Miracle-dz/UniFAR-FTUs huggingface dataset:
Global land-surface evaporation estimated from satellite-based observations

Abstract. This paper outlines a new strategy to derive evaporation from satellite observations. The approach uses a variety of satellite-sensor products to estimate daily evaporation at a global scale and 0.25 degree spatial resolution. Central to this methodology is the use of the Priestley and Taylor (PT) evaporation model. The minimalistic PT equation combines a small number of inputs, the majority of which can be detected from space. This reduces the number of variables that need to be modelled. Key distinguishing features of the approach are the use of microwave-derived soil moisture, land surface temperature and vegetation density, as well as the detailed estimation of rainfall interception loss. The modelled evaporation is validated against one year of eddy covariance measurements from 43 stations. The estimated annual totals correlate well with the stations' annual cumulative evaporation (R=0.80, N=43) and present a low average bias (−5%). The validation of the daily time series at each individual station shows good model performance in all vegetation types and climate conditions with an average correlation coefficient of R =0.83, still lower than the R =0.90 found in the validation of the monthly time series. The first global map of annual evaporation developed through this methodology is also presented.
LTE-U over Wi-Fi

LTE is a standard for wireless data communications technology and a development of the GSM/UMTS standards, aimed at increasing the capacity and speed of wireless data networks, in licensed band. Now, LTE is being upgraded to LTE-U, which utilizes the unlicensed band. Wi-Fi is a local area wireless technology that allows an electronic device to exchange data or connect to the internet using 2.4 GHz UHF and 5 GHz SHF radio waves. Wi-Fi follows IEEE 802.11 standards. The latest standard of Wi-Fi that is in use is 802.11ac. It uses 5 GHz band only. This paper examines Wifi and its various standards, LTE and its bands, the difference between Wi-Fi (802.11ac) and LTE-U, and the need why unlicensed spectrum is used. We shall mainly focus on layer one and layer two parameters.
Self-Configuration and Reachability Metrics in Massively Defective Multiport Chips

The downsizing of transistor dimensions enabled in the future nanotechnologies will inevitably increase the number of faults in the complex ULSI chips. To maintain the production yield at acceptable level, several levels of protection mechanisms will have to be implemented to tolerate the permanent and transient faults occurring in the physical layers. In this paper, we study fault tolerance at the architectural level in multiport processor grids (MPG) through core dual diagnosis and self-configuration of communications. MPGs are considered to ensure the scalability of future hundred-core chips. We characterize defective technologies by the IOP reachability (i.e., the ability of the IOPs to contact a fraction of cores in the grid) that we study as a function of the fraction of defective cores or links. We show that almost all valid cores in the grid are accessible by all input-output ports (IOP) up to approximately 20-25% of defective cores. This property is quasi-independent of the position of the IOPs in the grid.
Designing Meaning and Identity in Multiliteracies Pedagogy: From Multilingual Subjects to Authentic Speakers

Author(s): Blyth, Carl | Abstract: This essay examines textual engagement of two students during a Multiliteracies lesson on a French poem (Liberte, Paul Eluard) in terms of the multilingual subject (Kramsch, 2009) and the authentic speaker (Van Compernolle, 2016). The case studies are based on personal data: (1) the students’ autobiographies written on the first day of the course; (2) the transcript of their annotated comments about the poem; (3) their essays comparing the French poem to an English translation; and (4) their retrospective analysis about the effects of the multiliteracies lesson and course. The essay begins with a review of the Multiliteracies Framework, and the concepts of the multilingual subject and the authentic speaker. Next, the essay turns to a description of the subjective experiences of the two learners. Finally, the essay illustrates how the two students filtered the poem through their own subjectivities to arrive at a new sense of multilingual authenticity.
Web Service Integration Using Cloud Data Store Web Service Integration Using Cloud Data Store Web Service Integration Using Cloud Data Store Web Service Integration Using Cloud Data Store

