Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating Forest Stand Height in Savannakhet, Lao PDR Using InSAR and Backscatter Methods with L-Band SAR Data

Forest stand height (FSH), or average canopy height, serves as an important indicator for forest monitoring. The information provided about above-ground biomass for greenhouse gas emissions reporting and estimating carbon storage is relevant for reporting for Reducing Emissions from Deforestation and Forest Degradation (REDD+). A novel forest height estimation method utilizing a fusion of backscatter and Interferometric Synthetic Aperture Radar (InSAR) data from JAXA’s Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) is applied to a use case in Savannakhet, Lao. Compared with LiDAR, the estimated height from the fusion method had an RMSE of 4.90 m and an R2 of 0.26. These results are comparable to previous studies using SAR estimation techniques. Despite limitations of data quality and quantity, the Savannakhet, Lao use case demonstrates the applicability of these techniques utilizing L-band SAR data for estimating FSH in tropical forests and can be used as a springboard for use of L-band data from the future NASA-ISRO SAR (NISAR) mission.
New Irregular Solutions in the Spatially Distributed Fermi–Pasta–Ulam Problem

For the spatially-distributed Fermi–Pasta–Ulam (FPU) equation, irregular solutions are studied that contain components rapidly oscillating in the spatial variable, with different asymptotically large modes. The main result of this paper is the construction of families of special nonlinear systems of the Schrödinger type—quasinormal forms—whose nonlocal dynamics determines the local behavior of solutions to the original problem, as t→∞. On their basis, results are obtained on the asymptotics in the main solution of the FPU equation and on the interaction of waves moving in opposite directions. The problem of “perturbing” the number of N elements of a chain is considered. In this case, instead of the differential operator, with respect to one spatial variable, a special differential operator, with respect to two spatial variables appears. This leads to a complication of the structure of an irregular solution.
Polycistronic Artificial microRNA-Mediated Resistance to Cucumber Green Mottle Mosaic Virus in Cucumber

Cucumber green mottle mosaic virus (CGMMV), as a typical seed-borne virus, causes costly and devastating diseases in the vegetable trade worldwide. Genetic sources for resistance to CGMMV in cucurbits are limited, and environmentally safe approaches for curbing the accumulation and spread of seed-transmitted viruses and cultivating completely resistant plants are needed. Here, we describe the design and application of RNA interference-based technologies, containing artificial microRNA (amiRNA) and synthetic trans-acting small interfering RNA (syn-tasiRNA), against conserved regions of different strains of the CGMMV genome. We used a rapid transient sensor system to identify effective anti-CGMMV amiRNAs. A virus seed transmission assay was developed, showing that the externally added polycistronic amiRNA and syn-tasiRNA can successfully block the accumulation of CGMMV in cucumber, but different virulent strains exhibited distinct influences on the expression of amiRNA due to the activity of the RNA-silencing suppressor. We also established stable transgenic cucumber plants expressing polycistronic amiRNA, which conferred disease resistance against CGMMV, and no sequence mutation was observed in CGMMV. This study demonstrates that RNA interference-based technologies can effectively prevent the occurrence and accumulation of CGMMV. The results provide a basis to establish and fine-tune approaches to prevent and treat seed-based transmission viral infections.
Compact modeling of high voltage MOSFETs

In the automotive industry, there is a strong trend that has increased the electronics in cars for various functions like fuel injection, electric control of doors and windows, electric chair adjustment, air conditioning etc. The 12V battery used in the present cars will not be sufficient for the increasing number of functions, as a consequence, a change towards 42V batteries will be necessary. For these automotive systems, so called smart power ICs must be used. These are the chips in which the power functionality e.g. control of motor is integrated with logic control. There is also a trend towards operation at high voltages and integrating more intelligence using a microcontroller's RAM/ROM memory and several other sensors and interfaces. The final goal is the integration of a complete system on a single chip, so called power system on chip (SoC). The interest in accurate modeling of high voltage transistors has increased in recent years due to the compatibility of these devices with standard CMOS technology. However, existing LDMOS models are not accurate enough for this task and SPICE models are specially weak for AC performance. The limitation of these models lies in their lack of capability to physically model some of the characteristic phenomena observed in high voltage devices. The increased difficulty is related to complex 2D effects specific to asymmetric high voltage device architectures. This thesis presents the compact modeling of high voltage devices. First, a highly scalable general high voltage MOSFET model, for the first time, is presented, which can be used for any high voltage MOSFET with extended drift region. This model includes physical effects like the quasi-saturation, impact-ionization and self-heating, and a new general model for drift resistance. The model is validated on the measured characteristics of two widely used high voltage devices in the industry i.e. LDMOS and VDMOS devices, and implemented in Verilog-A code and tested on commercial circuit simulators like SABER (Synopsys), ELDO (Mentor Graphics), Spectre (Cadence) and UltraSim (Cadence). The model exhibits excellent scalability with transistor width, drift length, number of fingers and temperature. Second, the compact modeling of lateral non-uniform doping is presented, which has great impact on the AC behavior. Third, the invalidity of Ward-Dutton charge partitioning scheme for lateral non-uniformly doped MOSFET is explained. A novel partitioning scheme is then developed and validated on the device simulation. For the first time, noise modeling of lateral non-uniformly doped MOSFET is carried out and validated on the device simulation.
(Un)expected Similarity of the Temporary Adhesive Systems of Marine, Brackish, and Freshwater Flatworms

