Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Forest Disturbance and Recovery in Primorsky Krai, Russia, Using Annual Landsat Time Series and Multi-Source Land Cover Products

The spatial distribution and dynamic changes of the forests in Primorsky Krai, Russia, are of great significance for regional ecological security and sustainable economic and societal development. With the support of the Google Earth Engine cloud computing platform, we first synthesized yearly Landsat surface reflectance images of the best quality of the research area and then used the random forest method to calculate the forest classification probability of the study area year by year from 1998 to 2015. Furthermore, we used a time–series segmentation algorithm to perform temporal trajectory segmentation for forest classification probability estimation, and determined the spatial and temporal distribution characteristics and change laws of the forest. We extended the existing algorithms and parameters of forest classification probability trajectory analysis, achieving a high overall accuracy (86.2%) in forest change detection in the study area. The extended method can accurately capture the time node information of the changes. In the present research we observed: (1) that from 1998 to 2015, the forest area of the whole district showed a net loss state, with a loss area of 0.56 × 106 ha, of which the cumulative forest disturbance area reached 1.12 × 106 ha, and the cumulative forest recovery area reached 0.55 × 106 ha; and (2) that more than 90% of the forest change occurred in areas with a slope of less than 18◦, at a distance of less than 20 km from settlements, and at a distance of less than 10 km from roads. The forest disturbance monitoring results are consistent with the changes in official statistical results over time, but there was a 20% overestimation. The technical method we extended in this study can be used as a reference for large–scale and high–precision dynamic monitoring of the forests in Russia’s Far East and other regions of the world; it also provides a basis for estimating illegal timber harvesting and determining the appropriate amount of forest harvested.
Stress Response to Total Abdominal Hysterectomy under General Anesthesia in Type 2 Diabetic Subjects

Aims: This study was designed to investigate the hemodynamic alteration and changes of glycemic, cortisol and electrolytes status in total abdominal hysterectomy of type 2 diabetic subjects under general anesthesia. Subjects and method: Fourty subjects under general anesthesia for total abdominal hysterectomy were recruited and thrice blood samples were collected from each subject, before anesthesia (PT 0 ), 10 minutes after incision (PT 1 ) and 10 minutes after extubation (PT 2 ). Plasma glucose was measured by glucose-oxidase method, serum C-peptide and serum cortisol by chemiluminescence’s based ELISA technique (Immulite, USA). Serum electrolytes were measured by Dry Chemistry method (DT-60, USA) Results: All the subjects were hemodynamically stable during surgery. Plasma glucose increased significantly in PT2. Serum cortisol was significantly higher in PT 1 and PT 2 than PT 0 . Conclusions: Total abdominal hysterectomy under general anesthesia in well controlled type 2 diabetic subjects is accompanied by a hyperglycemic response which results from rise of insulin antagonists like cortisol.
Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions

Urban geographical maps are important to urban planning, urban construction, land-use studies, disaster control and relief, touring and sightseeing, and so on. Satellite remote sensing images are the most important data source for urban geographical maps. However, for optical satellite remote sensing images with high spatial resolution, certain inevitable factors, including cloud, haze, and cloud shadow, severely degrade the image quality. Moreover, the geometrical and radiometric differences amongst multiple high-spatial-resolution images are difficult to eliminate. In this study, we propose a robust and efficient procedure for generating high-resolution and high-quality seamless satellite imagery for large-scale urban regions. This procedure consists of image registration, cloud detection, thin/thick cloud removal, pansharpening, and mosaicking processes. Methodologically, a spatially adaptive method considering the variation of atmospheric scattering, and a stepwise replacement method based on local moment matching are proposed for removing thin and thick clouds, respectively. The effectiveness is demonstrated by a successful case of generating a 0.91-m-resolution image of the main city zone in Nanning, Guangxi Zhuang Autonomous Region, China, using images obtained from the Chinese Beijing-2 and Gaofen-2 high-resolution satellites.
Mapping Urban Impervious Surfaces by Using Spectral Mixture Analysis and Spectral Indices