Current Web users usually have their own files, work documents, communications and personal contacts distributed in the storage systems of many widely-used Internet services (e.g. Google Docs, Gmail, Face book, Zoho). Therefore, they face the challenge of being not able to have an integrated view for their related data objects (e.g. mails, pics, docs, contacts). Recently, most of the major Internet services provide standard APIs that allow developing software applications that can read and write data from their underlying data store after providing the credential access information of registered accounts. The World Wide Web is witnessing an increase in the amount of structured content – vast heterogeneous collections of structured data are on the rise due to the Deep Web, annotation schemes like Flickr, and sites like Google Base. While this phenomenon is creating an opportunity for structured data management, dealing with heterogeneity on the web-scale presents many new challenges. In this paper, we highlight these challenges in two scenarios – the Deep Web and Google Base. We contend that traditional data integration techniques are no longer valid in the face of such heterogeneity and scale. We propose new data integration architecture, as means for achieving web-scale data integration.
Quantifying River Bank Erosion with Scanning Laser Altimetry

Detailed topographic data collected with an airborne laser scanner can help determine the extent of bank erosion and identify banks that are more vulnerable to bank collapse and thus require stabilization efforts. The Minnesota River which flows through a 95% agricultural watershed has been ranked among the top 20 most polluted rivers in the U.S. Greater than 50% of the sediment load carried by the river at Mankato, MN is delivered by a single tributary, the Blue Earth River. A 56km length of the main stem of the Blue Earth River corridor was scanned April 2001 with an helicopter mounted Topeye laser system. The database includes X, Y, Z coordinates of laser returns from the river valley plus return intensity. Other data collection included ground elevation measurements for two banks using a total station, and vegetation density at eight locations along the river. A bare earth model was constructed by removing returns from vegetation and is currently being tested against the ground elevation measurements. Plans are to make another scan in a year or more to calculate volumetric change in the river valley due to bank erosion / bank collapse. This volume change along with soil bulk density along the river corridor will be used to assess the extent of bank erosion. The mass wasting rates will then be converted to total suspended sediments assuming fine silt and clay fractions are most likely to be transported.
Evaluation of the L5 spinal nerve ligation on Aδ- and C-fibers activation threshold and also LTP-induced by electrical high frequency stimulation of sciatic nerve in spinal dorsal horn of rats

Background: The underlying central mechanisms for the development and maintenance of neuropathic pain are unknown. The current study aimed to evaluate the long-term potentiation (LTP) changes in spinal dorsal horn wide dynamic range (WDR) neurons following a peripheral neuropathy model. Materials and Methods: This study was conducted on 26 male Wistar rats. The spinal nerve ligation (SNL) model was performed to induce neuropathy. After surgery, thermal hyperalgesia and mechanical allodynia were evaluated one day before neuropathy, and then on days 2, 5, 7, 14, 21 and 28 after neuropathy. Single-unit recording was used to study the changes of LTP. The changes of LTP and Aδ- and C-fiber evoked responses by highfrequency stimulation (100 Hz and current intensity six times that of the threshold for activation of C- fibers) of sciatic nerve in spinal WDR synapses were studied on day 14 after surgery up to 2 hours. Results: Neuropathy was induced thermal hyperalgesia and mechanical allodynia on day 2 and persisted for 28 days after neuropathy. Electrophysiological recording revealed that HFS induced LTP either in the Aδ- or in the C-fibers in both sham and neuropathy groups up to 2 hr on day 14 after neuropathy. Neuropathy also significantly decreased the threshold of these fibers. Conclusion: LTP-induced HFS in spinal WDR neurons can be one of the underlying central mechanisms in the maintenance of neuropathic pain.
Silent Synapses in the Developing Rat Visual Cortex: Evidence for Postsynaptic Expression of Synaptic Plasticity

