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SUMMARY We analyse dominant sources identified in a catalogue of more than 156 000 localizations performed using a 26-d data set recorded by a dense array set on the San Jacinto fault near Anza, in California. Events were localized using an array processing technique called Match Field Processing. As for all array processing techniques, the quality of the event position decrease when the events are outside of the array. We thus separate localizations in and outside the array using simple geometrical conditions. We compare the time distribution of the localization to additional data such as meteorological data, day of human activity as well as existing catalogues to determine the nature of the dominant events located using our method. We find that most of the events located outside of the array could be attributed to a surface structure excited by wind. On the other hand, part of the localizations under the array occur during regional earthquakes and could correspond to diffraction on the fault's heterogeneities. The rest of the localizations inside the array could be generated by the fault itself.

We have analysed the response of cells on a bed of micro-posts idealized as a Winkler foundation using a homeostatic mechanics framework. The framework enables quantitative estimates of the stochastic response of cells along with the coupled analysis of cell spreading, contractility and mechano-sensitivity. In particular the model is shown to accurately predict that: (i) the extent of cell spreading, actin polymerisation as well as the traction forces that cells exert increase with increasing stiffness of the foundation; (ii) the traction forces that cells exert are primarily concentrated along the cell periphery; and (iii) while the total tractions increase with increasing cell area the average tractions are reasonably independent of cell area, i.e. for a given substrate stiffness, the average tractions that are normalized by cell area do not vary strongly with cell size. These results thus suggest that the increased foundation stiffness causes both the cell area and the average tractions that the cells exert to increase through higher levels of stress-fibre polymerization rather than the enhanced total tractions being directly linked through causation to the larger cell areas. A defining feature of the model is that its predictions are statistical in the form of probability distributions of observables such as the traction forces and cell area. In contrast, most existing models present solutions to specific boundary value problems where the cell morphology is imposed a priori. In particular, in line with observations we predict that the diversity of cell shapes, sizes and measured traction forces increase with increasing foundation stiffness. The homeostatic mechanics framework thus suggests that the diversity of observations in in vitro experiments is inherent to the homeostatic equilibrium of cells rather than being a result of experimental errors.

To reduce the efficiency reduction caused by non-uniformity of illumination, a dense-array module with non-uniform sizing of photovoltaic (PV) cells is proposed for dish-type concentrating PV systems. The non-uniform-sized dense-array module has been designed and analyzed theoretically at the ideal irradiance of Gaussian distribution, which consists of 48 silicone solar cells. Using the ZEMAX optical simulation software, the realistic distribution of the Gaussian-like facula on the PV module has been modelled in a dish-type concentrator system. The experiments are done under the conditions of different alignments to imitate the different two-axis tracking accuracy with or without a homogenizer. Besides, the performances of dense-array modules with the classical uniform-sized and the proposed non-uniform-sized PV cells are analyzed under various illumination distributions using ZEMAX, respectively. Results show that when the deviation angle of tracking is 0, 0.02, 0.2, the photoelectric conversion efficiency and output power of the proposed non-uniform size dense-array module considerably exceeds the traditional uniform size module. Furthermore, when the tracking deviation angle is no more than 0.02°, it is a very definite possibility that the dish-type concentrator system with non-uniform-sized dense-array module need not a homogenizer as a secondary optical element, which may hence simplify the system structure.

Colonoscopy screening for the detection and removal of colonic adenomas is central to efforts to reduce the morbidity and mortality of colorectal cancer. However, up to a third of adenomas may be missed at colonoscopy, and the majority of post-colonoscopy colorectal cancers are thought to arise from these. Adenomas have three-dimensional surface topographic features that differentiate them from adjacent normal mucosa. However, these topographic features are not enhanced by white light colonoscopy, and the endoscopist must infer these from two-dimensional cues. This may contribute to the number of missed lesions. A variety of optical imaging technologies have been developed commercially to enhance surface topography. However, existing techniques enhance surface topography indirectly, and in two dimensions, and the evidence does not wholly support their use in routine clinical practice. In this narrative review, co-authored by gastroenterologists and engineers, we summarise the evidence for the impact of established optical imaging technologies on adenoma detection rate, and review the development of photometric stereo (PS) for colonoscopy. PS is a machine vision technique able to capture a dense array of surface normals to render three-dimensional reconstructions of surface topography. This imaging technique has several potential clinical applications in colonoscopy, including adenoma detection, polyp classification, and facilitating polypectomy, an inherently three-dimensional task. However, the development of PS for colonoscopy is at an early stage. We consider the progress that has been made with PS to date and identify the obstacles that need to be overcome prior to clinical application.