Many free-living flatworms have evolved a temporary adhesion system, which allows them to quickly attach to and release from diverse substrates. In the marine Macrostomum lignano, the morphology of the adhesive system and the adhesion-related proteins have been characterised. However, little is known about how temporary adhesion is performed in other aquatic environments. Here, we performed a 3D reconstruction of the M. lignano adhesive organ and compared it to the morphology of five selected Macrostomum, representing two marine, one brackish, and two freshwater species. We compared the protein domains of the two adhesive proteins, as well as an anchor cell-specific intermediate filament. We analysed the gene expression of these proteins by in situ hybridisation and performed functional knockdowns with RNA interference. Remarkably, there are almost no differences in terms of morphology, protein regions, and gene expression based on marine, brackish, and freshwater habitats. This implies that glue components produced by macrostomids are conserved among species, and this set of two-component glue functions from low to high salinity. These findings could contribute to the development of novel reversible biomimetic glues that work in all wet environments and could have applications in drug delivery systems, tissue adhesives, or wound dressings.
A two-dimensional ion-pump of a vanadium pentoxide nanofluidic membrane

The reactive surface and layered crystal structure of vanadium pentoxide (V2O5) are exploited here to prepare a two-dimensional (2D) ion pump that transports ions against their concentration gradient. The exfoliated layers of V2O5 were assembled into membrane form to create ion-channels with excellent nanofluidic transport characteristics. At the surface-charge-governed regime, the flexible and freestanding membrane of V2O5 showed a remarkable proton conductivity (∼0.01 S cm−1). The activation energy of proton conductivity (0.066 eV) suggests that the exceptional mobility of H+ ions (5.2 × 10−3 cm2 V−1 s−1) inside V2O5 ion-channels originates from the coordinated hopping of charges between the two-dimensionally arranged water molecules. The transport characteristics of V2O5 ion-channels can also be tuned just by tailor-cutting its lamellar membranes into different shapes. While rectangular devices of V2O5 membranes exhibit linear I–V curves, the triangularly cut membranes display a diode-like non-linear I–V curve. The ionic current rectification in the V2O5 triangle was found to originate from a combination of the unipolar conductivity of counter-ions inside the 2D nanochannels and geometrical asymmetry. The 2D ion rectifier of V2O5 also pumps ions at the rate of 3.32 × 10−8 amp s−1 against a 1000-fold concentration gradient under a fluctuating external potential with zero mean.
Balanced Sourcing: Cooperation and Competition in Supplier Relationships

Foreword Preface Part One: A New Model for Purchasing 1. The Emergence of Balanced Sourcing 2. Transforming the Organization Part Two: Building the Capabilities 3. Modeling Total Cost 4. Creating Sourcing Strategies 5. Building Sustainable Relationships 6. Integrating the Supply Web 7. Leveraging Supplier Innovation 8. Evolving a Global Supply Base Part Three: Balanced Sourcing Case Studies 9. Florida Power and Light Company 10. SUPERVALU 11. Honda of America 12. Cisco Systems Notes The Author Index Booz-Allen and Hamilton.
Biochar and compost amendments alter the structure of the soil fungal network in a karst mountainous area

