Miracle-dz/UniFAR-FTUs huggingface dataset:
Growth defects in GaN films on sapphire: The probable origin of threading dislocations

Single crystal GaN films with a wurtzite structure were grown on the basal plane of sapphire. A high density of threading dislocations parallel to the c -axis crossed the film from the interface to the film surface. They were found to have a predominantly edge character with a $${\textstyle{1 \over 3}}\langle 11\overline 2 0\rangle $$ Burgers vector. In addition, dislocation hal-loops, elongated along the c -axis of GaN, were also found on the prism planes. These dislocations had a mostly screw character with a [0001] Burgers vector. Substrate surface steps with a height of $${\textstyle{1 \over 6}}{c_{{\rm{A}}{{\rm{|}}_2}{{\rm{O}}_3}}}$$ were found to be accommodated by localized elastic bending of GaN (0001)_GaN planes in the vicinity of the film/substrate interface. Observations show that the region of the film, with a thickness of ∼100 nm, adjacent to the interface is highly defective. This region is thought to correspond to the low-temperature GaN “buffer” layer which is initially grown on the sapphire substrate. Based on the experimental observations, a model for the formation of the majority threading dislocations in the film is proposed. The analysis of the results leads us to conclude that the film is under residual biaxial compression.
Arabidopsis SH3P2 is an ubiquitin-binding protein that functions together with ESCRT-I and the deubiquitylating enzyme AMSH3

Significance The endosomal sorting of integral proteins is essential for controlling signaling pathways at the plasma membrane. Posttranslational modification by ubiquitin is key to proper degradation of plasma membrane proteins as the ubiquitylated transmembrane proteins are recognized by multiple ubiquitin adaptor proteins and trafficked to the vacuole for degradation. Although plants lack orthologs of the yeast and metazoan endosomal sorting complex required for transport-0 heterodimer that functions as an ubiquitin adaptor, plants appear to have evolved other strategies to recognize and concentrate ubiquitylated proteins that have been endocytosed. Here, we report the SH3P2 protein as a yet-unknown ubiquitin adaptor protein in Arabidopsis and its molecular function in regulating the endocytic transport and degradation. Clathrin-mediated endocytosis of plasma membrane proteins is an essential regulatory process that controls plasma membrane protein abundance and is therefore important for many signaling pathways, such as hormone signaling and biotic and abiotic stress responses. On endosomal sorting, plasma membrane proteins maybe recycled or targeted for vacuolar degradation, which is dependent on ubiquitin modification of the cargos and is driven by the endosomal sorting complexes required for transport (ESCRTs). Components of the ESCRT machinery are highly conserved among eukaryotes, but homologs of ESCRT-0 that are responsible for recognition and concentration of ubiquitylated proteins are absent in plants. Recently several ubiquitin-binding proteins have been identified that serve in place of ESCRT-0; however, their function in ubiquitin recognition and endosomal trafficking is not well understood yet. In this study, we identified Src homology-3 (SH3) domain-containing protein 2 (SH3P2) as a ubiquitin- and ESCRT-I–binding protein that functions in intracellular trafficking. SH3P2 colocalized with clathrin light chain-labeled punctate structures and interacted with clathrin heavy chain in planta, indicating a role for SH3P2 in clathrin-mediated endocytosis. Furthermore, SH3P2 cofractionates with clathrin-coated vesicles (CCVs), suggesting that it associates with CCVs in planta. Mutants of SH3P2 and VPS23 genetically interact, suggesting that they could function in the same pathway. Based on these results, we suggest a role of SH3P2 as an ubiquitin-binding protein that binds and transfers ubiquitylated proteins to the ESCRT machinery.
Fidelity-Weighted Learning