In the developing visual cortex activity-dependent refinement of synaptic connectivity is thought to involve synaptic plasticity processes analogous to long-term potentiation (LTP). The recently described conversion of so-called silent synapses to functional ones might underlie some forms of LTP. Using whole-cell recording and minimal stimulation procedures in immature pyramidal neurons, we demonstrate here the existence of functionally silent synapses, i.e., glutamatergic synapses that show only NMDA receptor-mediated transmission, in the neonatal rat visual cortex. The incidence of silent synapses strongly decreased during early postnatal development. After pairing presynaptic stimulation with postsynaptic depolarization, silent synapses were converted to functional ones in an LTP-like manner, as indicated by the long-lasting induction of AMPA receptor-mediated synaptic transmission. This conversion was dependent on the activation of NMDA receptors during the pairing protocol. The selective activation of NMDA receptors at silent synapses could be explained presynaptically by assuming a lower glutamate concentration compared with functional ones. However, we found no differences in glutamate concentration-dependent properties of NMDA receptor-mediated PSCs, suggesting that synaptic glutamate concentration is similar in silent and functional synapses. Our results thus support a postsynaptic mechanism underlying silent synapses, i.e., that they do not contain functional AMPA receptors. Synaptic plasticity at silent synapses might be expressed postsynaptically by modification of nonfunctional AMPA receptors or rapid membrane insertion of AMPA receptors. This conversion of silent synapses to functional ones might play a major role in activity-dependent synaptic refinement during development of the visual cortex.
Predictive Clinical Decision Support System with RNN Encoding and Tensor Decoding

With the introduction of the Electric Health Records, large amounts of digital data become available for analysis and decision support. When physicians are prescribing treatments to a patient, they need to consider a large range of data variety and volume, making decisions increasingly complex. Machine learning based Clinical Decision Support systems can be a solution to the data challenges. In this work we focus on a class of decision support in which the physicians' decision is directly predicted. Concretely, the model would assign higher probabilities to decisions that it presumes the physician are more likely to make. Thus the CDS system can provide physicians with rational recommendations. We also address the problem of correlation in target features: Often a physician is required to make multiple (sub-)decisions in a block, and that these decisions are mutually dependent. We propose a solution to the target correlation problem using a tensor factorization model. In order to handle the patients' historical information as sequential data, we apply the so-called Encoder-Decoder-Framework which is based on Recurrent Neural Networks (RNN) as encoders and a tensor factorization model as a decoder, a combination which is novel in machine learning. With experiments with real-world datasets we show that the proposed model does achieve better prediction performances.
Host-associated differentiation in a highly polyphagous, sexually reproducing insect herbivore

Insect herbivores may undergo genetic divergence on their host plants through host-associated differentiation (HAD). Much of what we know about HAD involves insect species with narrow host ranges (i.e., specialists) that spend part or all their life cycle inside their hosts, and/or reproduce asexually (e.g., parthenogenetic insects), all of which are thought to facilitate HAD. However, sexually reproducing polyphagous insects can also exhibit HAD. Few sexually reproducing insects have been tested for HAD, and when they have insects from only a handful of potential host-plant populations have been tested, making it difficult to predict how common HAD is when one considers the entire species’ host range. This question is particularly relevant when considering insect pests, as host-associated populations may differ in traits relevant to their control. Here, we tested for HAD in a cotton (Gossypium hirsutum) pest, the cotton fleahopper (CFH) (Pseudatomoscelis seriatus), a sexually reproducing, highly polyphagous hemipteran insect. A previous study detected one incidence of HAD among three of its host plants. We used Amplified fragment length polymorphism (AFLP) markers to assess HAD in CFH collected from an expanded array of 13 host-plant species belonging to seven families. Overall, four genetically distinct populations were found. One genetically distinct genotype was exclusively associated with one of the host-plant species while the other three were observed across more than one host-plant species. The relatively low degree of HAD in CFH compared to the pea aphid, another hemipteran insect, stresses the likely importance of sexual recombination as a factor increasing the likelihood of HAD.
The redshift distribution of type Ia supernovae: constraints on progenitors and cosmic star formation history

