Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of spatial resolution on NDVI over heterogeneous surface

The normalized difference vegetation index (NDVI) is the most widely used vegetation index. Several studies have investigated the impact of spatial resolution on NDVI, but without consensus. The objective of this paper is to analyze the difference between NDVI calculated from average reflectances, which represents NDVI derived from coarse spatial resolution data, and NDVI integrated from individual component NDVI’s, which represents NDVI derived from fine spatial resolution data, for heterogeneous surface by a linear vegetation-soil mixing model. Analytical results showed that they are different in formulation and that two correction terms involving vegetation fraction and the differences of red and NIR reflectances between vegetation and soil background, are required to correct NDVIC to NDVIF. It suggested that for heterogeneous surfaces, spatial resolution has an important impact on the NDVI measurement and NDVI at different scales may not be comparable, particularly for partially vegetated surface with dark soil background. The difference is relatively insignificant when soil background is bright. Keywords-NDVI; different spatial resolution; linear mixing model; heterogeneous surfaces.
Modeled Chl:C ratio and derived estimates of phytoplankton carbon biomass and its contribution to total particulate organic carbon in the global surface ocean

Chlorophyll (Chl) is a distinctive component of autotrophic organisms, often used as an indicator of phytoplankton biomass in the ocean. However, assessment of phytoplankton biomass from Chl relies on the accurate estimation of the Chl:carbon(C) ratio. Here we present global patterns of Chl:C ratios in the surface ocean obtained from a phytoplankton growth model that accounts for the optimal acclimation of phytoplankton to ambient nutrient, light, and temperature conditions. The model agrees largely with observed/expected global patterns of Chl:C. Combining our Chl:C estimates with satellite Chl and particulate organic carbon (POC), we infer phytoplankton C concentration in the surface ocean and its contribution to the total POC pool. Our results suggest that the portion of POC corresponding to living phytoplankton is higher in subtropical latitudes and less productive regions (∼30–70%) and decreases to ∼10–30% toward high latitudes and productive regions. An important caveat of our model is the lack of iron limiting effects on phytoplankton physiology. Comparison of our predicted phytoplankton biomass with an independent estimate of total POC reveals a positive correlation between nitrate concentrations and nonphotosynthetic POC in the surface ocean. This correlation disappears when a constant Chl:C is applied. Our analysis is not constrained by assumptions of constant Chl:C or phytoplankton:POC ratio, providing a novel independent analysis of phytoplankton biomass in the surface ocean. These results highlight the importance of accounting for the variability in Chl:C and its application in distinguishing the autotrophic and heterotrophic components in the assemblage of the marine plankton ecosystem.
Announcement: Remote Sensing 2017 Best Guest Editor Award

Guest Editors help invite many high-quality papers for Remote Sensing. To acknowledge and encourage the generous work and precious time of the guest editor team of Special Issues in Remote Sensing, we launched the Best Guest Editor Award last year for Special Issues closed from 1 June 2016 to 31 June 2017. In total, 40 Special Issues were closed from 1 June 2016 to 31 June 2017 and these Special Issues contributed 607 papers, with an average of 15 papers per Special Issue. A particular highlight was the Special Issue titled “Earth Observations for Geohazards” [1] edited by Prof. Zhenhong Li and Prof. Roberto Tomas. This Special Issue covered innovative Earth Observations methods and applications for monitoring and modeling geohazards. There were 44 papers [2–45] published in it. All of the publications in this Special Issue were cited and they contributed a total of 203 citations for the journal by the end of 2017. The paper focused on imaging land subsidence induced by groundwater extraction using radar interferometry [2] was highly cited, with 16 citations by the end of 2017. We are greatly excited to announce the winners: Prof. Dr. Zhenhong Li (Newcastle University, UK) and Prof. Roberto Tomas (University of Alicante, Spain) (Figure 1).
Influence of Al-Si Diffusion Coating on Low Cycle Fatigue Properties of Cast Superalloy Inconel 738LC at 800 °C

High temperature low cycle fatigue behaviour of cast nickel-based superalloy Inconel 738LC in as-received condition and coated with an Al-Si diffusion layer was studied. The Al-Si protective layer was deposited on the gauge section of cylindrical specimens using the slurry technique. Fatigue tests were performed on cylindrical specimens under total strain control in symmetrical cycle at 800 °C in air. The coating has a beneficial effect on fatigue life in the low amplitude domain. The stress response of the coated material is higher for high amplitudes in comparison with the uncoated one. Fracture surfaces and sections parallel to the specimen axis have been examined to study fatigue damage mechanisms.
Analyzing mHealth Engagement: Joint Models for Intensively Collected User Engagement Data

