Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecosystem production potential in the Northwest Atlantic

From a theoretical perspective, ecosystem production potential (EPP) is the expected biomass/carbon that the entire biological community would produce out of the primary production generated in that region in ideal conditions. In its simplest conception, the EPP would be a function of the fraction of the primary production retained in that region and available to higher trophic levels, the transfer efficiency between successive trophic levels, and the number of trophic levels through which energy must be transferred (e.g. Ryther 1969, Ware 2000). In reality, other processes (e.g. transport, state of ecosystem components, environmental conditions and variability, climate change) would affect primary production and influence realized ecosystem production of higher trophic levels.
A PARAMETER ESTIMATE FOR THE LAND SURFACE MODEL VIC WITH HORTON AND DUNNE RUNOFF MECHANISM FOR RIVER BASINS IN CHINA

This paper presents a parameter estimate of the land surface model VIC to simulate streamflow for river basins in China by a methodology for model parameter transfer that limits the number of basins requiring direct calibration, where the new surface runoff parameterization that represents both Horton and Dunne runoff generation mechanisms with the framework of considering subgrid spatial scale soil heterogeneity in VIC is applied. The mainland area of China is represented by 4355 cells with a resolution of 50 × 50 km for each cell and grouped into climate zones. Initially, some of model parameters were calibrated for nine catchments, and those for the nine catchments were transferred within the climate zones. The transferred parameters were then used to simulate the water balance in six other catchments and river basins in China. The simulated daily runoff of VIC-3L with transferred and un-calibrated parameters is routed to the outlets of the catchments, and compared to the monthly-observed streamflow at the related gauge stations. As a whole, the parameter transfer approach reduced the bias and relative root mean squared error (RRMSE) and increased the Nash-Sutcliffe model efficiency coefficients for each individual catchment, and the parameter transfer scheme improved the streamflow simulation. Subsequent recalibration of all basins further enhanced the modeling performance. Results show that the model for the transferred parameters can simulate the observations accurately.
Effect of Longitudinal Concentration Gradient on 1-D Double-Period Detonation

A detonation wave manifested pulsations in one dimension [1] and cellular instability in multiple dimensions [2], depending on the initial conditions and mixture properties. In uniform media, an unstable 1-D detonation presents pulsating mode. Regarding pulsating instability, extensive experiments have shown longitudinal oscillation of the detonation front when a blunt body travels through a reactive gas at nearChapman-Jouguet (C-J) velocities [3, 4], while extensive theoretical analyses and numerical simulations have also been performed on the propagating instability [5]. In previous simulations, 1-D detonation instability usually was described by using one-step [1,6], two-step [7] models. Subsequently, some numerical studies of 1-D detonation were carried out by using real chemistry [8, 9].
Blood serum levels of ochratoxin A and nutrition habits

A statistical evaluation was carried out of the ochratoxin A (OTA) analyses of 785 serum samples from healthy volunteer blood donors of different parts of Germany and their data on nutritional habits. These were obtained by a retrospective food-frequency questionnaire covering the last four weeks before blood sampling. Statistical analyses of the OTA serum concentrations showed a significant effect due to location in Germany (p = 0.05), but no effect due to the other parameters such as sex, age, weight, body-mass-index and vegetarian diet. In case of the significantly high mean blood serum levels from persons from the Jena region the statistical analyses revealed a higher intake of blood type sausages and red grape juice and a lower intake of light beers compared to other regions. For 27 food items weak positive regression coefficients in the range of b = 0.004-0.0874 were obtained, while further 21 food items yielded weak negative regression coefficients ranging from (0.0195 to (0.0007. The statistical comparison of the persons with low, medium and high OTA-serum levels (0.2 ng/ml, 0.2-0.4 ng/ml and >0.4 ng/ml, respectively) showed significant effects (p = 0.05) due to the consumption of bread, rye bread, muesli, blood sausages, salami type sausages, chocolate with nuts and coffee. However, when summarising the results, it can be concluded that the ochratoxin A levels in human blood sera are not caused by one single food item or food group alone.
Structural Ductility of Edge-supported Two-Way Slabs Reinforced with Low-Ductility Steel