Training deep neural networks requires many training samples, but in practice training labels are expensive to obtain and may be of varying quality, as some may be from trusted expert labelers while others might be from heuristics or other sources of weak supervision such as crowd-sourcing. This creates a fundamental quality versus-quantity trade-off in the learning process. Do we learn from the small amount of high-quality data or the potentially large amount of weakly-labeled data? We argue that if the learner could somehow know and take the label-quality into account when learning the data representation, we could get the best of both worlds. To this end, we propose "fidelity-weighted learning" (FWL), a semi-supervised student-teacher approach for training deep neural networks using weakly-labeled data. FWL modulates the parameter updates to a student network (trained on the task we care about) on a per-sample basis according to the posterior confidence of its label-quality estimated by a teacher (who has access to the high-quality labels). Both student and teacher are learned from the data. We evaluate FWL on two tasks in information retrieval and natural language processing where we outperform state-of-the-art alternative semi-supervised methods, indicating that our approach makes better use of strong and weak labels, and leads to better task-dependent data representations.
Acoustic wood tomography on trees and the challenge of wood heterogeneity

Abstract The assessment of tree stability requires information about the location and the geometry of fungal decay or of a cavity in the interior of the trunk. This work aims at specifying which size of decay or cavity can be detected non-destructively by acoustic wood tomography. In the present work, the elastic waves that propagate in a trunk during a tomographic measurement were visualized by numerical simulations. The numerical model enabled to systematically investigate the influence of fungal decay on tomographic measurements neglecting the heterogeneity of wood. The influence of wood heterogeneity was studied in laboratory experiments on trunks. The experiments indicated that the waveforms of the measured signals are by far more sensitive to the natural heterogeneity of trunk wood than the travel times, thereby making waveforms unsuitable for decay detection. Thus, it is recommended to further develop the travel time inversion algorithms for trunks and to neglect the information in waveforms or amplitudes. Fungal decay is detectable if the influence of the decay is distinguishable from the influence of the heterogeneity. It was found from the numerical analysis that the cross-section of a cavity, which is larger than 5% of the total cross-section of the trunk, can be detected by acoustic wood tomography.
Sex differences in cerebral responses to images of high versus low-calorie food

Men and women differ in cerebral organization and prevalence rates of eating disorders. However, no studies have yet examined sex differences in cerebral responses to the caloric content of food images. Sixteen healthy adults (eight men; eight women) underwent functional magnetic resonance imaging while viewing images of high-calorie and low-calorie foods. Compared with men, women showed significantly greater activation to calorie-rich foods within dorsolateral, ventrolateral, and ventromedial prefrontal cortex, middle/posterior cingulate, and insula. Men failed to show greater activation in any cortical region compared with women, although amygdala responses were greater in men at a more liberal threshold. When viewing high-calorie food images, women seem more responsive than men within cortical regions involved in behavioral control and self-referential cognition.
Control of time varying nonlinear system of supporting robot based on neural network

This paper takes mining hydraulic supporting robot as the research object. On the basis of analyzing the dynamic model of the supporting robot and transfer functions of the hydraulic system, system construction and simulation are realized in Simulink. Due to the existence of time-varying parameters in the system, common negative feedback controls are not effective and stable. Therefore, a neural network adaptive PID controller is proposed in this paper, and results are analyzed and compared with traditional PID control. Results show that the neural network adaptive PID controller has fast response speed and very small overshoot. The remarkable feature is that the system shows an excellent adaptive ability to quickly return to the control position after interference impacts, which fully demonstrates the effectiveness of the neural network adaptive PID controller for hydraulic supporting robot time-varying system.
Alternative Oxidase Isoforms Are Differentially Activated by Tricarboxylic Acid Cycle Intermediates1[OPEN]