Impervious surface is the major component of urban areas, and it has been widely considered as the key for assessing the degree of urban sprawl. While the effectiveness of applying spectral mixture analysis (SMA) and spectral indices in mapping urban impervious surface has been proved, most studies have relied either on SMA or spectral indices without considering both. In this study, the SMA and spectral indices were integrated together to map impervious surfaces distributions in both Milwaukee County in the Wisconsin State and Fayette County in the Kentucky State. Specifically, spectral indices were used for identifying major land covers. Two-dimensional feature space plots were generated by calculated spectral indices images for endmember selection and extraction. Linear constrained SMA was finally applied to quantify the fractional impervious surfaces. Research results indicate that the proposed method has achieved a promising accuracy, and better performance was achieved in less developed areas than the developed areas. Moreover, a comparative analysis shows that the proposed method performs better than the conventional method in both the whole study area and the developed areas, and a comparable performance has been achieved in the less developed areas.
The Verhulst-Like Equations: Integrable OΔE and ODE with Chaotic Behavior

In this paper, we study various variants of Verhulst-like ordinary differential equations (ODE) and ordinary difference equations (O Δ E). Usually Verhulst ODE serves as an example of a deterministic system and discrete logistic equation is a classic example of a simple system with very complicated (chaotic) behavior. In our paper we present examples of deterministic discretization and chaotic continualization. Continualization procedure is based on Padé approximants. To correctly characterize the dynamics of obtained ODE we measured such characteristic parameters of chaotic dynamical systems as the Lyapunov exponents and the Lyapunov dimensions. Discretization and continualization lead to a change in the symmetry of the mathematical model (i.e., group properties of the original ODE and O Δ E). This aspect of the problem is the aim of further research.
Fluctuating Asymmetry in Ground Beetles (Coleoptera, Carabidae) and Conditions of Its Manifestation

Fluctuating asymmetry (FA) is used to reveal environmental or genetic stress, but the results of some studies are inconsistent. We aimed to give some explanations of possible controversial conclusions, when FA was employed. We measured FA (one dimensional and one meristic traits) in the recognized bioindicators—ground beetles (Coleoptera, Carabidae). Beetles were sampled in a vast area (four provinces of Russia with the spectrum of the studied sites, which differed in anthropogenic impact, vegetation, and landscape features). On the basis of such measurements (4673 specimen) we created a data base. Subsequent ANOVA showed, that FA was species-specific (out of six species investigated it was expressed in five ones), sex-biased (males had higher levels of FA), and were affected practically by all environmental factors. Besides significant species–sex and factors–sex interactions were found. So, when employing FA as an indicator of stress, overall biological and ecological variation in species-indicator must be investigated before. Sometimes FA (or its absence) may not be due to pollution or another disturbing factor, but be the result of the effect of unaccounted but FA determinative factors.
Combining Multiband Remote Sensing and Hierarchical Distance Sampling to Establish Drivers of Bird Abundance

Information on habitat preferences is critical for the successful conservation of endangered species. For many species, especially those living in remote areas, we currently lack this information. Time and financial resources to analyze habitat use are limited. We aimed to develop a method to describe habitat preferences based on a combination of bird surveys with remotely sensed fine-scale land cover maps. We created a blended multiband remote sensing product from SPOT 6 and Landsat 8 data with a high spatial resolution. We surveyed populations of three bird species (Yellow-breasted Bunting Emberiza aureola, Ochre-rumped Bunting Emberiza yessoensis, and Black-faced Bunting Emberiza spodocephala) at a study site in the Russian Far East using hierarchical distance sampling, a survey method that allows to correct for varying detection probability. Combining the bird survey data and land cover variables from the remote sensing product allowed us to model population density as a function of environmental variables. We found that even small-scale land cover characteristics were predictable using remote sensing data with sufficient accuracy. The overall classification accuracy with pansharpened SPOT 6 data alone amounted to 71.3%. Higher accuracies were reached via the additional integration of SWIR bands (overall accuracy = 73.21%), especially for complex small-scale land cover types such as shrubby areas. This helped to reach a high accuracy in the habitat models. Abundances of the three studied bird species were closely linked to the proportion of wetland, willow shrubs, and habitat heterogeneity. Habitat requirements and population sizes of species of interest are valuable information for stakeholders and decision-makers to maximize the potential success of habitat management measures.
High-performance Diagnosis of Sleep Disorders: A Novel, Accurate and Fast Machine Learning Approach Using Electroencephalographic Data