Background Evaluating engagement with an intervention is a key component of understanding its efficacy. With an increasing interest in developing behavioral interventions in the mobile health (mHealth) space, appropriate methods for evaluating engagement in this context are necessary. Data collected to evaluate mHealth interventions are often collected much more frequently than those for clinic-based interventions. Additionally, missing data on engagement is closely linked to level of engagement resulting in the potential for informative missingness. Thus, models that can accommodate intensively collected data and can account for informative missingness are required for unbiased inference when analyzing engagement with an mHealth intervention. Objective The objectives of this paper are to discuss the utility of the joint modeling approach in the analysis of longitudinal engagement data in mHealth research and to illustrate the application of this approach using data from an mHealth intervention designed to support illness management among people with schizophrenia. Methods Engagement data from an evaluation of an mHealth intervention designed to support illness management among people with schizophrenia is analyzed. A joint model is applied to the longitudinal engagement outcome and time-to-dropout to allow unbiased inference on the engagement outcome. Results are compared to a naïve model that does not account for the relationship between dropout and engagement. Results The joint model shows a strong relationship between engagement and reduced risk of dropout. Using the mHealth app 1 day more per week was associated with a 23% decreased risk of dropout (P<.001). The decline in engagement over time was steeper when the joint model was used in comparison with the naïve model. Conclusions Naïve longitudinal models that do not account for informative missingness in mHealth data may produce biased results. Joint models provide a way to model intensively collected engagement outcomes while simultaneously accounting for the relationship between engagement and missing data in mHealth intervention research.
Inhibiting checkpoint kinase 1 protects bone from bone resorption by mammary tumor in a mouse model

DNA damage response plays a critical role in tumor growth, but little is known about its potential role in bone metabolism. We employed selective inhibitors of Chk1 and examined their effects on the proliferation and migration of mammary tumor cells as well as the development of osteoblasts and osteoclasts. Further, using a mouse model of bone metastasis we evaluated the effects of Chk1 inhibitors on bone quality. Chk1 inhibitors blocked the proliferation, survival, and migration of tumor cells in vitro and suppressed the development of bone-resorbing osteoclasts by downregulating NFATc1. In the mouse model, Chk1 inhibitor reduced osteolytic lesions and prevented mechanical weakening of the femur and tibia. Analysis of RNA-seq expression data indicated that the observed effects were mediated through the regulation of eukaryotic translation initiation factor 2 alpha, stress to the endoplasmic reticulum, S100 proteins, and bone remodeling-linked genes. Our findings suggest that targeting Chk1 signaling without adding DNA damaging agents may protect bone from degradation while suppressing tumor growth and migration.
Patch Transporter: Incentivized, Decentralized Software Patch System for WSN and IoT Environments

In the complicated settings of WSN (Wireless Sensor Networks) and IoT (Internet of Things) environments, keeping a number of heterogeneous devices updated is a challenging job, especially with respect to effectively discovering target devices and rapidly delivering the software updates. In this paper, we convert the traditional software update process to a distributed service. We set an incentive system for faithfully transporting the patches to the recipient devices. The incentive system motivates independent, self-interested transporters for helping the devices to be updated. To ensure the system correctly operates, we employ the blockchain system that enforces the commitment in a decentralized manner. We also present a detailed specification for the proposed protocol and validate it by model checking and simulations for correctness.
Do Wireless Sensor Networks Need to be Completely Integrated into the Internet

Wireless sensor networks are considered as an integral part of the Internet of Things paradigm. Not only they provide a virtual presence to elements of the real world, but also allow any computational system to know about the physical state of those elements thanks to the use of embedded sensors. In order to belong to the Internet of Things, the elements of a sensor network can implement Internet protocols and services such as the TCP/IP stack and web services. Still, a question that must be raised at this point of time is whether all sensor network applications should be completely integrated into the Internet or not. The purpose of this paper is to analyze this question, reviewing the challenges and security requirements of Internet-enabled sensor networks.
Addressing Statistical Biases in Nucleotide-Derived Protein Databases for Proteogenomic Search Strategies

Proteogenomics has the potential to advance genome annotation through high quality peptide identifications derived from mass spectrometry experiments, which demonstrate a given gene or isoform is expressed and translated at the protein level. This can advance our understanding of genome function, discovering novel genes and gene structure that have not yet been identified or validated. Because of the high-throughput shotgun nature of most proteomics experiments, it is essential to carefully control for false positives and prevent any potential misannotation. A number of statistical procedures to deal with this are in wide use in proteomics, calculating false discovery rate (FDR) and posterior error probability (PEP) values for groups and individual peptide spectrum matches (PSMs). These methods control for multiple testing and exploit decoy databases to estimate statistical significance. Here, we show that database choice has a major effect on these confidence estimates leading to significant differences in the number of PSMs reported. We note that standard target:decoy approaches using six-frame translations of nucleotide sequences, such as assembled transcriptome data, apparently underestimate the confidence assigned to the PSMs. The source of this error stems from the inflated and unusual nature of the six-frame database, where for every target sequence there exists five "incorrect" targets that are unlikely to code for protein. The attendant FDR and PEP estimates lead to fewer accepted PSMs at fixed thresholds, and we show that this effect is a product of the database and statistical modeling and not the search engine. A variety of approaches to limit database size and remove noncoding target sequences are examined and discussed in terms of the altered statistical estimates generated and PSMs reported. These results are of importance to groups carrying out proteogenomics, aiming to maximize the validation and discovery of gene structure in sequenced genomes, while still controlling for false positives.
Computerised cognitive-behavioural therapy for depression: systematic review.