We have studied HEMS (Home Energy Management System). In that study, we have regarded the wireless power transmission as the most useful energy source for sensor network node. Sensor network nodes need more than 100uW average power on working. Our scope of transmitting distance from power supplier to receiver is more than 1m. In our previous study we have shown the experimental result of more than 0.55m transmitting distance with one turn small loop coil and shown the possibility of further transmission by using other kinds of coil shape under the magnetic coupled method. In the latest paper we have shown the results of using silver nano-particle paste as the magnetic flux concentrator. In this study we have clarified the advantage of applying for repeating coils between transmitting coil and receiving coil. At first we have shown the results of introducing repeating coils by measurement. Next we have defined the scope concept as the novel concept. That is the concept for guaranteeing the transmitting efficiency in the scope range. We have measured and calculated the transmitting efficiency under the assumption that scope range is defined as 1m. As the results we can show the possibility of 1m rage transmission referring to the HEMS specification.

A three-dimensional heterostructure using selective growth of ZnO nanowires on TiO2/ZnO nanocomposite nanofiber by a novel combination of a postseeding method in an electrospinning process and a hy...

For the traditional DOA estimation of coherent and incoherent targets based on monostatic (massive) uniform dense array, the number of resolvable targets is limited to the number of physical sensors. To exceed the limitation, it is desirable to have sparse transmitting and receiving arrays. In this study, we consider the monostatic co-prime MIMO array with N sparse transmitters and 2M-1 sparse receivers in the DOA estimation of mixed coherent and incoherent targets. The sparse co-prime MIMO array with O( M + N ) physical sensors generates a non-redundant and uniform sub-coarray with O(MN) contiguous sensors in the sum co-array. Based on the defined wide-sense or narrow-sense sum co-array equivalence, we can obtain different configurations of virtual MIMO arrays with O(MN) contiguous virtual sensors, and then construct the corresponding virtual data matrices, which provides different tradeoffs between the number of resolvable targets and the maximum number of mutually coherent targets that can be resolved. On the basis of the virtual data matrix and the conventional DOA estimation approaches such as MUSIC, O(MN) mixed coherent and incoherent targets can be resolved only with O( M + N ) physical sensors, namely the number of resolvable targets exceeds the limitation of the number of physical sensors. Furthermore, the application of two additional operation frequencies extends the contiguous sub-coarray accompanied with the improvement of degree-of-freedom for more resolvable coherent and incoherent targets. Finally, simulation results demonstrate the effectiveness of the proposed DOA estimation method.

The 3D S-wave velocity of shallow structure, especially the Quaternary sediments at 0-1 km near the surface, is an important issue of concern in urban planning and construction for the requirements...