While diagnosing sleep disorders by physicians using electroencephalographic data is protracted and inaccurate, we report promising results from a novel, fast and reliable machine learning approach. Our approach only needs an electroencephalographic recording snippet of 10 minutes instead of eight hours to correctly classify the disorder with an accuracy of over 90 percent. The Rapid Eye Movement sleep behavior disorder can lead to secondary diseases like Parkinson or Dementia. Therefore, it is important to classify the disorder fast and with a high level of accuracy – which is now possible with our approach.
Adaptive TVD-RK Discontinuous Galerkin Algorithms for Shallow Water Equations

The adaptive Discontinuous Galerkin (DG) method for solving the one-dimensional conservation equation is presented. In this paper we consider the advection equation, the Burgers’ equation, and the shallow water equations. To improve the accuracy of this method, two types of adaptive technique are employed. These are the adaptive polynomial(p-daptive) and the adaptive mesh(h-adaptive). Troubled cells needed to be refined are detected by two types of indicators, which are error and gradient indicators. The present schemes have been improved the accuracy of the solution during time integration process. For smooth solution the accuracy can be improve by the adaptive polynomial criteria, while the accuracy of moving shock, rarefaction and high gradient solution can be improved by the adaptive mesh scheme. High gradient area in the computational domain can be detected efficiently by both presented indicators Keywords—Adaptive Discontinuous Galerkin method, Advection equation, Burgers’ equation, Shallow water equations
Model Selection for Optimal Prediction in Statistical Machine Learning

DOI: https://doi.org/10.1090/noti2014 science with several ideas from cognitive neuroscience and psychology to inspire the creation, invention, and discovery of abstract models that attempt to learn and extract patterns from the data. One could think of SML as a field of science dedicated to building models endowed with the ability to learn from the data in ways similar to the ways humans learn, with the ultimate goal of understanding and then mastering our complex world well enough to predict its unfolding as accurately as possible. One of the earliest applications of statistical machine learning centered around the now ubiquitous MNIST benchmark task, which consists of building statistical models (also
Three-dimensional electrochemical Li-ion battery modelling featuring a focused ion-beam/scanning electron microscopy based three-phase reconstruction of a LiCoO2 cathode

We combine a three-phase, three-dimensional reconstruction of a LiCoO2 battery cathode based on focused ion-beam/scanning electron microscopy (FIB/SEM) imaging with an electrochemical model. The model considers the electric potential and lithium/salt concentration distribution in both the liquid electrolyte and the solid active-material phases. In contrast to previously presented models, we spatially resolve the carbon-binder phase to provide a more realistic description of the electric potential. We observe that carbon-binder coverage of the solid electrolyte interface (SEI) impedes local surface reactions and thus affects lithium redistribution. For the considered cathode, the total surface to volume 5 5 2 −3 econstruction i-ion battery cathode orous media icrostructural electrochemical battery odel seudo-two-dimensional porous electrode ratio of the SEI is reduced from 11.2 × 10 to 6.5 × 10 m m when the carbon-binder phase is modelled explicitly. This leads to increased inhomogeneity of the lithium concentration in active-material grains during charging. Additionally, we study lithium/salt concentration in the electrolyte, revealing gradients between 0.9 and 1.5 kmol m−3 depending on the distance to the separator. This is significant because the lithium/salt ects t odel concentration directly aff
Gabapentinoids for Chronic Pain: Do the Harms Outweigh the Benefits?