BACKGROUND Computerised cognitive-behavioural therapy (CCBT) is used for treating depression and provides a potentially useful alternative to therapist cognitive-behavioural therapy (CBT). AIMS To systematically review the evidence for the effectiveness of CCBT for the treatment of mild to moderate depression. METHOD Electronic databases were searched to identify randomised controlled trials. Selected studies were quality assessed and data extracted by two reviewers. RESULTS Four studies of three computer software packages met the inclusion criteria. Comparators were treatment as usual, using a depression education website and an attention placebo. CONCLUSIONS There is some evidence to support the effectiveness of CCBT for the treatment of depression. However, all studies were associated with considerable drop-out rates and little evidence was presented regarding participants' preferences and the acceptability of the therapy. More research is needed to determine the place of CCBT in the potential range of treatment options offered to individuals with depression.
Active Model-Based Control for Pneumatic Artificial Muscle

In this paper, an active model-based control scheme is developed for the pneumatic artificial muscle (PAM), to compensate for the uncertainties in the dynamics model of the PAM. First, a simplified three-element model with respect to a specific range of pressure is formulated as the reference model. Second, a Kalman filter is adopted to actively estimate the errors involved in the reference model, especially while the PAM was working at the pressure outside the specific range where the reference model was built. Finally, a compensation control is proposed using the estimated errors to reject the modeling errors and improve the performance of the PAM. Experiments are conducted on a one degree-of-freedom testbed actuated by the PAM. The experimental results with and without the active-model-based compensation are presented and compared to demonstrate the improvements of the proposed scheme.
A novel four-bar linkage prosthetic knee based on magnetorheological effect: principle, structure, simulation and control

In this paper, the principle and structure of the four-bar linkage prosthetic knee based on the magnetorheological effect (FLPKME) are proposed and realized by individually integrating the upper and lower link rods of the four-bar linkage with the piston rod and the outer cylinder of the magnetorheological (MR) damper. The integrated MR damper, in which the MR fluid is operated in the shear mode, has a double-ended structure. The prototype of the FLPKME is designed and fabricated. Utilizing the developed FLPKME, the lower limb prosthesis is developed, modeled, and simulated. On these bases, the control algorithm for the FLPKME is developed. A test platform for the FLPKME is developed and the performance of the FLPKME with seven constant currents and controlled currents by the control algorithm developed in this paper are experimentally tested. The results show that the FLPKME with a constant current of 1.6 A possesses the basic stable gait, and the FLPKME with the controlled currents by the control algorithm developed in this paper is able to track the motions well and to imitate the natural motions of a healthy human knee joint.
Mapping Optimization for a MAP Turbo Detector Over a Frequency-Selective Channel

In this paper, we consider a bit interleaved coded modulation (BICM) scheme over a frequency-selective channel. At the receiver, a turbo detector composed of a maximum a posteriori (MAP) detector and a MAP decoder is used. We propose to optimize the mapping choice in this context since it is well known that it has a significant impact on the performance of iterative receivers. We consider fixed and Rayleigh fading channels. Based on the Gaussian approximation, we give an analytical upper bound of the bit error probability (BEP) at the output of the detector for fixed channels. Then, we derive an approximate analytical expression of the BEP for both fixed and Rayleigh fading channels when the a priori information provided by the decoder is reliable, and then, most errors at the output of the detector are isolated. We find that the mapping minimizing this expression corresponds to a move away from the symbols differing by only one bit, unlike the Gray mapping. Since an exhaustive search to find this mapping is complicated for high-order modulations, we propose to use the binary switching algorithm (BSA) to approach the solution. Then, based on these results, we propose to adapt the mapping according to the signal-to-noise ratio (SNR) of the transmission.
Monocortical Mandibular Bone Grafting for Reconstruction of Alveolar Cleft