Electrostatic flocking is a textile technology that employs a Coulombic driving force to launch short fibers from a charging source towards an adhesive-covered substrate, resulting in a dense array of aligned fibers perpendicular to the substrate. However, electrostatic flocking of insulative polymeric fibers remains a challenge due to their insufficient charge accumulation. We report a facile method to flock electrostatically insulative poly(ε-caprolactone) (PCL) microfibers (MFs) and electrospun PCL nanofiber yarns (NFYs) by incorporating NaCl during pre-flock processing. Both MF and NFY were evaluated for flock functionality, mechanical properties, and biological responses. To demonstrate this platform's diverse applications, standalone flocked NFY and MF scaffolds were synthesized and evaluated as scaffold for cell growth. Employing the same methodology, scaffolds made from poly(glycolide-co-l-lactide) (PGLA) (90:10) MFs were evaluated for their wound healing capacity in a diabetic mouse model. Further, a flock-reinforced polydimethylsiloxane (PDMS) disc was fabricated to create an anisotropic artificial vertebral disc (AVD) replacement potentially used as a treatment for lumbar degenerative disc disease. Overall, a salt-based flocking method is described with MFs and NFYs, with wound healing and AVD repair applications presented., Graphical abstract This work reports electrostatic flocking of salt-treatment microfibers and nanofiber yarns for applications in wound healing and artificial vertebral disc replacement.Image 1, Highlights • NaCl coatings enable sufficient charge accumulation on electrically insulative polymer fibers during electrostatic flocking. • Flocked nanofiber yarns allow further functionalization of flocked scaffolds. • Flocked fiber scaffolds sustain cell proliferation. • Flocked PGLA (90:10) fiber scaffolds promote modest fiber-density dependent wound healing and angiogenesis. • Flock fibers-reinforced elastomeric artificial vertebral discs are mechanically robust.

KM3NeT/ORCA is a dense array that constitutes the low-energy branch of the KM3NeT project with the main goal of resolving the question of the neutrino mass ordering. At present, the KM3NeT/ORCA Phase 1 has already been deployed, which means that six out of the planned 115 detection lines are operational. Even with this limited configuration, neutrino oscillations can already be measured and studied. In this contribution, the sensitivity to the neutrino Non-Standard Interactions (NSI) parameter $\epsilon_{\mu \tau}$ using the current stage of the KM3NeT/ORCA detector together with the projections for the final configuration are presented.

This paper is devoted to the recently proposed mixing model with constant separating vector (CSV) for Blind Source Extraction of moving sources using the FastDIVA algorithm, which is an extension of the famous FastICA and FastIVA for static mixtures. The benefits due to the CSV model and FastDIVA are demonstrated in three new applications. First, the extraction of a moving speaker in a noisy reverberant environment using a dense array of 48 MEMS microphones is considered. Second, a case study on the blind extraction of moving brain activity from visually evoked potentials in electroencephalogram is reported. Third, a simulation of block-by-block online extraction of a moving source is demonstrated. In these examples, the CSV and FastDIVA show their new potential and good performance in handling the blind moving source extraction problem.

In this study, we investigate the shallow shear wave velocity structure of the Los Angeles Basin in southern California, using ambient noise correlations between 5 dense arrays and 21 broadband stations from the Southern California Seismic Network (SCSN). We observe clear fundamental mode and first overtone Rayleigh waves in the frequency band 0.25–2.0 Hz, and obtain group velocity maps through tomography. We further derive a 3D shear wave velocity model, covering a large portion of the central LA Basin for the depths shallower than 3 km. We found that the small scale shallow velocity structure heterogeneities are better resolved compared with the SCEC Community velocity models. Our model captures the presence of the Newport‐Inglewood fault by a NW–SE trending high velocity belt. Our model provides more accurate constraints on local ground motion predictions with detailed mapping of structural heterogeneities.

We derive the 3-D S-wave velocity structures of sediments and upper crust in the region off Ibaraki by applying ambient noise tomography to a dense array of short-period ocean bottom seismometers (...

