structure of the GRN is denoted as dependence among genes by an ensemble of the obtained local network structures. Loc-PCA-CMI was evaluated on DREAM3 knock-out datasets, and its performance was compared to other information theory-based network inference methods including ARACNE, MRNET, PCA-CMI, and PCA-PMI. Experimental results demonstrate our novel method Loc-PCA-CMI outperforms the other four methods in DREAM3 datasets especially in size 50 and 100 networks.
Dynamic Interaction System Design of Urban Landscape Information Based on PHP Technology

In the transitional period of Urbanization, the urban landscape and its aesthetical experience became one of research priorities. Design and develop professional interactive information system is one of the most important thing for urban landscape design. The research uses PHP as core technology, uses DW which is the integration of MySQL-related technologies as developing tools, to set up a integrated system platform based on Apache, MySQL and PHP. It is a dynamic interactive information system of urban landscape based on Web technologies. This article described the structure and functions of the system, explained design methods of the database and application. The construction and application of the system can integrate landscape information of the transitional period of Urbanization, such as item information, engineering information, education information and artistic information, offer a human-machine interactive communication platform based on P2P mode (point-to-point). It will become innovative power for the development of urban landscape industry.
Biosensors for Epilepsy Management: State-of-Art and Future Aspects

Epilepsy is a serious neurological disorder which affects every aspect of patients’ life, including added socio-economic burden. Unfortunately, only a few suppressive medicines are available, and a complete cure for the disease has not been found yet. Excluding the effectiveness of available therapies, the timely detection and monitoring of epilepsy are of utmost priority for early remediation and prevention. Inability to detect underlying epileptic signatures at early stage causes serious damage to the central nervous system (CNS) and irreversible detrimental variations in the organ system. Therefore, development of a multi-task solving novel smart biosensing systems is urgently required. The present review highlights advancements in state-of-art biosensing technology investigated for epilepsy diseases diagnostics and progression monitoring or both together. State of art epilepsy biosensors are composed of nano-enabled smart sensing platform integrated with micro/electronics and display. These diagnostics systems provide bio-information needed to understand disease progression and therapy optimization timely. The associated challenges related to the development of an efficient epilepsy biosensor and vision considering future prospects are also discussed in this report. This review will serve as a guide platform to scholars for understanding and planning of future research aiming to develop a smart bio-sensing system to detect and monitor epilepsy for point-of-care (PoC) applications.
Effect of single-dose magnesium sulfate on total postoperative analgesic requirement in patients receiving balanced general anesthesia- A prospective, randomized, placebo controlled study

Aim: The aim of this study was to see the effect Single-Dose Magnesium Sulfate on total Postoperative analgesic requirement in patients receiving balanced general anesthesia. Materials and Methods: 100 ASA status I & II patients of age >20 years & < 60 years posted for elective abdominal surgeries under general anaesthesia were randomly allocated into two groups. Group M (n=50) patients were given magnesium sulphate 50 mg/kg in 100 ml NS infused over 10 minutes just prior to induction of balanced general anaesthesia & Group P (n=50) – patients were given 100 ml NS infused over 10 minutes as placebo just prior to induction. Balanced general anaesthesia was given as per preset protocol and intraoperative vitals were recorded at regular intervals. In PACU after complete recovery from anaesthesia NRS score was noted. Tramadol was given when NRS > 4. Total tramadol consumtion over 24 hours after surgery was calculated for each group. Results: In group P post-operativly NRS score was significantly higher in at 6, 12, 18 and 24 hours. Consumption of tramadol was significantly more in group P. Conclusion: Ten minutes before induction of balanced general anaesthesia 50 Mg/Kg magnesium sulphate mixed in 100 ml of normal saline given to alley post-operative pain and significantly reduces post-operative analgesic consumption after open abdominal surgeries.
Disease mortality in domesticated animals is predicted by host evolutionary relationships

Significance Diseases that infect domestic and wild species cause severe human health burdens and exacerbate declines of endangered species. However, we currently lack theory for predicting the mortality of multihost parasites in different hosts: Some of these diseases rarely harm their hosts, while others are nearly always fatal. Using global case-fatality data for multiple diseases of domestic mammals, we show that the evolutionary relationship among infected and susceptible hosts is a strong predictor of disease-induced mortality. We find that parasites infecting domestic species that are more evolutionarily distant from their other known hosts have a higher probability of resulting in lethal infections. Infectious diseases of domesticated animals impact human well-being via food insecurity, loss of livelihoods, and human infections. While much research has focused on parasites that infect single host species, most parasites of domesticated mammals infect multiple species. The impact of multihost parasites varies across hosts; some rarely result in death, whereas others are nearly always fatal. Despite their high ecological and societal costs, we currently lack theory for predicting the lethality of multihost parasites. Here, using a global dataset of >4,000 case-fatality rates for 65 infectious diseases (caused by microparasites and macroparasites) and 12 domesticated host species, we show that the average evolutionary distance from an infected host to other mammal host species is a strong predictor of disease-induced mortality. We find that as parasites infect species outside of their documented phylogenetic host range, they are more likely to result in lethal infections, with the odds of death doubling for each additional 10 million years of evolutionary distance. Our results for domesticated animal diseases reveal patterns in the evolution of highly lethal parasites that are difficult to observe in the wild and further suggest that the severity of infectious diseases may be predicted from evolutionary relationships among hosts.
Implementation of Maximum Power Point Tracking Based on Variable Speed Forecasting for Wind Energy Systems