This paper describes a series of full range load tests on two-way, edge-supported reinforced concrete slab panels containing either Class L WWF or Class N deformed bars. Five rectangular slab panels were tested each with two free edges and two adjacent edges continuously supported. A point support was included under the corner of each panel at the intersection of the two free edges. Each slab specimen was loaded by four transverse loads applied symmetrically in the mid-panel region by a deformation controlled actuator in a stiff testing frame. The continuous edge supports were provided by clamping two adjacent edges in a carefully designed and constructed testing frame. The slabs were instrumented with load cells to measure applied forces and reactions, strain gauges to measure strain in the steel reinforcement and on the concrete surfaces, linear variable displacement transducers and lasers to measure deflections at all stages of loading. The results of the tests are presented and evaluated, with particular emphasis on the strength, ductility and failure mode of the slabs.
Smoking and womens health.

Each year more than 600000 women have deaths associated with cigarette smoking. In addition cigarette smoking is associated with a wide array of morbidities (such as osteoporosis cardiovascular disease and adverse pregnancy outcomes). 200 million women smoke worldwide and this number appears to be rising particularly in developing countries. Obstetrician-gynecologists can play a role in reducing morbidity and mortality from cigarette smoking by educating women about the dangers advising them not to smoke and assisting those who do smoke to quit. (authors)
Study on Modelling Human Behavior in Cooperative Games

Modelling human behavior provides insight into the underlying decision making mechanisms, allows evaluation of performance and provides a framework for replicating the behaviour with autonomous agents. The behaviour can be observed from game situations, where the human subjects are making decisions in order to obtain rewards, for example. In this thesis we introduce a novel network-based game of group formation. The game is a limited information game that requires interactions between players with non-overlapping information. The game was implemented as an application for experiments and two different sessions with varying incentives were held in 2017 and 2018. The results from the 2017’s fully cooperative experiment were used to develop a data driven model based on probability matching for evaluating the effectiveness of the human behaviour as well as constructing autonomous agents or bots replicating the human subjects. The experiment in 2018 had an individualistic reward function and 3 treatments with varying hybrid groups of humans and bots. The behaviour of the human subjects was analyzed and compared to the previous cooperative setting and the differences between hybrid and non-hybrid treatments were measured. The study also includes a novel learning model in the style of Q-learning. The model was used as a benchmark for the probability matching model as well as a prior evaluation tool for the 2018 experiment. The results show that the human subjects’ risk perception is close to optimal, but the rationality behind decision making is not, when measured using the proposed framework. In an individualistic experiment, the human subjects’ behaviour was observed to be changed by the bots.
Towards high mobility InSb nanowire devices

We study the low-temperature electron mobility of InSb nanowires. We extract the mobility at 4.2 K by means of field effect transport measurements using a model consisting of a nanowiretransistor with contact resistances. This model enables an accurate extraction of device parameters, thereby allowing for a systematic study of the nanowire mobility. We identify factors affecting the mobility, and after optimization obtain a field effect mobility of ∼ × 2.5 104 cm V s. We further demonstrate the reproducibility of these mobility values which are among the highest reported for nanowires. Our investigations indicate that the mobility is currently limited by adsorption of molecules to the nanowire surface and/or the substrate. S Online supplementary data available from stacks.iop. org/nano/26/215202/mmedia
Scaling relation for the size dependence of acoustic, dielectric and photoelectronic behaviour of nanosolid silicon

Structural miniaturization provides us with a new freedom that is indeed fascinating. The new freedom of size not only allows us to tune the physical and chemical properties of a specimen by simply adjusting the shape and size but also enables us to gain information that is beyond the scope of conventional approaches. Here we show that a recent bond order-length-strength (BOLS) correlation could reconcile the size effect on nanosolid silicon with elucidation of information such as the single energy level of an isolated Si atom, the frequency of Si-Si dimer vibration, the upper limit of photoabsorption/emission, and dielectric suppression.
KnowSemLM: A Knowledge Infused Semantic Language Model