Objective To assess and develop a monocortical mandibular bone grafting procedure for reconstruction of alveolar cleft. Design Prospective study. Setting Hokkaido University Hospital. Patients Forty-two consecutive Japanese patients who had been treated for a total of 48 clefts according to a strict clinical protocol. Mean age at bone grafting was 6 years 11 months. Interventions Bone grafting was performed by harvesting lateral cortical bone plates from the symphysis and/or body and then placing them on the labial and palatal openings of the alveolar process defect. No particulate bone grafts were packed into the bony cavity. Mean follow-up after bone grafting was 37 months. Main Outcome Measures Status of the grafted area and eruption of cleft-adjacent teeth were assessed prospectively using computed tomography and periapical radiography. Results At 6 months postoperatively, computed tomography showed sufficient bone bridge formation at the cleft site in 85.4% of clefts. Periapical radiography showed ≥75% of the root surfaces of cleft-adjacent teeth were covered with spanning bone in 83.3% of clefts. In 92.6% of clefts in which the cleft-adjacent canine was uncovered with bone during follow-up, the canines erupted spontaneously. Conclusions Monocortical mandibular bone grafting appears extremely effective for sufficient bone bridge formation and facilitation of cleft-adjacent teeth eruption. The procedure is advantageous in that the quantity of bone required per unit volume of cleft defect is relatively reduced, and larger clefts can thus be treated.
Tastant-Evoked Arc Expression in the Nucleus of the Solitary Tract and Nodose/Petrosal Ganglion of the Mouse Is Specific for Bitter Compounds

Despite long and intense research, some fundamental questions regarding representation of taste information in the brain still remain unanswered. This might in part be due to shortcomings of the established methods that limit the researcher either to thorough characterization of few elements or to analyze the response of the entirety of neurons to only one stimulus. To overcome these restrictions, we evaluate the use of the immediate early gene Arc as a neuronal activity marker in the early neural structures of the taste pathway, the nodose/petrosal ganglion (NPG) and the nucleus of the solitary tract (NTS). Responses of NPG and NTS neurons were limited to substances that taste bitter to humans and are avoided by mice. Arc-expressing cells were concentrated in the rostromedial part of the dorsal NTS suggesting a role in gustatory processing. The use of Arc as a neuronal activity marker has several advantages, primarily the possibility to analyze the response of large numbers of neurons while using more than one stimulus makes Arc an interesting new tool for research in the early stages of taste processing.
Assessment of Eco-Friendly Natural Antimicrobial Textile Finish Extracted from Aloe Vera and Neem Plants

*Faculty of Pharmacy, Bahauddin Zakariya University, 60800 Multan, Pakistan E-mail: engr.furqan@bzu.edu. pk Abstract The aim of the present work was to assess an eco friendly natural antimicrobial textile finish extracted from Aloe gel and Neem plants. Extracted Aloe gel and active substance of Neem were mixed in a mordant to form a finish. Bleached cotton samples were treated with 5, 7, and 10% concentrations of Aloe gel and Neem separately. The same samples were then treated with a hybrid combination of Aloe gel and Neem (HCAN) extracts having 5, 7 and 10% concentrations. These finished samples were subjected to an antibacterial activity test against E. coli and S. aureus, an antifungal activity test against Aspergillus Niger, and a test of their durability of antibacterial finish fastness to washing by standard test methods. It was found that the hybrid combination of Aloe gel and Neem (HCAN) was an effective antibacterial and antifungal agent as compared to Aloe gel and Neem separately. It also showed good durability to washing.
Four-Year Cost-effectiveness of Cognitive Behavior Therapy for Preventing First-episode Psychosis: The Dutch Early Detection Intervention Evaluation (EDIE-NL) Trial

Background This study aims to evaluate the long-term cost-effectiveness of add-on cognitive behavior therapy (CBT) for the prevention of psychosis for individuals at ultrahigh risk (UHR) of psychosis. Method The Dutch Early Detection and Intervention randomized controlled trial was used, comparing routine care (RC; n = 101) with routine care plus CBT for UHR (here called CBTuhr; n = 95). A cost-effectiveness analysis was conducted with treatment response (defined as proportion of averted transitions to psychosis) as an outcome and a cost-utility analysis with quality-adjusted life years (QALYs) gained as a secondary outcome. Results The proportion of averted transitions to psychosis was significantly higher in the CBTuhr condition (with a risk difference of 0.122; b = 1.324, SEb = 0.017, z = 7.99, P < 0.001). CBTuhr showed an 83% probability of being more effective and less costly than RC by -US$ 5777 (savings) per participant. In addition, over the 4-year follow-up period, cumulative QALY health gains were marginally (but not significantly) higher in CBTuhr than for RC (2.63 vs. 2.46) and the CBTuhr intervention had a 75% probability of being the superior treatment (more QALY gains at lower costs) and a 92% probability of being cost-effective compared with RC at the Dutch threshold value (US$ 24 560; €20 000 per QALY). Conclusions Add-on preventive CBTuhr had a high likelihood (83%) of resulting in more averted transitions to psychosis and lower costs as compared with RC. In addition, the intervention had a high likelihood (75%) of resulting in more QALY gains and lower costs as compared to RC.