SUMMARY We develop a methodology to separate continuous seismic waveforms into random noise (RN), not random noise (NRN) produced by earthquakes, wind, traffic and other sources of ground motions, and an undetermined mixture of signals. The analysis is applied to continuous records from a dense seismic array on the San Jacinto fault zone. To detect RN signals, we cut hourly waveforms into non-overlapping 1 s time windows and apply cross-correlations to separate RN candidates from outliers. The cross-correlation coefficients between different RN candidates fall into a tight range (i.e. 0.09–0.35), while cross-correlation coefficients of RN candidates with NRN signals (e.g. seismic or air-traffic events) are lower. The amplitude spectra of RN candidates have a well-defined level, while the amplitude spectra of other signals deviate from that level. Using these properties, we examine the amplitude spectra of moving time windows and cross-correlation coefficients with RN templates in each hour. The hourly RN is quasi-stationary and the results cluster tightly in the parameter space of cross-correlation coefficients and L2 norm deviations from the mean spectra of RN candidates. Time windows with parameters in this tight cluster are identified as RN, windows that deviate significantly from the RN cluster are identified as NRN and windows with values in between are identified as mixed signals. Several iterations on each hourly data are used to update and stabilize the selection of RN templates and mean noise spectra. For the days examined, the relative fractions of RN, NRN and mixed signals in local day (night) times are about 26 (42 per cent), 40 (33 per cent) and 34 per cent (25 per cent), respectively.

SUMMARY We introduce a methodology based on array processing to detect and locate weak seismic events in a complex fault zone environment. The method is illustrated using data recorded by a dense array of 1108 vertical component geophones in a 600 m × 600 m area on the Clark branch of the San Jacinto Fault. Because surface and atmospheric sources affect weak ground motion, it is necessary to discriminate them from weak seismic sources at depth. Source epicentral positions and associated apparent velocities are extracted from continuous seismic waveforms using Match Field Processing (MFP). We implement MFP at specific frequencies targeting surface and subsurface sources, using for computational efficiency a forward model of acoustic source in a homogenous medium and Markov Chain Monte Carlo sampling. Surface sources such as Betsy gun shots and a moving vehicle are successfully located. Weak seismic events are also detected outside of the array, and their backazimuth angle is retrieved and found to be consistent with the fault geometry. We also show that the homogeneous acoustic model does not yield satisfying results when extracting microseismic event depth, because of the ambiguity between depth and the apparent velocity based on surface data.

In this paper, the multi-physics effects on the performance of dense array concentrator photovoltaic (DA-CPV) system are investigated in detail by considering CPV module connections, non-uniform illumination, and temperature distribution. It is observed that the optimized module configuration can significantly reduce the overall cells temperature and then improve the efficiency and stability. We also analyze the effects of temperature uniformity on output performance. When the illumination, configuration and mean temperature are certain, the temperature distribution can affect the output performance of the DA-CPV system. In the case of non-uniform illumination, the maximum power of the module will be achieved with an inverse Gaussian temperature distribution, instead of uniform temperature. Through this comprehensive understanding the temperature effects of the DA-CPV module, a suitable cooling system can be designed to reduce power loss.

This study investigated the dynamic response and liquefaction of level saturated-sand deposits subjected to biaxial shaking using a number of centrifuge tests. Dense and loose sandy soil deposits were built in a 2D laminar container and subjected to a series of biaxial base excitations that approximate in somewhat realistic fashion the conditions of a site subjected to earthquake shaking. A dense array of accelerometers and pore pressure sensors was used to monitor the deposit response. The recorded accelerations and pore pressures were employed along with a non-parametric identification procedure to estimate the corresponding dynamic shear stress-strain histories. In turn, these histories were employed to assess the effects of non-proportional loading on soil contraction and dilation mechanisms. Pore water pressure buildup was found to be affected by load non-proportionality and a direct function of the phase angle of the induced shear stresses. The loose and dense soil deposits had contrasting as well as similar response patterns.

In his landmark paper, Keller (J Appl Phys 34:991–993, 1963) obtained an approximation for the effective conductivity of a composite medium made out of a densely packed square array of perfectly conducting circular cylinders embedded in a conducting medium. We here examine Keller’s problem for the case of square cylinders, considering both a full-pattern and a checkerboard configurations. The dense limit is handled using matched asymptotic expansions, where the conduction problem is separately analyzed in the the “local” narrow gap between adjacent cylinders and the “global” region outside the gap. The conduction problem in both regions is solved using conformal-mapping techniques.