We use the redshift distribution of type Ia supernovae (SNe) discovered by the Supernova Cosmology Project to constrain the star formation history (SFH) of the Universe and SN Ia progenitor models. Given some of the recent determinations of the SFH, the observed SN Ia redshift distribution indicates a long (≥1 h -1 Gyr) mean delay time between the formation of a stellar population and the explosion of some of its members as SNe Ia. For example, if the SFH of Madau et al. is assumed, the delay time τ is constrained to be τ ≥ 1.7(τ ≥ 0.7) h -1 Gyr at the 95 per cent (99 per cent) confidence level (CL). SFHs that rise at high redshift, similar to those advocated by Lanzetta et al., are inconsistent with the data at the 95 per cent CL unless r > 2.5 h -1 Gyr. Long time-delays disfavour progenitor models such as edge-lit detonation of a white dwarf accreting from a giant donor, and the carbon core ignition of a white dwarf passing the Chandrasekhar mass due to accretion from a subgiant. The SN Ia delay may be shorter, thereby relaxing some of these constraints, if the field star formation rate falls, between z = 1 and the present, less sharply than implied, e.g. by the original Madau plot. We show that the discovery of larger samples of high-z SNe Ia by forthcoming observational projects should yield strong constraints on the progenitor models and the SFH. In a companion paper, we demonstrate that if SNe Ia produce most of the iron in galaxy clusters, and the stars in clusters formed at z ∼ 2, the SN Ia delay time must be lower than 2 Gyr. If so, then the SFH of Lanzetta et al. will be ruled out by the data presented here.
Nonlinear Inversion with L 1-Wavelet Regularization – Application to Autocalibrated Parallel Imaging

To improve parallel imaging techniques with autocalibration, algorithms were recently presented which estimate the coil sensitivities and the image at the same time [1,2]. However, even with perfectly known coil sensitivites parallel imaging suffers from much lower SNR than to be expected from the reduced scan time alone. This is due to the reconstruction process (quantified by the g-factor map) and usually counteracted by regularization. Linear reconstruction methods are restricted to a regularization term which is related to the L2-norm of the image. Nevertheless, nonlinear regularization methods like the L1-norm in combination with a sparsity transform or total variation are known to suppress noise much more efficiently. This work demonstrates how L1-wavelet regularization can be incorporated into an autocalibrating parallel imaging algorithm based on a regularized nonlinear inversion method described earlier [2].
Automatic fault detection and diagnosis for photovoltaic systems using combined artificial neural network and analytical based methods

Long term exposure of photovoltaic (PV) systems under relatively harsh and changing environmental conditions can result in fault conditions developing during the operational lifetime. The present solution is for system operators to manually perform condition monitoring of the PV system. However, it is time-consuming, inaccurate and dangerous. Thus, automatic fault detection and diagnosis is a critical task to ensure the reliability and safety in PV systems. The current state-of-the-art techniques either cannot provide enough detailed fault information with high accuracy or have too much complexity. This work presents an automatic fault detection and diagnosis method for string based PV systems. It combines an artificial neural network (ANN) with the conventional analytical method to conduct the fault detection and diagnosis tasks. A two-layered ANN is applied to predict the expected power which is then compared with the measured power from the real PV system. Based on the difference between the ANN estimated power and the measured power, the open circuit voltage and short circuit current of the PV string determined using analytical equations are used to identify any of the six defined fault types. The proposed method has a fast detection, compact structure and good accuracy. Simulation results show the effective fault detection and diagnosis capability of the proposed method.
“Homelang” or how to live in a language

