Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Reconstruction of 1D Compressive Sensing Data Using a Deep Neural Network

—A deep neural network is used to recognize the nonzero positions of a one-dimensional signal in its sparse domain. Unlike classical data reconstruction methods in Compressive Sensing (CS), such as basis pursuit or recast as a linear programming problem and solved with Primal-Dual Interior Point Method (PDIPM), the proposed data reconstruction method is inspired by the performance of Convolutional Neural Networks (CNNs) on image edge detection. A CNN is expected to find the nonzero positions of a sequence in the sparse domain. The proposed method trains the CNN with deep residual learning [1] and takes the Half-Mean-Squared-Error (HMSE) as the loss function. It is difficult with a CNN to get accurate amplitude of nonzero points directly, but the CNN finds the nonzero positions efficiently. When the nonzero positions are found, Lower– Upper (LU) matrix factorization with partial pivoting can be used to acquire accurate CS reconstruction. The experiments show that the proposed method operates with higher speed and reconstruction accuracy than competing methods.
Data-Driven Structured Noise Filtering via Common Dynamics Estimation

Classical signal from noise separation problems assume that the signal is a trajectory of a low-complexity linear time-invariant system and that the noise is a random process. In this paper, we generalize this classical setup to what we call data-driven structured noise filtering. In the new setup, the noise has two components: structured noise, which is also a trajectory of a low-complexity linear time-invariant system, and unstructured noise, which is a zero-mean white Gaussian process. The key assumption that makes the separation problem in the new setup well posed is that among several experiments, the signal's dynamics remains the same while the structured noise's dynamics varies. The data-driven structured noise filtering problem then becomes a problem of estimation of common linear time-invariant dynamics among several observed signals. We show that this latter problem is a structured low-rank approximation problem with multiple rank constraints and use a subspace identification approach for solving it. The resulting methods allow computationally efficient and numerically robust implementation and have the system theoretic interpretation of finding the intersection of autonomous linear time-invariant behaviors. Statistical analysis providing confidence bounds is a topic for future research.
Serum protein changes associated with ulcerative dermal necrosis (UDN) in the trout Salmo trutta L.

The total protein level is reduced and the electrophoretic pattern of the serum is changed in trout Salmo trutta L. infected with UDN, as in the Atlantic salmon. However, the changes in the trout are not as characteristic as those in salmon and thus are of very limited use in diagnosis of outbreaks of this disease among trout.
Biochemical systematics of the Australian cockatoos (Psittaciformes : Cacatuinae)

The genetic and evolutionary relationships of the Australian cockatoos (excluding Probosciger) and of the cockatiel, Nymphicus hollandicus, were examined by the technique of isozyme electrophoresis. A cladistic analysis of data from 28 loci showed that Nymphicus is more closely related to cockatoos than to any ofthe non-cockatoos; accordingly Nymphicus should be included within the Cacatuinae, but in a monotypic tribe. The other genera form two well defined groupings. One comprises all of the white cockatoos (Cacatua) and the gang gang Callocephalon fimbriatum, and the other, the black cockatoos (Calyptorhynchus). Within the white cacatuine cockatoos there seem to be at least two minor groups. One, clearly indicated by the electrophoretic data, comprises the galah Cacatua roseicapilla and Australo-Papuan corellas, all of which have short plain crests and usually coloured periophthalmic skin. The other, neither denied nor confirmed biochemically, is a looser assemblage characterized by coloured up-curving crests and plain periophthalmic skin; it included the sulphur-crested cockatoo Cacatua galerita and the pink cockatoo Cacatua leadbeateri, and their allospecies on islands north of Australia. Isozyme electrophoresis of the loci examined in this study could not differentiate members of the Calyptorhynchus funereus superspecies, nor of the Cacatua tenuirostris-pastinator group of corellas. The results are therefore in accord with other studies that show that isozyme electrophoresis has limited application in elucidating species boundaries in birds.
Bacterial Endotoxins and Their Role in Periparturient Diseases of Dairy Cows: Mucosal Vaccine Perspectives

During the periparturient period there is a significant increase in the incidence of multiple metabolic and infectious diseases in dairy cows. Dairy cows are fed high-grain diets immediately after calving to support production of large amounts of milk. Mounting evidence indicates these types of diets are associated with the release of high amounts of endotoxins in the rumen fluid. If infected, the udder and uterus additionally become important sources of endotoxins during the postpartum period. There is increasing evidence that endotoxins translocate from rumen, uterus, or udder into the systemic circulation and trigger chronic low-grade inflammatory conditions associated with multiple diseases including fatty liver, mastitis, retained placenta, metritis, laminitis, displaced abomasum, milk fever, and downer cow syndrome. Interestingly, endotoxin-related diseases are triggered by a bacterial component and not by a specific bacterium. This makes prevention of these type of diseases different from classical infectious diseases. Prevention of translocation of endotoxins into the host systemic circulation needs to take priority and this could be achieved with a new approach: mucosal vaccination. In this review article, we discuss all the aforementioned issues in detail and also report some of our trials with regards to mucosal vaccination of periparturient dairy cows.
Selection of a Similarity Measure Combination for a Wide Range of Multimodal Image Registration Cases