Crevasses are inherent features of glaciers and Ice Sheets. They exert a primary control on glacier dynamics, such as, for example, along shear margins through reducing the overall glacier ice viscosity, or at glacier and Ice Sheet fronts through controlling the onset of serac falls and of ice sheet instabilities (calving, ice shelf disintegration). However, our understanding of crevasse formation and propagation, and in particular the effect of melt water, remains limited due to lacking observations. Here we provide novel observational insights into englacial fracturing, the depth of crevasses and their depth propagation rates using dense seismic array monitoring on an Alpine glacier. We systematically detect and locate englacial seismic events through applying matched-field-processing on a particularly dense seismic array of 98 sensors deployed on the Glacier d’Argentière during 1-month in spring 2018. We observe rupture fronts along crevasses, which propagate from the glacier center to the glacier side at typical velocities of few hundreds of meters per day, i.e. at velocities that are much lower than those of seismic waves but much higher than those of glacier flow. We argue based on a dedicated spatial and temporal analysis that crevasse rupture propagation is set by the migration of water along the crevasse tip. We also observe that crevasses are associated with a wide range of depths, varying from the near surface to the glacier base, which at the present site is located about a hundred meters below the surface. This observation is particularly interesting, since it provides evidences that (i) crevasses are water filled and (ii) crevasses play a role in the supply of water to the bed. These findings are further supported by the observation that surface melt modulates the seismic activity of crevasses including those reaching the bed. Finally, by evaluating coherent structures in the crevasse population, we are able to infer their depth propagation rate, which we find is constant through the ice column, as expected if the surrounding ice stress field is counterbalanced by the water pressure in the crevasse. These observationally-derived findings provide useful grounds to test and improve theories of crevasse dynamics and their control in the overall transfer of water from the surface to the bed.

© 2020, VLDB Endowment. All rights reserved. Recent advancements in learned index structures propose replacing existing index structures, like B-Trees, with approximate learned models. In this work, we present a unified benchmark that compares well-tuned implementations of three learned index structures against several state-of-the-art "traditional" baselines. Using four real-world datasets, we demonstrate that learned index structures can indeed outperform non-learned indexes in read-only in-memory workloads over a dense array. We investigate the impact of caching, pipelining, dataset size, and key size. We study the performance profile of learned index structures, and build an explanation for why learned models achieve such good performance. Finally, we investigate other important properties of learned index structures, such as their performance in multi-threaded systems and their build times.

In both 2D and 3D object detection algorithms, the reference boxes obtained by the anchor mechanism lay the foundation for the next detection tasks of the network. Most of the existing anchor mechanisms are designed by hand to generate a dense array of anchors. The size of the anchors obtained in this way is single and the anchors are densely distributed in the image space. It has poor robustness and a large number of redundant anchors. In views of these defects, we propose the 3D anchor generating network. It predicts the 3D anchors by learning the semantic features of the picture, in which the anchors are sparsely distributed around the objects in the image with different sizes in different positions of the image. We applied it to TLNet’s baseline monocular network for 3D object detection on KITTI dataset, the result showed a significant improvement on the performance of 3D object detection algorithms.

Current design codes require a dense array of steel reinforcement for shear-critical structural elements in earthquake-resistant structures, such as columns, walls, coupling beams, and beam-column joints. However, this leads to congested reinforcement in such elements during construction, which could cause extensively prolonged construction and reduced construction quality. This paper aims to investigate the potential of utilizing Ultra High Performance Concrete with hybrid fibers to reduce shear reinforcement in shear-critical structural elements. A series of beams reinforced with longitudinal steel bars and various combinations of hybrid fibers were tested in a four-point loading setup. Two different shear spans to depth ratio were used to evaluate the effect of the hybridization in the shear response of the member. The test results showed that the presence of hybrid fibers enhanced the shear cracking strength, ultimate shear strength, and crack width controlled ability of the specimens compared to the monofiber beams. The results also indicated that the hybrid specimen with a less volume fraction of fibers could delay the appearance of cracking in the member.