Story understanding requires developing expectations of what events come next in text. Prior knowledge – both statistical and declarative – is essential in guiding such expectations. While existing semantic language models (SemLM) capture event co-occurrence information by modeling event sequences as semantic frames, entities, and other semantic units, this paper aims at augmenting them with causal knowledge (i.e., one event is likely to lead to another). Such knowledge is modeled at the frame and entity level, and can be obtained either statistically from text or stated declaratively. The proposed method, KnowSemLM, infuses this knowledge into a semantic LM by joint training and inference, and is shown to be effective on both the event cloze test and story/referent prediction tasks.
Dynamic Slicing of RAN Resources for Heterogeneous Coexisting 5G Services

Network slicing is one of the key components allowing to support the envisioned 5G services, which are organized in three different classes: Enhanced Mobile Broadband (eMBB), massive Machine Type Communication (mMTC), and Ultra-Reliable and Low-Latency Communication (URLLC). Network Slicing relies on the concept of Network Softwarization (Software Defined Networking - SDN and Network Functions Virtualization - NFV) to share a common infrastructure and build virtual instances (slices) of the network tailored to the needs of different 5G services. Although it is straightforward to slice and isolate computing and network resources for Core Network (CN) elements, isolating and slicing Radio Access Network (RAN) resources is still challenging. In this paper, we leverage a two-level MAC scheduling architecture and provide a resource sharing algorithm to compute and dynamically adjust the necessary radio resources to be used by each deployed network slice, covering eMBB and URLLC slices. Simulation results clearly indicate the ability of our solution to slice the RAN resources and satisfy the heterogeneous requirements of both types of network slices.
MIR tools: Self-similarity matrices and dynamic time warp- ing

There are numerous motivations for seeking patterns in music: the need to identify recurring themes, identify musical structure, determine the start of a musical segment, discover rhythm, match timbre, or even just identify note onsets. Because music contains so many different hierarchical layers, pattern-identifying algorithms that don’t require training or involve assumptions about the type of music or sound being studied are highly desirable. Self-similarity matrices and dynamic time warping are tools that enable such identification. Self-similarity matrices match a series of musical features at set time frames to themselves, in order to show similarities and differences between those musical features at every pair of time frames in the series. Dynamic time warping enables mapping one set of musical events to another, when non-linear tempo or event variations are present in one line when compared to the other.
Revisiting Capability of PDG-based Clone Detection

Code cloning is an active research topic in the field of software engineering over the last two decades. Recently, many research efforts have been focusing on detecting clones from very large scale source code and detecting clones incrementally from multiple versions of source code. However, PDG(Program Dependency Graph)-based detection techniques have not been researched very actively over the last several years. In this paper, we revisit capability of the PDG-based clone detection and discuss its potential and importance. Besides, we propose new techniques, which increase capability of the PDG-based clone detection. The proposed techniques have already been implemented as a software tool, SCORPIO, which is open to the public. We evaluated the proposed techniques on four open source software by using the tool. The application result showed that the proposed techniques were able to detect more clones to be detected than conventional techniques without raising the rate of false positives.
Self-Sensing for Twisted String Actuators Using Conductive Supercoiled Polymers

The twisted string actuator (TSA), as a recently discovered artificial muscle, has attracted a lot of attention as a compliant and powerful actuation mechanism. A TSA consists of two strings attached to a motor on one end and a load on the other end. The motor’s rotation twists the strings and generates linear actuation. A common challenge is to obtain TSAs’ strains using compact approaches. Previous studies exclusively utilized external position sensors that not only increased system cost, size and complexity, but also lowered actuator compliance. In this paper, self-sensing strategies are presented to estimate TSAs’ strains without external sensors. By incorporating conductive and stretchable nylon strings, called super-coiled polymer (SCP) strings, into TSAs, their strains can be estimated from the resistance values of SCP strings. Two self-sensing configurations are realized: (1) TSA with one regular string and one SCP string, and (2) TSA with two SCP strings. Experiments are conducted to show the correlation between the length and resistance of TSA under different conditions. Polynomial and Preisach hysteresis models were successfully employed to capture the Length – Resistance correlation and to estimate TSA’s length using the resistance.
Performance Analysis of Antenna Using Fdtd