The karst ecosystem is prone to degradation and this accounts for a large proportion of land degradation in southwestern China. In order to improve the nutrient status and microbial community structure of karst soil, the amendment method of combining biochar, compost, and chemical fertilizer l was explored. With CK as the control, M as manure compost, B as wood biochar, and F as chemical fertilizer, field trials were set up with eight treatments. The results showed that the biochar treatments led to higher fungal diversity and soil nutrient content than no‐biochar treatments, and the compost treatments resulted in higher fungal diversity and soil nutrient content than no‐compost treatments. Cluster and linear discriminant analysis effect size (LEfSe) analyses indicated that the composition and structure of the fungal community varied under different treatments; both the compost fungal network and biochar fungal network were more complex than their respective control networks. Soil carbon and nutrient fractions had significant effects on soil fungal networks. In short, the addition of both biochar and manure compost enlarged the complexity of microbial‐related networks and enhanced the soil nutrient status, indicating that biochar‐based fertilizer was beneficial in karst‐degraded soil restoration.
Human Factors Analysis of a Waiver: A Case Study

Case law has questioned the enforceability of waivers due to deficiencies in two categories: whether the defendant took reasonable steps to bring notice of the waiver and its contents to the attention of the plaintiff, and whether the waiver contained key design flaws. This report presents a case study on an accident at a recreational sports facility. An analysis was conducted on two versions of the facility’s waiver from a human factors perspective. The analysis reveals the application of forensic human factors concepts to waiver design and the influence that improperly designed waivers can have on sports and recreational injury lawsuits.
Bouwers aan de slag of in de slag? : lessen uit internationale samenwerking : onderzoek naar Nederlandse ervaringen in het Duitse bouwproces

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Attributing Blame in Human-Robot Teams with Robots of Differing Appearance

As automation becomes increasingly common in daily life the importance of understanding how we interact with automated systems increases, especially attribution of blame for accidents involving a human-automation team. The current research project looks at how humans attribute blame in an accident involving a human operator and a robot worker and is based on a previous study (Furlough et al., 2019). Participants will read two scenarios detailing an accident while being shown both the operator and robot. The robot’s appearance is manipulated to imply varying levels of automation, ranging from a simple robot to one with a human appearance. Results showed no significant effects, however, this research still has the potential to contribute to the understanding of interactions between humans and automated systems and could inform design in the future to facilitate a positive working environment with robots and humans.
Albumin Substitution in Decompensated Liver Cirrhosis: Don’t Forget Zinc

Decompensated liver cirrhosis has a dismal prognosis, with patients surviving on average for 2–4 years after the first diagnosis of ascites. Albumin is an important tool in the therapy of cirrhotic ascites. By virtue of its oncotic properties, it reduces the risk of cardiovascular dysfunction after paracentesis. Treatment with albumin also counteracts the development of hepatorenal syndrome and spontaneous bacterial peritonitis. More recently, the positive impact of long-term albumin supplementation in liver disease, based on its pleiotropic non-oncotic activities, has been recognized. These include transport of endo- and exogenous substances, anti-inflammatory, antioxidant and immunomodulatory activities, and stabilizing effects on the endothelium. Besides the growing recognition that effective albumin therapy requires adjustment of the plasma level to normal physiological values, the search for substances with adjuvant activities is becoming increasingly important. More than 75% of patients with decompensated liver cirrhosis do not only present with hypoalbuminemia but also with zinc deficiency. There is a close relationship between albumin and the essential trace element zinc. First and foremost, albumin is the main carrier of zinc in plasma, and is hence critical for systemic distribution of zinc. In this review, we discuss important functions of albumin in the context of metabolic, immunological, oxidative, transport, and distribution processes, alongside crucial functions and effects of zinc and their mutual dependencies. In particular, we focus on the major role of chronic inflammatory processes in pathogenesis and progression of liver cirrhosis and how albumin therapy and zinc supplementation may affect these processes.
NaCoDAE: Navy Conversational Decision Aids Environment

This report documents NaCoDAE, the Navy Conversational Decision Aids Environment being developed at the Navy Center for Applied Research in Artiicial Intelligence (NCARAI), which is a branch of the Naval Research Laboratory. Na-CoDAE is a software prototype that is being developed under the Practical Advances in Case-Based Reasoning project, which is funded by the OOce for Naval Research, for the purpose of assisting Navy and other DoD personnel in decision aids tasks such as system maintenance, operational training, crisis response planning, logistics, fault diagnosis, target classiication, and meteorological nowcasting. Implemented in Java, NaCoDAE can be used on any machine containing a Java virtual machine (e.g., PCs, Unix). This document describes and exempliies NaCoDAE's capabilities. Our goal is to transition this tool to operational personnel, and to continue its enhancement through user feedback and by testing recent research advances in case-based reasoning and related areas.
Evaluation of vehicle body stiffness and strength for car to car compatibility