SUMMARYWe image the internal structure of the San Jacinto fault zone (SJFZ) near Anza, California, with seismic data recorded by two dense arrays (RA and RR) from ∼42 000 local and ∼180 teleseismic events occurring between 2012 and 2017. The RA linear array has short aperture (∼470 m long with 12 strong motion sensors) and recorded for the entire analysed time window, whereas the RR is a large three-component nodal array (97 geophones across a ∼2.4 km × 1.4 km area) that operated for about a month in September–October 2016. The SJFZ at the site contains three near-parallel surface traces F1, F2 and F3 from SW to NE that have accommodated several Mw > 6 earthquakes in the past 15 000 yr. Waveform changes in the fault normal direction indicate structural discontinuities that are consistent with the three fault surface traces. Relative slowness from local events and delay time analysis of teleseismic arrivals in the fault normal direction suggest a slower SW side than the NE with a core damage zone between F1 and F2. This core damage zone causes ∼0.05 s delay at stations RR26–31 in the teleseismic P arrivals compared with the SW-most station, and generates both P- and S-type fault zone trapped waves. Inversion of S trapped waves indicates the core damaged structure is ∼100 m wide, ∼4 km deep with a Q value of ∼20 and 40 per cent S-wave velocity reduction compared with bounding rocks. Fault zone head waves observed at stations SW of F3 indicate a local bimaterial interface that separates the locally faster NE block from the broad damage zone in the SW at shallow depth and merges with a deep interface that separates the regionally faster NE block from rocks to the SW with slower velocities at greater depth. The multiscale structural components observed at the site are related to the geological and earthquake rupture history at the site, and provide important information on the preferred NW propagation of earthquake ruptures on the San Jacinto fault.

Source mask and polarization optimization (SMPO) is a promising extension of the widely used resolution enhancement technology, source mask optimization (SMO), to further enhance chip manufacturability beyond 28-nm node. Our work is aimed to develop an efficient gradient-based SMPO method by employing the hybrid Hopkins–Abbe imaging model to fulfill the goal. In addition to source and mask variables, the model is adapted to also include polarization variables to realize the optimization. Compact formulas for forward and backward model application are derived. The computation benefits from precomputed transmission cross coefficients and features high efficiency. Validity of the method is confirmed by case studies. For dense array pattern case, the optimal source and polarization can be found analytically. SMPO optimized results match well with the theoretical expectations. In addition, process window, mask error enhancement factor, and normalized image log-slope for the studied cases all get improved over the counterpart SMO results, which employ commonly used polarization. Runtime analysis shows the method is computationally efficient. Our work provides a valid way to optimize polarization together with source and mask.

Volumetric transperineal imaging has the potential to improve motion management for external beam radiotherapy of the prostate. A fully wired, dense 2D array and a system to control such a probe is costly and not generally clinically available. Therefore, a bespoke sparse ellipsoidal array with 256 elements is proposed, allowing the use of standard ultrasound frontends for larger aperture. Based on simulated performance metrics, the array was selected from a population of potential configurations differing in element size, aperture size and ellipse eccentricity. Simulated B-Modes of the selected configuration were then compared to a dense array, which it outperformed in terms of FWHM and generalized Contrast-to-Noise ratio.

We fabricated a Ge 0.92 Sn 0.08 micro-disk laser with a lasing threshold as low as 20-30 kW/cm2 at 75 K. A specific etching process was developed to remove the dense array of misfit dislocations from the gain medium. Further surface treatments and passivations improved the lasing dynamics.