In order to precisely control the wind power generation systems under nonlinear variable wind velocity, this paper proposes a novel maximum power tracking (MPPT) strategy for wind turbine systems based on a hybrid wind velocity forecasting algorithm. The proposed algorithm adapts the bat algorithm and improved extreme learning machine (BA-ELM) for forecasting wind speed to alleviate the slow response of anemometers and sensors, considering that the change of wind speed requires a very short response time. In the controlling strategy, to optimize the output power, a state feedback control technique is proposed to achieve the rotor flux and rotor speed tracking purpose based on MPPT algorithm. This method could decouple the current and voltage of induction generator to track the reference of stator current and flux linkage. By adjusting the wind turbine mechanical speed, the wind energy system could operate at the optimal rotational speed and achieve the maximal power. Simulation results verified the effectiveness of the proposed technique.
Dense networks with relative location awareness for thorax disease identification.

PURPOSE Chest X-ray is one of the most common examinations for diagnosing heart and lung diseases. Due to the existing of a large number of clinical cases, many automated diagnosis algorithms based on chest X-ray images have been proposed. To our knowledge, almost none of the previous auto-diagnosis algorithms consider the effect of relative location information on disease incidence. In this study, we propose to use relative location information to assist the identification of thorax diseases. METHOD In this work, U-Net is used to segment lung and heart from chest image. The relative location maps are computed through Euclidean distance transformation from segmented masks. By introducing the relative location information into the network, the usual location of disease is combined with the incidence. The proposed network is the fusion of two branches: mask branch and image branch. A mask branch is designed to be a bottom-up and top-down structure to extract relative location information. The structure has a large receptive field, which can extract more information for large lesion and contextual information for small lesion. The features learned from mask branch are fused with image branch, which is a 121-layers DenseNet. RESULTS We compare our proposed method with four state-of-the-art methods on the largest public chest X-ray dataset: ChestX-ray14. The proposed method achieves the area under a curve of 0.820, which outperforms all the existing models and algorithms. CONCLUSION This paper proposed a dense network with relative location information to identify thorax disease. The method combines the usual location of disease with the incidence for the first time and performs good.
Changes in Iron Status Are Related to Changes in Brain Activity and Behavior in Rwandan Female University Students: Results from a Randomized Controlled Efficacy Trial Involving Iron-Biofortified Beans

ABSTRACT Background Evidence suggests that iron deficiency (ID) affects cognitive performance, as measured in behavior. Although such effects must be mediated by changes in the brain, very few studies have included measures of brain activity to assess this relation. Objective We tested the hypothesis that provision of iron-biofortified beans would result in improvements in measures of iron status, brain dynamics, and behavior. Methods A double-blind, randomized, intervention study was conducted in 55 women aged 18–27 y with low iron status (serum ferritin <20 µg/L). Women were randomly assigned to consume iron-biofortified (86.1 ppm iron) or comparison beans (50.1 ppm iron) daily for 18 wk. Iron status was assessed by hemoglobin, ferritin, transferrin receptor, and body iron; cognitive performance with 5 computerized tasks; and brain dynamics by concurrent electroencephalography (EEG). All measures were taken at baseline and endline. Results The groups did not differ on any measures at baseline. Intention-to-treat analyses revealed significant (all P < 0.05) improvements in hemoglobin (partial effect size attributable to the independent variable, η2 = 0.16), ferritin (η2 = 0.17), and body iron (η2 = 0.10), speed of responding in attentional and mnemonic tasks (η2 = 0.04-0.29), sensitivity and efficiency of memory retrieval (η2 = 0.12-0.55), and measures of EEG amplitude and spectral power (η2 = 0.08 to 0.49). Mediation models provided evidence in support of the hypothesis that changes in iron status produce changes in behavior by way of changes in brain activity. Conclusions Behavioral performance and brain activity, as measured by EEG, are sensitive to iron status, and the consumption of iron-biofortified beans for 18 wk resulted in improvements in measures of both, relative to what was obtained with a comparison bean, in a sample of female university students. Furthermore, the results support the conclusion that changes in brain activity resulting from consumption of biofortified beans mediate the relations between changes in iron biomarkers and changes in cognition. Clinical trial registry: ClinicalTrials.gov Reg No. NCT01594359.
To Beep or Not to Beep? Evaluating Modalities for Multimodal ICU Alarms