Microstrip patch antennas are widely used because of thin profile, light weight, low cost; conformability to shaped surface and compatibility with integrated circuits. In order to increase the strengths of antenna using time domain method, a micro strip patch antenna is directly treated in the time domain, using modified Finite Difference Time Domain (FDTD) method. The Finite Difference Time Domain (FDTD) method, first introduced by Yee, is a powerful, robust, and popular modelling algorithm based on the direct numerical solution of Maxwell’sequationsin the differential, time domain form. The most important feature of the FDTD method is that broad-band frequency information can be provided in a single pass simulation. It has been extensively used in the parameter extraction of wave guides, micro strip circuits and multiple coupled lines. Broad band characteristics of network parameters such as input impedance, scattering parameters are calculated from time domain simulated data. The Microstrip patch antenna is again simulated using Ansoft High Frequency Structure Simulator (HFSS) software. To reduce the cost, fR4 substrate with permittivity 4.4 is used. The obtained return loss also indicates the antenna has good matching at the output port. The result of the modelling is compared with HFSS simulated results to show effectiveness of this approach.
ADDITION OF TRANSITION ELEMENTS TO THE PHOSPHATE SEALING OF CERIUM OXIDE PROTECTIVE PRIMER DEPOSITED ON AA2024-T3 ALLOY

A concise investigation was undertaken to determine the impact of transitional elements on the phosphate sealing of cerium oxide primer layers deposited on AA2024-T3 aircraft alloy. The cerium oxide primer layers were deposited electrochemically on preliminary treated alloy specimens under potentiostatic conditions. The subsequent phosphate sealing layer deposition was performed in equimolar solutions of NaMoO4, NaVO3 or ZrO(NO3)2 in (NH4)2HPO4 medium for 30 min at 90oС. The already coated and sealed specimens were submitted to comparative measurements via electrochemical impedance spectroscopy and linear voltammetry after 168 h of exposure to 3.5% NaCl model corrosive medium. The obtained bi-layer coatings were characterized by systematic analyses using scanning electron microscopy, energy dispersion X-ray spectroscopy and X-ray photoelectron spectroscopy. The latter analysis evinced that cerium present in a cerium phosphate coating was predominantly in Ce(III) state, while doping by Mo, V and Zr caused oxidation to Ce(IV) species. The results obtained reveal successful inclusion of these elements inside the phosphate sealing layer.
SYNTHESIS AND CHARACTERIZATION OF TiO2 THIN FILM ON FLY ASH CENOSPHERES

Titanium dioxide (TiO2) thin films obtained on quartz glass and fly ash cenospheres were studied. Titanium(IV) butoxide (Ti(OBu)4), diethanoloamine (DEA), ethanol and deionized water were used as the starting materials. A layer of TiO2 nanoparticles was coated on the surface of the substrates using the sol-gel method. The thickness of the TiO2 coatings and the influence of the annealing temperature on the formation of TiO2 crystallites were studied. The dried gels were treated for 90 min in the temperature range of 400÷640°C to obtain crystallized anatase and rutile. Additional nanopowder TiO2 samples were prepared and their crystallinity was determined using X-ray diffraction (XRD). It was successfully shown that the anatase crystalline phase is formed when the TiO2 gel is heated to 480°C, while the rutile phase is obtained at 640°C. Changes in film thickness were studied using an atomic force microscope (AFM). The profound effect of gel viscosity on the thickness of the film was noticed. UV-Vis absorption spectroscopy, performed on the sample treated at 480°C (containing anatase phase only), showed strong ultraviolet light absorption below 400 nm. The estimated band-gap value was 3.2 eV. Transmission scanning microscopy (TEM) examination of the powders revealed agglomerated nanoparticles. A uniform, continuous layer on the surface of the treated microspheres was observed under a scanning electron microscope (SEM). The study shows that the annealing temperature has a profound effect on the phase composition and crystallite size of the sol-gel synthesized TiO2 nanopowders.
Rotation-invariant infrared aerial target identification based on SRC