Karatungk Mine is the second-largest Cu-Ni sulfide mine in China. However, the detailed structure beneath the mine remains unclear. Using continuous waveforms recorded by a dense temporary seismic array, here we apply ambient noise tomography to study the shallow crustal structure of Karatungk Mine down to ~1.3 km depth. We obtain surface-wave dispersions at 0.1&ndash, 1.5 s by calculating cross-correlation functions, which are inverted for 3D shear-wave structure at the top-most (0&ndash, 1.3 km) crust by a joint inversion of group and phase dispersions. Our results show that low-velocity zones beneath Y1 ore-hosting intrusion (hereafter called Y1) at 0&ndash, 0.5 km depth and northwest of the Y2 ore-hosting intrusion (hereafter called Y2) at 0&ndash, 0.6 km depth are consistent with highly mineralized areas. A relatively high-velocity zone is connected with a weakly mineralized area located to the southeast of Y2 and Y3 (hereafter called Y3) ore-hosting intrusions. Two high-velocity zones, distributed at 0.7&ndash, 1.3 km depth in the northernmost and southernmost parts of the study area respectively, are interpreted to be igneous rocks related to early magma intrusion. Furthermore, the low-velocity zone at 0.7&ndash, 1.3 km depth in the middle of the study area may be related to: a possible channel related to initial magma transport, mine strata or a potentially mineralized area. This study demonstrates a new application of dense-array ambient noise tomography to a mining area that may guide future studies of mineralized regions.

In traditional surface wave tomography based on seismic noise, 2D phase or group velocity distribution is obtained by performing pure-path inversion after extracting interstation velocities based on the noise cross-correlation function. In this paper, we show that 2D surface wave phase velocity maps of adequate quality can be obtained directly, without interferometry, by beamforming the ambient noise recorded at array of stations. This method does not require a good azimuthal distribution of the noise sources. The 2D surface wave phase velocity map is obtained by moving the subarrays within a larger dense network of stations. The method is illustrated with seismic noise recorded by over 600 stations of the ChinArray (Phase II). We obtain 2D Rayleigh wave phase velocity maps between 7 and 35 s in Northeastern (NE) Tibetan Plateau and adjacent regions that compare well with results obtained with other methods. The shear wave velocity model is then derived by inverting the phase velocity with depth. The model correlates well with geology and tectonics in NE Tibet. Two clear mid-to-low crustal low-velocity zones are observed at 15- to 35-km depth beneath the Songpan-Ganzi terrane and Northwestern Qilian Orogen, possibly facilitating lower crustal flow in this key region for the tectonic evolution of NE Tibet.

Subglacial hydrology strongly modulates glacier basal sliding, and thus likely exerts a major control on ice loss and sea-level rise. However, the limited direct and spatialized observations of the subglacial drainage system make difficult to assess the physical processes involved in its development. Recent work shows that detectable seismic noise is generated by subglacial water flow, such that seismic noise analysis may be used to retrieve the physical properties of subglacial channelized water flow. Yet, investigating the spatial organisation of the drainage system (e.g. channels numbers and positions) together with its evolving properties (e.g. pressure conditions) through seismic observations remains to be done. The objective of this study is to bring new insights on the subglacial hydrology spatio-temporal dynamics using dense array seismic observations.We use 1-month long ground motion records at a hundred of sensors deployed on the Argentière Glacier (French Alps) during the onset of the melt season, when the subglacial drainage system is expected to strongly evolve in response to the rapidly increasing water input. We conduct a multi-method approach based on the analysis of both amplitude and phase maps of seismic signals. We observe characteristic spatial patterns, consistent across those independent approaches, which we attribute to the underlying subglacial drainage system.The phase-driven approach shows seismic noise sources that focuses in the along-flow direction as the water input increases. We identify this evolution as the development of the main subglacial channel whose position is coherent with the one expected from hydraulic potential calculations. During periods of rapid changes in water input (5 days over 31) and concomitant glacier acceleration the amplitude-driven approach shows spatial pattern highly consistent with the seismic noise sources location. At this time, we suggest that the spatial variations in the amplitude are representative of the water pressure conditions in subglacial channels and surrounding areas. Our spatialized observations therefore reveal the spatio-temporal evolution of the subglacial drainage system together with its changing pressure conditions. We observe, for instance, that channels develop at the very onset of the melt-season and rapidly capture the water from surrounding areas. Such unique observations may allow to better constrain the physics of subglacial water flow and therefore strengthen our knowledge on the dynamics of subglacial environments.