Gabapentinoids, pregabalin (LyricaTM) and gabapentin (NeurontinTM) are anticonvulsants that have been approved for chronic pain conditions such as diabetic peripheral neuropathy, postherpetic neuralgia, fibromyalgia, and are also widely prescribed off-label for chronic low back pain. Prescriptions for gabapentinoids have increased rapidly in the last five years, however, the evidence for its efficacy can be conflicting and will be analyzed for each of these chronic pain conditions. The adverse event rates and safety profile will be examined, including case reports of the occurrence of serious adverse events, to ascertain whether gabapentinoids have the potential to cause harm above the benefit of providing effective pain relief. Further case reports documenting serious withdrawal syndromes will add to the body of evidence to weigh the benefits over the risks and will identify areas where research is lacking. From the analysis of evidence on efficacy, adverse events and withdrawal there will be resulting recommendations for practice when considering gabapentinoid treatment for chronic pain.
Human Vδ2 versus non-Vδ2 γδ T cells in antitumor immunity

The Vδ2 and non-Vδ2 (mainly Vδ1) subsets of human γδ T cells have distinct homing patterns and recognize different types of ligands, yet both exert potent antitumor effects. While the T-cell receptor of Vδ2 T cells primarily recognizes tumor cell-derived pyrophosphates, non-Vδ2 γδ T cells preferentially recognize stress-associated surface antigens. Here, we discuss the pros and cons of Vδ2 versus non-Vδ2 γδ T cells as tools for future immunotherapeutic interventions against cancer.
Modelling and Control Design for Electric Power Steering system with Cascaded Lead Compensation Method

This paper presents a new control strategy for an Electric Power Steering system. Due to higher steering assist gain and non linear torque map, which reduces stability and causes vibrations in steering system, an stabilizing compensator should be included in the controller system. The role of compensator is to provide stability to the system and also to accelerate the system response time. A faster response is required as a slight delay or overshoot in steering control can lead to severe consequences. The stability of the system with torque map is detailed. Cascaded lead compensators are designed and applied to the system and the theoretical analysis is verified from the simulation and experimental results.
Epidemiological study for common causes of diarrhea disease among children under 5 years of age in some Iraqi province

Background: Acute diarrheal disease among children less than 5 years old remains a major cause of morbidity and mortality worldwide. S evere infectious diarrhea in children occurs most frequently under circumstances of poor environmental sanitation and hygiene, inadequate water supplies, and poverty. In Iraq the control of diarrheal disease ( CDD), including promotion of breast-feeding, oral rehydration therapy and specific health education is a part of national strategies a ming to improve the quality of life and reduce the burdens caused by diseases. Objectives: the study aimed to identify the most common causes of diarrheal disease among children aged less than five years admitted t o pediatrics Hospitals in some Iraq province. Patient and method:Hospitals in five Iraq provinces, karbala, Dyala, Hila, and Najaf during 12 months of 2013 received 1639 cases of dia rrhe disease among children under 5 years of age, a hospital – based cross sectional study was performed a respective cases was defined as a child having three or more loose, liquid, or watery stools or at least one bloody loose stool within the last 24 hours. Accord ingly, all cases admitted to general pediatrics Hospital between January and December 20 13, which fulfilled the inclusion criteria were recruited into the study. Results: in current study shows statistical prevalence to b acteria spp. (0.006) and Giardiasis among Dyala province at p. value (0.001 ) as well as highly significant difference between Entamaebea. Histolytica.and Karb al city at p. value (0.001), among other pathogens in our study provinces. Conclusion: our study revealed some of pathogens can lead to c ause diarrhea disease among children under 5 years of age especially E. h istolytica and Giardia Lamblia in some Iraq province so demonstrate poor hygiene and educational health and inadequate safe water supply and food safety.caused by diarrhe among children less than five years of age in the district. Karbala journal of pharmaceutical sciences No. (11 ) 2016 (11)دعلا ةينلاديصلا مولعلل ءلابرك ةلجم 125 ةيئابو ةسارد ضرم تاببسمل لاهسلإا ىدل ةعئاشلا لافطلأا نس نود ةسماخلا ب يف رمعلا نم ضع
File System Aging