In Arabidopsis, alternative oxidase activation is isoform specific, with AOX1A activated by oxaloacetate and 2-oxoglutarate, AOX1D solely by 2-oxoglutarate, and AOX1C insensitive to both. The cyanide-insensitive alternative oxidase (AOX) is a non-proton-pumping ubiquinol oxidase that catalyzes the reduction of oxygen to water and is posttranslationally regulated by redox mechanisms and 2-oxo acids. Arabidopsis (Arabidopsis thaliana) possesses five AOX isoforms (AOX1A–AOX1D and AOX2). AOX1D expression is increased in aox1a knockout mutants from Arabidopsis (especially after restriction of the cytochrome c pathway) but cannot compensate for the lack of AOX1A, suggesting a difference in the regulation of these isoforms. Therefore, we analyzed the different AOX isoenzymes with the aim to identify differences in their posttranslational regulation. Seven tricarboxylic acid cycle intermediates (citrate, isocitrate, 2-oxoglutarate, succinate, fumarate, malate, and oxaloacetate) were tested for their influence on AOX1A, AOX1C, and AOX1D wild-type protein activity using a refined in vitro system. AOX1C is insensitive to all seven organic acids, AOX1A and AOX1D are both activated by 2-oxoglutarate, but only AOX1A is additionally activated by oxaloacetate. Furthermore, AOX isoforms cannot be transformed to mimic one another by substituting the variable cysteine residues at position III in the protein. In summary, we show that AOX isoforms from Arabidopsis are differentially fine-regulated by tricarboxylic acid cycle metabolites (most likely depending on the amino-terminal region around the highly conserved cysteine residues known to be involved in regulation by the 2-oxo acids pyruvate and glyoxylate) and propose that this is the main reason why they cannot functionally compensate for each other.
New Modulated Carrier Controlled PFC Boost Converter

A new modulated carrier control (MCC) method is proposed in this paper for a power factor correction (PFC) boost converter, which provides high power factor (PF) and low total harmonic distortion (THD) in wide input voltage and load range. The proposed MCC method employs a zero current duration (ZCD) demodulator that detects ZCD in each switching cycle to estimate current conduction duration of the boost inductor. Using the estimated signal of the ZCD demodulator, the proposed controller generates a compensated duty signal with a PFC converter to properly operate in continuous conduction mode (CCM) or discontinuous conduction mode (DCM). Unlike the conventional MCC PFC converter where the line current is distorted in DCM resulting in poor PF and high THD, the proposed MCC method can provide higher PFC performance regardless of CCM and DCM while maintaining the simple control loop of conventional MCC control method that does not require inner current loop and using relatively small inductance. In this paper, the operational principle of the proposed method has been discussed. To verify the proposed method, it has been tested on a 400-W PFC boost converter.
Allegro: User-centered Design of a Tool for the Crowdsourced Transcription of Handwritten Music Scores

In this paper, we describe the challenge of transcribing a large corpus of handwritten music scores. We conducted an evaluation study of three existing optical music recognition (OMR) tools. The evaluation results indicate that OMR approaches do not work well for our corpus of highly heterogeneous, handwritten music scores. For this reason, we designed Allegro, a web-based crowdsourcing tool that can be used to transcribe scores. We relied on a user-centered design process throughout the development cycle of the application, to ensure a high level of usability. The interface was designed in a way it can be used intuitively, even by novices of musical notation. We describe the core features of Allegro and the basic transcription workflow. A first public beta test with 18 users shows that a crowdsourced transcription approach via the Allegro tool is a viable option for the encoding of our corpus of folk songs.
dvances in diagnosis of protozoan diseases

Microscopy still remains the gold standard procedure for the diagnosis of many protozoan infections in animals, but the specific identification requires skilled and experienced personnel. Immunoassays, detecting antibodies or specific protozoan antigens, have been developed but often lack sensitivity and specificity due to close relationship between many CR erology protozoa. Recent research has focussed almost exclusively on molecular based techniques for the identification and quantification of parasite DNA in samples. Opinion differ on most appropriate targets to use and there are very few diagnostic kits available making comparison between laboratories difficult. Future research needs to focus on robust, cheap field
M2 macrophages induce ovarian cancer cell proliferation via a heparin binding epidermal growth factor/matrix metalloproteinase 9 intercellular feedback loop