When considering a car to car frontal crash between a small light car and a large heavy car, it is necessary to evaluate the stiffness and strength of each vehicle body. As interactive force at the contact surface cannot be measured directly in a car to car crash test, a simplified practical method has been developed to estimate the interactive force based on the vehicle deceleration. The adequacy and consistency of the proposed method was verified by using the principle of conservation of energy. The calculated force-deformation curves revealed that the interactive force reached the maximum designed strength of the small light car based on the ODB (Offset Deformable Barrier) test for crash protection, while the force level was far below the corresponding design limit of the large heavy car. It was observed that the relatively lower stiffness of the small light car resulted in absorbing a larger share of the total input energy of the system when crashed into the large heavy car. By analyzing the interactive force profile in detail, it was found that the maximum impact force and the end of crash force could be used as a barometer to assess car to car crash compatibility.
Efficient Group K Nearest-Neighbor Spatial Query Processing in Apache Spark

Aiming at the problem of spatial query processing in distributed computing systems, the design and implementation of new distributed spatial query algorithms is a current challenge. Apache Spark is a memory-based framework suitable for real-time and batch processing. Spark-based systems allow users to work on distributed in-memory data, without worrying about the data distribution mechanism and fault-tolerance. Given two datasets of points (called Query and Training), the group K nearest-neighbor (GKNN) query retrieves (K) points of the Training with the smallest sum of distances to every point of the Query. This spatial query has been actively studied in centralized environments and several performance improving techniques and pruning heuristics have been also proposed, while, a distributed algorithm in Apache Hadoop was recently proposed by our team. Since, in general, Apache Hadoop exhibits lower performance than Spark, in this paper, we present the first distributed GKNN query algorithm in Apache Spark and compare it against the one in Apache Hadoop. This algorithm incorporates programming features and facilities that are specific to Apache Spark. Moreover, techniques that improve performance and are applicable in Apache Spark are also incorporated. The results of an extensive set of experiments with real-world spatial datasets are presented, demonstrating that our Apache Spark GKNN solution, with its improvements, is efficient and a clear winner in comparison to processing this query in Apache Hadoop.
Cross-Domain Object Representation via Robust Low-Rank Correlation Analysis

Cross-domain data has become very popular recently since various viewpoints and different sensors tend to facilitate better data representation. In this article, we propose a novel cross-domain object representation algorithm (RLRCA) which not only explores the complexity of multiple relationships of variables by canonical correlation analysis (CCA) but also uses a low rank model to decrease the effect of noisy data. To the best of our knowledge, this is the first try to smoothly integrate CCA and a low-rank model to uncover correlated components across different domains and to suppress the effect of noisy or corrupted data. In order to improve the flexibility of the algorithm to address various cross-domain object representation problems, two instantiation methods of RLRCA are proposed from feature and sample space, respectively. In this way, a better cross-domain object representation can be achieved through effectively learning the intrinsic CCA features and taking full advantage of cross-domain object alignment information while pursuing low rank representations. Extensive experimental results on CMU PIE, Office-Caltech, Pascal VOC 2007, and NUS-WIDE-Object datasets, demonstrate that our designed models have superior performance over several state-of-the-art cross-domain low rank methods in image clustering and classification tasks with various corruption levels.
Single-Cell Genomics: Enabling the Functional Elucidation of Infectious Diseases in Multi-Cell Genomes

Since the time when detection of gene expression in single cells by microarrays to the Next Generation Sequencing (NGS) enabled Single Cell Genomics (SCG), it has played a pivotal role to understand and elucidate the functional role of cellular heterogeneity. Along this journey to becoming a key player in the capture of the individuality of cells, SCG overcame many milestones, including scale, speed, sensitivity and sample costs (4S). There have been many important experimental and computational innovations in the efficient analysis and interpretation of SCG data. The increasing role of AI in SCG data analysis has further enhanced its applicability in building models for clinical intervention. Furthermore, SCG has been instrumental in the delineation of the role of cellular heterogeneity in specific diseases, including cancer and infectious diseases. The understanding of the role of differential immune responses in driving coronavirus disease-2019 (COVID-19) disease severity and clinical outcomes has been greatly aided by SCG. With many variants of concern (VOC) in sight, it would be of great importance to further understand the immune response specificity vis-a-vis the immune cell repertoire, the identification of novel cell types, and antibody response. Given the potential of SCG to play an integral part in the multi-omics approach to the study of the host–pathogen interaction and its outcomes, our review attempts to highlight its strengths, its implications for infectious disease biology, and its current limitations. We conclude that the application of SCG would be a critical step towards future pandemic preparedness.