In this paper, we present two statistical methods to quantify the heterogeneity of the irradiance flux distribution, in a Concentrator Photovoltaic (CPV) dense-array, based on its operation and the optimization of current-matching. Preventing non-uniform flux distribution from design avoids the generation of hot spots, current mismatch and increases the overall efficiency of the system. This new approach considers the effects of the lowest irradiance values in the performance of the complete array, and its performance was corroborated by the simulations of a CPV array modelled in Matlab/Simulink; the irradiance distribution data as an input parameter was obtained from the images taken in a homogenization experiment, in the HoSIER, an 18,000 X solar furnace. The results are interpreted through the new concept of photovoltaic homogeneity, proven that the methodology successfully predicts the flux distributions, which enhances the efficiency of a series connected CPV array. Additionally, we found that the proposed methodology can also be used to optimize the electrical performance of dense-array CPV systems, working under the effects of non-uniformity illumination by rewiring the series connections into series-parallel configurations.

Organoids are three dimensional structures composed of multiple cell types that are capable of recapitulating tissue architecture and functions of organs in vivo. Formation of organoids has opened up different avenues of basic and translational research. In recent years, testicular organoids have garnered interest in the field of male reproductive biology. Testicular organoids allow for the study of cell-cell interactions, tissue development, and the germ cell niche microenvironment and facilitate high throughput drug and toxicity screening. A method is needed to reliably and reproducibly generate testicular organoids with testis specific tissue architecture. The microwell culture system contains a dense array of pyramid-shaped microwells. Testicular cells derived from pre-pubertal testes are centrifuged into these microwells and cultured to generate testicular organoids with testis-specific tissue architecture and cell associations. Thousands of homogeneous organoids can be generated via this process. The protocol reported here will be of broad interest to researchers studying male reproduction.

A smart, magnetically responsive superhydrophobic surface was facilely prepared by combining spray coating and magnetic-field-directed self-assembly. The surface comprised a dense array of magnetorheological elastomer micropillars (MREMPs). Benefitting from the magnetic field-stiffening effect of the MREMPs, the surface exhibited reversible switching of the wettability and adhesion that was responsive to an on/off magnetic field. The wettability and adhesion properties of the surfaces with MREMPs were investigated under different magnetic fields. The results revealed that the adhesion force and sliding behaviors of these surfaces were strongly dependent on the intensity of the applied magnetic field and the mixing ratio of poly(dimethylsiloxane) (PDMS), iron particles, and solvent (in solution) used for preparation of the magnetically responsive superhydrophobic surfaces. The adhesion transition was attributed to the tunable mechanical properties of the MREMPs, which was easily controlled by an external magnetic field. It was also demonstrated that the magnetically responsive superhydrophobic surface can be used as a "mechanical hand" for no-loss liquid droplet transportation. This magnetically responsive superhydrophobic surface not only provides a novel interface for microfluidic control and droplet transportation, but also opens up new avenues for achieving smart liquid-repellent skin, programmable fluid collection and transport, and smart microfluidic devices.

International audience; The stochastic estimation of coherency is perceived, in some studies, to be significantly influenced by the time window length under consideration. For the engineering purposes, usually, coherency is estimated from the strong motion, i.e., the shear (S-) wave segment of the recorded time series. However, the identification of a purely S-wave dominated window could be challenging in case of complex wave mixing on the seismograms. Moreover, there has been relatively little research on how much variation, in reality, is introduced in the coherency estimates owing to the choice of signal length. Therefore, the debate about the procedure for selecting a representative time window has remained inconclusive: different authors keep their different practices. The current article is an effort to shed light on the sensitivity of the coherency estimates to the choice of various time windows. The research draws on the dataset gathered from a dense seismic-array deployed at the small size, shallow alluvial valley of Koutavos-Argostoli, situated in Cephalonia Island, Greece. The lagged coherency over interstation distance ranges from 5 to 80 m has been estimated from a set of 46 earthquakes having magnitude 2–5 and epicentral distance 3–200 km, considering different lengths of time windows. The findings revealed that the statistics of coherency estimates derived from many events is only weakly sensitive to the selection of time window lengths provided that the segments include the same energetic pulse.