Aircraft identification is implemented on thermal images acquired from ground-to-air infrared cameras. SRC is proved to be an effective image classifier robust to noise,which is quite suitable for thermal image tasks. However,rotation invariance is challenging requirements in this task. To solve this issue,a method is proposed to compute the target main orientation firstly,then rotate the target to a reference direction. Secondly,an overcomplete dictionary is learned from histogram of oriented gradient features of these rotated targets. Thirdly,a sparse representation model is introduced and the identification problem is converted to a l1-minimization prob⁃ lem. Finally,different aircraft types are predicted based on an evaluation index,which is called residual error. To validate the aircraft identification method,a recorded infrared aircraft dataset is implemented in an airfield. Experimental results show that the proposed method achieves 98. 3% accuracy,and recovers the identity beyond 80% accuracy even when the test images are corrupted at 50%.
Random Sketching, Clustering, and Short-Term Memory in Spiking Neural Networks

We study input compression in a biologically inspired model of neural computation. We demonstrate that a network consisting of a random projection step (implemented via random synaptic connectivity) followed by a sparsification step (implemented via winner-take-all competition) can reduce well-separated high-dimensional input vectors to well-separated low-dimensional vectors. By augmenting our network with a third module, we can efficiently map each input (along with any small perturbations of the input) to a unique representative neuron, solving a neural clustering problem. Both the size of our network and its processing time, i.e., the time it takes the network to compute the compressed output given a presented input, are independent of the (potentially large) dimension of the input patterns and depend only on the number of distinct inputs that the network must encode and the pairwise relative Hamming distance between these inputs. The first two steps of our construction mirror known biological networks, for example, in the fruit fly olfactory system [Caron et al., 2013; Lin et al., 2014; Dasgupta et al., 2017]. Our analysis helps provide a theoretical understanding of these networks and lay a foundation for how random compression and input memorization may be implemented in biological neural networks. Technically, a contribution in our network design is the implementation of a short-term memory. Our network can be given a desired memory time t_m as an input parameter and satisfies the following with high probability: any pattern presented several times within a time window of t_m rounds will be mapped to a single representative output neuron. However, a pattern not presented for c⋅t_m rounds for some constant c>1 will be "forgotten", and its representative output neuron will be released, to accommodate newly introduced patterns.
A New 2,2′-dipyridine and Its Analogues from Endophytic Streptomyces sp. KIB H017c with Potent Cytotoxicity

A new 2,2′-dipyridyl compound 1, along with three known analogues (2–4), was isolated from the culture broth of endophytic Streptomyces sp. KIB H017c derived from Fragaria ananassa. Their structures were elucidated by analysis of 1D and 2D NMR as well as HRESIMS data, and comparison with literature data. The biological properties of all isolates were explored for antibacterial, antifungal and cytotoxic activity. All four compounds exhibited weak antifungal activity against Saccharomyces cerevisiae, and compound 4 exhibited weak antifungal activity against Penicillium decumbens ATCC 10436. Compound 3 displayed moderate cytotoxic activity against HL-60 (human myeloid leukemia), SMMC-7721 (hepatocellular carcinoma), A-549 (lung carcinoma), MCF-7 (breast adenocarcinoma), and SW480 (colon carcinoma) with IC50 values of 12.10, 11.15, 23.64, 31.13 and 14.62 μM, respectively. Compound 4 exhibited potent activity against A-549 (lung carcinoma), MCF-7 (breast adenocarcinoma), and SW480 (colon carcinoma) with IC50 values 0.88, 0.34 and 0.55 μM, respectively.