In ovarian cancer, a high ratio of anti-inflammatory M2 to pro-inflammatory M1 macrophages correlates with poor patient prognosis. The mechanisms driving poor tumor outcome as a result of the presence of M2 macrophages in the tumor microenvironment remain unclear and are challenging to study with current techniques. Therefore, in this study we utilized a micro-culture device previously developed by our lab to model concentrated paracrine signaling in order to address our hypothesis that interactions between M2 macrophages and ovarian cancer cells induce tumor cell proliferation. Using the micro-culture device, we determined that co-culture with M2-differentiated primary macrophages or THP-1 increased OVCA433 proliferation by 10–12%. This effect was eliminated with epidermal growth factor receptor (EGFR) or heparin-bound epidermal growth factor (HB-EGF) neutralizing antibodies and HBEGF expression in peripheral blood mononuclear cells from ovarian cancer patients was 9-fold higher than healthy individuals, suggesting a role for HB-EGF in tumor progression. However, addition of HB-EGF at levels secreted by macrophages or macrophage-conditioned media did not induce proliferation to the same extent, indicating a role for other factors in this process. Matrix metalloproteinase-9, MMP-9, which cleaves membrane-bound HB-EGF, was elevated in co-culture and its inhibition decreased proliferation. Utilizing inhibitors and siRNA against MMP9 in each population, we determined that macrophage-secreted MMP-9 released HB-EGF from macrophages, which increased MMP9 in OVCA433, resulting in a positive feedback loop to drive HB-EGF release and increase proliferation in co-culture. Identification of multi-cellular interactions such as this may provide insight into how to most effectively control ovarian cancer progression.
TMS SMART – Scalp mapping of annoyance ratings and twitches caused by Transcranial Magnetic Stimulation

The magnetic pulse generated during Transcranial magnetic stimulation [TMS] also stimulates cutaneous nerves and muscle fibres, with the most commonly reported side effect being muscle twitches and sometimes painful sensations. These sensations affect behaviour during experimental tasks, presenting a potential confound for ‘online’ single-pulse TMS studies. Our objective was to systematically map the degree of disturbance (ratings of annoyance, pain, and muscle twitches) caused by TMS at 43 locations across the scalp. Ten participants provided ratings whilst completing a choice reaction time task, and ten participants provided ratings whilst completing a ‘flanker’ reaction time task. TMS over frontal and inferior regions resulted in the highest ratings of annoyance, pain, and muscle twitches caused by TMS. In separate analyses we predicted the difference in reaction times (RT) under TMS by scalp location and subjective ratings. Frontal and inferior scalp locations showed the greatest cost to RTs under TMS (i.e., slowing), with midline sites showing no or minimal slowing. Increases in subjective ratings of disturbance predicted longer RTs under TMS. Critically, ratings were a better predictor of the cost of TMS than scalp location or scalp-to-cortex distance, and the more difficult ‘flanker’ task showed a greater effect of subjective disturbance. The peripheral sensations and discomfort caused by TMS pulses significantly and systematically influence RTs during single-pulse, online TMS experiments. We provide the data as an online resource (http://www.tms-smart.info) so that researchers can select control sites that account for the level of general interference in task performance caused by online single-pulse TMS.
Real-time computational photon-counting LiDAR

Abstract. The availability of compact, low-cost, and high-speed MEMS-based spatial light modulators has generated widespread interest in alternative sampling strategies for imaging systems utilizing single-pixel detectors. The development of compressed sensing schemes for real-time computational imaging may have promising commercial applications for high-performance detectors, where the availability of focal plane arrays is expensive or otherwise limited. We discuss the research and development of a prototype light detection and ranging (LiDAR) system via direct time of flight, which utilizes a single high-sensitivity photon-counting detector and fast-timing electronics to recover millimeter accuracy three-dimensional images in real time. The development of low-cost real time computational LiDAR systems could have importance for applications in security, defense, and autonomous vehicles.
Patch-based fully convolutional neural network with skip connections for retinal blood vessel segmentation