File systems must allocate space for files without knowing what will be added or removed in the future. Over the life of a file system, this may cause suboptimal file placement decisions that eventually lead to slower performance, or aging. Conventional wisdom suggests that file system aging is a solved problem in the common case; heuristics to avoid aging, such as colocating related files and data blocks, are effective until a storage device fills up, at which point space pressure exacerbates fragmentation-based aging. However, this article describes both realistic and synthetic workloads that can cause these heuristics to fail, inducing large performance declines due to aging, even when the storage device is nearly empty. We argue that these slowdowns are caused by poor layout. We demonstrate a correlation between the read performance of a directory scan and the locality within a file system's access patterns, using a dynamic layout score. We complement these results with microbenchmarks that show that space pressure can cause a substantial amount of inter-file and intra-file fragmentation. However, our results suggest that the effect of free-space fragmentation on read performance is best described as accelerating the file system aging process. The effect on write performance is non-existent in some cases, and, in most cases, an order of magnitude smaller than the read degradation from fragmentation caused by normal usage. In short, many file systems are exquisitely prone to read aging after a variety of write patterns. We show, however, that aging is not inevitable. BetrFS, a file system based on write-optimized dictionaries, exhibits almost no aging in our experiments. We present a framework for understanding and predicting aging, and identify the key features of BetrFS that avoid aging.
Sensing of Oxygen Partial Pressure in Air with ZnO Nanoparticles

The demand for sensors in response to oxygen partial pressure in air is increasingly high in recent years and small-size sensors on a micrometer scale and even a nanometer scale are particularly desirable. In this paper, the sensing of oxygen partial pressure in air was realized by a solution-processed ZnO nanoparticle (NP). Thin-film ZnO NP was prepared by spin-coating and a highly sensitive sensor was then fabricated. The oxygen sensing performance was characterized in air and compared with that in nitrogen, which showed an increase in electrical conductance by more than 100 times as a result of decreasing oxygen partial pressure from 103 mBar to 10−5 mBar. Moreover, higher sensitivity was achieved by increasing the annealing temperature and the effect of thermal annealing was also investigated. Furthermore, ZnO NP lines with 7 μm in width were successfully patterned with low cost by a mould-guided drying technique from ZnO NP dispersion, which makes ZnO NP extremely promising for miniaturized and integrated sensing applications.
Author’s response to reviews Title: Healthy Options: Study protocol and baseline characteristics for a cluster randomized controlled trial of group psychotherapy for perinatal women living with HIV and depression in Tanzania Authors:

Authors: Mary Kay Smith Fawzi (mksfawzi@msn.com) Hellen Siril (neemasiril@gmail.com) Elysia Larson (elarson@mail.harvard.edu) Zenaice Aloyce (zalosha9@yahoo.com) Ricardo Araya (ricardo.araya@kcl.ac.uk) Anna Kaale (annafuraha@gmail.com) Janeth Kamala (janeth.kamala@gmail.com) Muhummed Nadeem Kasmani (nadeem@hms.harvard.edu) Amina Komba (komba.amina@gmail.com) Anna Minja (agape_minja@yahoo.com) Angelina Mwimba (ingilina@yahoo.com) Fileuka Ngakongwa (fillejully@gmail.com) Magreat Somba (magreats@yahoo.com) Christopher R Sudfeld (csudfeld@hsph.harvard.edu) Sylvia Kaaya (skaaya@gmail.com)