Technology plays a prominent role in intensive care units (ICU), with a variety of sensors monitoring both patients and devices. A serious problem exists, however, that can reduce the sensors’ effectiveness. When important values exceed or fall below a certain threshold or sensors lose their signal, up to 350 alarms per patient a day are issued. These frequent alarms are audible in several locations on the ICU, resulting in a massive cognitive load for ICU nurses, as they must evaluate and acknowledge each alarm. “Alarm fatigue” sets in, a desensitization and delayed response time for alarms that can have severe consequences for patients and nurses. To counteract the acoustic load on ICUs, we designed and evaluated personal multimodal alarms for a wearable alarm system (WAS). The result was a lower response time and higher ratings on suitability and feasibility, as well as a lower annoyance level, compared to acoustic alarms. We find that multimodal alarms are a promising new approach to alert ICU nurses, reduce cognitive load, and avoid alarm fatigue.
Cepstral Analysis of Speech using Discrete Hartley Transform

This paper presents Cepstral analysis of speech signal using Discrete Hartley Transform. Hitherto, the cepstral analysis of speech was carried out using in temporal domain and in the frequency domain using Discrete Fourier Transform (DFT) based approach. A new approach of finding the cepstral coefficients in the frequency domain using DHT, rather than using the DFT is proposed. DFT being a complex transform takes more computation time for finding the cepstral coefficients of the speech signal, but DHT being a real transform takes less computation time to do the same with less memory requirement. The relationship between DFT and DHT is made use of for finding the cepstral coefficients, rather than using the DFT directly. The usage of DHT method is found to be optimal than using the direct DFT approach thereby saving implementation cost substantially in the cepstral analysis of speech signals. The analysis is done by comparing the usage of DFT directly on the speech signal and then using DHT, there by seeing the performance of these mathematical transforms based on computation time which is used as a performance metric for validating the veracity of the two discrete transforms used. This work is implemented using MATLAB R2014a software. Keywords—DHT, DFT, Cepstrum.
Towards Unified Business Process Modeling and Verification for Role-based Resource-oriented Service Composition

With the prevalence of ubiquitous computing, big data, and Internet of things in cloud computing environment, it’s important to consider both of collaboration, heterogeneity, isolation of multi-tenant applications and information security and privacy in service composition. Current methods need to be readdressed to cope with cross-organizational, multi-roles participated and knowledge-intensive service composition in an integrated way. Based on the modeling and verification theories of hierarchical colored petri-net, a resource-oriented collaborative workflow model, its resource control model and the joint modeling and verification method are proposed which present a unified solution bridging the gap between traditional structure-oriented workflow execution model and resource-oriented workflow domain model taking into account the underlying roles, tasks, resources and their association and coordination in design-time and runtime as well. In our approach, a business process is divided into three layers: the backbone top-level process, the task fulfillment sub-process and the task execution sub-process in order to reduce the complexity of model verification. In addition this paper gives in-depth discussions on the fine control of implicit parallel and multi-threaded process executions. Finally, the case studies show that the proposed methods are not only applicable to modeling and verification of traditional task-oriented workflows, but also suited for knowledge or data-intensive workflows which involve multi-entities complex interrelationships and relate to the domain knowledge closely.
Isolation of RAR1 Gene from Thinopyrum intermedium and Analysis of Its Function in Wheat Background

【Objective】The study established the foundation to understand the role of RAR1 gene in wheat resistance to diseases, especially powdery mildew, as RAR1 is a required component in some signaling pathways mediated by disease resistance (R) genes in many plant species. 【Method】 RT-PCR and RACE methods were used to isolate the full-length cDNA sequence of the RAR1 gene from Thinopyrum intermedium,a wheat wild-relative with multi-resistance to various pathogens. The gene expression vector pUBI∷RAR1 was constructed and then transformed into a wheat variety ‘Yangmai 12’ by the biolistic particle method. The regenerated transgenic plants were detected through PCR, RT-PCR and test of the resistance to powdery mildew. 【Result】The full-length cDNA of the RAR1 gene was isolated from Thinopyrum intermedium, named TiRAR1, which encodes the RAR1 protein possessing 2 CHORD domains and 1 CCCH domain. The sequence of the TiRAR1 protein shows high homology with the sequences of RAR1 proteins in barley and rice. The expression vector of TiRAR1 gene, pUBI::RAR1, was correctly constructed, and transformed into the wheat variety ‘Yangmai 12’. 1545 immature embryos of ‘Yangmai 12’ were bombarded by the particle containing pUBI∷RAR1. From the regenerated 154 plants, 18 positive transgenic individuals were identified by PCR assay in the T0 generation with a transformation frequency of 1.17%. The results of PCR and RT-PCR assay showed that the RAR1 gene could be inheritable from T0 generation to T1 one, then from T1 generation to T2 one, and could be transcribed and expressed. The resistance test showed that the RAR1 transgenic individuals in T1 and T2 generations showed high resistance to powdery mildew in their all lifecycle, suggesting that the overexpression of RAR1 enhanced the resistance to powdery mildew. 【Conclusion】The full-length cDNA of the RAR1 gene in Thinopyrum intermedium was isolated and transformed into a wheat variety ‘Yangmai 12’. The RAR1 gene could confer high resistance to powdery mildew when overexpressed, and could be used as a potential gene in wheat breeding with broad spectrum resistance to powdery mildew.