Automated segmentation of retinal blood vessels plays an important role in the computer aided diagnosis of retinal diseases. The paper presents a new formulation of patch-based fully Convolutional Neural Networks (CNNs) that allows accurate segmentation of the retinal blood vessels. A major modification in this retinal blood vessel segmentation task is to improve and speed-up the patch-based fully CNN training by local entropy sampling and a skip CNN architecture with class-balancing loss. The proposed method is experimented on DRIVE dataset and achieves strong performance and significantly outperforms the-state-of-the-art for retinal blood vessel segmentation with 78.11% sensitivity, 98.39% specificity, 95.60% accuracy, 87.36% precision and 97.92% AUC score respectively.
Towards Information-Centric Networking (ICN) Naming for Internet of Things (IoT): The Case of Smart Campus

Information-Centric Networking (ICN) specifically Name Data Networking (NDN) is the name-base (content-base) networking and takes named-contents as "first class citizen", being considered as the ideal candidate to form the Future Internet basis. NDN striking features like named-data self-secured contents, name-base-forwarding, in-network caching and mobility support suits the Internet of Things (IoT) environment, which aims to enable communication among smart devices and to combine all Internet-based smart applications under the one roof. With these aims, IoT put many research challenges regarding its network architecture as it should support heterogeneous devices and offer scalability. IoT may depend on the names and addresses of billions of the devices and should smartly manage the bulk of data produced every second. IoT application smart campus has gained a lot of attention in both industry and academia due to many reasons. Therefore, to design NDN for IoT, a sophisticated naming scheme is needed to explore and it is the main motivation for this work. In this paper, we study NDN-IoT smart campus (in terms of connected devices and contents) and find that it lacks in a reasonable naming and addressing mechanism; and thus we propose NDN based Hybrid Naming Scheme (NDN-HNS) for IoT based Smart Campus (IoTSC).
Game-theoretic quorum-based frequency hopping for anti-jamming rendezvous in DSA networks

Establishing communications in a dynamic spectrum access (DSA) network requires the communicating parties to “rendezvous” before transmitting their data packets. Frequency hopping (FH) is an effective rendezvous method that does not rely on a predetermined control channel. Recently, “quorum-based” FH approaches have been proposed for asynchronous rendezvous in DSA networks. These approaches are highly vulnerable to jamming, especially when the attacker is an insider node (i.e., a compromised node). In this paper, we investigate the problem of two secondary users (SUs), a transmitter and a receiver, try to rendezvous in the presence of a third SU acting as a jammer. The jammer is aware of the underlying (quorum-based) rendezvous design. First, we consider the case when all SUs are time-synchronized and are aware of the “rendezvous channel. ” We formulate the problem as a three-player game between the transmitter, receiver, and jammer. The transmitter and receiver try to maximize the number of successful rendezvous slots, while minimizing the number of jammed rendezvous slots. The jammer has the opposite objective. We show that this game does not have a pure Nash equilibrium (NE). Accordingly, we formulate a simplified two-player game between the receiver and jammer (assuming a uniform strategy by the transmitter), and derive multiple pure NE strategies. Next, we study the case when the rendezvous channel is unknown and obtain the Bayesian NE. Finally, the asynchronous case is addressed by exploiting the “rotation closure property” of quorum systems. Our numerical experiments show that uncertainty about the transmitter's strategy improves the anti-jamming rendezvous performance. They also show that the rendezvous performance improves if the receiver and jammer are time-synchronized, and also improves if the receiver and jammer have a common guess about the transmitter's strategy.
Real-Time and In-Flow Sensing Using a High Sensitivity Porous Silicon Microcavity-Based Sensor

Porous silicon seems to be an appropriate material platform for the development of high-sensitivity and low-cost optical sensors, as their porous nature increases the interaction with the target substances, and their fabrication process is very simple and inexpensive. In this paper, we present the experimental development of a porous silicon microcavity sensor and its use for real-time in-flow sensing application. A high-sensitivity configuration was designed and then fabricated, by electrochemically etching a silicon wafer. Refractive index sensing experiments were realized by flowing several dilutions with decreasing refractive indices, and measuring the spectral shift in real-time. The porous silicon microcavity sensor showed a very linear response over a wide refractive index range, with a sensitivity around 1000 nm/refractive index unit (RIU), which allowed us to directly detect refractive index variations in the 10−7 RIU range.