The society we are living in is the society of a simple click that opens the world, breaks the barriers and gives access to any type of information no matter time or space. Today, we can live, without any problems, in almost any language. It depends on the person’s interest and willingness to live in a certain language. The study aims at placing the term “home” in a close connection with the term “language” by determining whether the word is the only house that we have and accepting that language is a continuously changing and lifelong battlefield . With the help of metaphors (living metaphor, distance metaphor, mother metaphor, birth and family metaphor, etc.) that are among our principle tools for understanding the construction of linguistic, social and political reality, we have tried to conduct a double levelled research: on one side, the paper aims to identify the identity framework of living in a language (as a mother tongue, as a regional language – dialects, as a national language or official language, as a foreign language learning – which undoubtedly implies foreign culture learning by increasing awareness and developing people’s curiosity towards the target culture and their own, and, of course, helping people to be able to make comparisons among cultures or as a European language according to the Common European Framework for Foreign Languages which provides a common basis for the elaboration of language syllabuses, curriculum guidelines, examinations, textbooks across Europe or as a lingua franca ) . On the other side, the paper aims to highlight the fact that there are also risks related to the language leaving phenomenon. We live in a language in different ways, but at the same time, for different reasons, people are tempted to leave the language: immigration, high-tech effects, etc. Living in a language vs. leaving a language interfere and the two phenomena still raise questions among researchers and linguists.
Transfer Matrix Approach to the Triangular Decoupling of General Neutral Multi-Delay Systems

Abstract The following major aspects of the problem of Input–Output Triangular Decoupling (TD) for general neutral multi–delay systems, via proportional realizable state feedback, are resolved for the first time: The necessary and sufficient conditions for the problem to have a realizable solution and the general analytical expressions of the proportional realizable TD controller matrices. The conditions and the solution of the controller matrices are computed using a finite step pure algebraic approach.
Species‐specific differences in the ability of feline lentiviral Vif to degrade feline APOBEC3 proteins

How host–virus co‐evolutionary relationships manifest is one of the most intriguing issues in virology. To address this topic, the mammal–lentivirus relationship can be considered as an interplay of cellular and viral proteins, particularly apolipoprotein B mRNA editing enzyme catalytic polypeptide‐like 3 (APOBEC3) and viral infectivity factor (Vif). APOBEC3s enzymatically restrict lentivirus replication, whereas Vif antagonizes the host anti‐viral action mediated by APOBEC3. In this study, the focus was on the interplay between feline APOBEC3 proteins and two feline immunodeficiency viruses in cats and pumas. To our knowledge, this study provides the first evidence of non‐primate lentiviral Vif being incapable of counteracting a natural host's anti‐viral activity mediated via APOBEC3 protein.
Maintenance of Normal Stress Tolerance in the Moss Physcomitrella patens Lacking Chloroplastic CuZn-Superoxide Dismutase

Superoxide dismutases (SODs) catalyze the dismutation of superoxide and play an important role in reducing oxidative stress in plants. Based on in-gel SOD activity staining, chloroplasts of the moss Physcomitrella patens have two CuZn-SODs as the major SOD isozymes and minor SODs, including a Fe-SOD and two Mn-SODs. To investigate the contribution of chloroplastic SODs to stress tolerance in P. patens, we generated a double mutant lacking chloroplastic CuZn-SOD genes. The mutant did not show any differences in comparison to the wild type based on the growth of protonemata on normal and high-salt media, extractable activities of the other SODs after culture on normal and high-salt media, and inhibition of Fv/Fm under stress conditions (high-salt, high-light, and high-temperature). These results indicate that chloroplastic CuZn-SODs do not play a principal role in oxidative stress tolerance in chloroplasts under the investigated conditions. These findings explain the previously reported unusual response of P. patens to copper deficiency, in which chloroplastic CuZn-SODs are preferentially inactivated but cytosolic CuZn-SODs are unaffected.
Euclidean Distance Geometry and Applications

Euclidean distance geometry is the study of Euclidean geometry based on the concept of distance. This is useful in several applications where the input data consist of an incomplete set of distances and the output is a set of points in Euclidean space realizing those given distances. We survey the theory of Euclidean distance geometry and its most important applications, with special emphasis on molecular conformation problems.