—Many similarity measures (SMs) were proposed to measure the similarity between multimodal remote sensing (RS) images. Each SM is efﬁcient to a different degree in different registration cases (we consider visible-to-infrared, visible-to-radar, visible-to-digital elevation model (DEM), and radar-to-DEM ones), but no SM was shown to outperform all other SMs in all cases. In this article, we investigate the possibility of deriving a more powerful SM by combining two or more existing SMs. This combined SM relies on a binary linear support vector machine (SVM) classiﬁer trained using real RS images. In the general registration case, we order SMs according to their impact on the combined SM performance. The three most important SMs include two structural SMs based on modality independent neighborhood descriptor (MIND) and scale-invariant feature transform-octave (SIFT-OCT) descriptors and one area-based logarithmic likelihood ratio (logLR) SM: the former ones are more robust to structural changes of image intensity between registered modes, the latter one is to image noise. Importantly, we demonstrate that a single combined SM can be applied in the general case as well as in each particular considered registration case. As compared to existing multimodal SMs, the proposed combined SM [based on ﬁve existing SMs, namely, MIND, logLR, SIFT-OCT, phase correlation (PC), histogram of orientated phase congruency (HOPC)] increases the area under the curve (AUC) by from 1% to 21%. From a practical point of view, we demonstrate that complex multimodal image pairs can be successfully registered with the proposed combined SM, while existing single SMs fail to detect enough correspondences for registration. Our results demonstrate that MIND, SIFT, and logLR SMs capture essential aspects of the similarity between RS modes, and their properties are complementary for
Profiling lipid changes in plant response to low temperatures

Changes in membrane lipid composition play multiple roles in plant adaptation and survival in the face of chilling and freezing damage. An electrospray ionization tandem mass spectrometry (ESI-MS/MS)-based approach has been used to quantitatively profile membrane lipid molecular species in plant response to low temperatures. This method involves the direct infusion of unfractionated lipid extracts into a mass spectrometer in the precursor and neutral loss scanning modes to identify and quantify lipid species. The profiling analysis reveals significant and distinct lipid changes during cold acclimation and freezing. Comparative profiling of wildtype and mutants provides information about the metabolic and cellular functions of specific phospholipase D genes and enzymes.
Fraud Frevention for Sustainable Social Enterprise Using Participative Social Governance

Social enterprise is not immune from fraud. As social enterprise is growing, there are some risks of fraud occurrance. Therefore, the purpose of this paper are to discuss types of frauds risks in Indonesian social enterprise and the effective ways to prevent it. This study used case study in one of social enterprise in Indonesia, that is at Panggungharjo, Indonesia. Panggungharjo has Village-owned Enterprise that manage waste management as its social business. The finding of this study indicates that there are three types of fraud occurred in Indonesian social enterprise. These types of fraud could be prevented by engaging community in decision making and monitoring process which are known as participative social governance. This study argue that participative social governence is more effective in fraud prevention rather than external audit and monitoring. The study will be useful for scholars, policy makers and regulators who are interested in Indonesian social enterprise.
Formative assessment with understanding by design to improve students’habits of mind

The high competition in the globalization era makes students often faced with various complicated problems. Therefore, teaching process that facilitate students to have smart thingking habits and strong understanding is needed. One way to train and develop students’ habits of mind is through the implementation of formative assessments. This study aims to know the effect of formative assessment with understanding by design (UbD) in improving students’ habits of mind and understanding. The method used is quantitative method with one-group pre-test post-test design. The result of the research shows that there is a significant increase both in student’s habits of mind and student’s understanding. The student’s habits of mind increases by 43,9%, while students’ understanding increases by 45%.
Bacteriological spectrum of urinary, wound and respiratory infection with antibiogram of gram negative bacteria in a Bangladeshi tertiary care hospital

Infection remains the main cause of morbidity and mortality in man, particularly in developing areas where it is associated with poverty and overcrowding. Infectious disease cause nearly 25% of all human deaths. This rate of mortality is increasing day by day due to antibiotic resistance, which is a major concern nowadays. Wound, respiratory tract and urinary tract are commonly associated with bacterial infection in both hospital and community settings. Area-specific monitoring studies aimed to gain knowledge about the type of bacterial pathogens responsible for these kinds of infections and resistance pattern of the causative agents may help clinicians to choose correct treatment regimen. So, the present study was aimed to investigate the pattern of bacteria which are responsible for Urinary tract, respiratory tract and wound infection. In addition, we also determined the antibiotic susceptibility profile of gram negative bacteria isolated from the patients who were attending both in and out patient departments at Sir Salimullah Medical College & Mitford Hospital (SSMC & MH) during January, 2009 to December, 2009. In this cross-sectional study, out of 308 clinical samples, a total of 159 (51.62%) samples were found to be positive for bacterial culture. Among the isolates 139 (87.42%) were Gram negative bacteria (Esch. coli, Klebsiella spp., Proteus spp., Pseudomonas spp., Acinetobacter spp.) and 20 (12.57%) were Gram positive bacteria (Staphylococcus aureus, Coagulase negative Staphylococcus). Antibiotic susceptibility of gram negative bacteria showed members of the Enterobacteriaceae were 100% sensitive to imipenem while they were found variably resistance to other commonly used antibiotics. We conclude that infections in the wound, respiratory and urinary tract are caused by both gram negative and gram positive bacteria. However, the frequency of gram negative bacteria is higher than the gram positive bacteria for these infections. Gram negative bacteria showed sensitive to imipenem and most of them were resistant to commonly used antibiotics. Therefore, clinicians should choose imipenem for patients who would be unresponsive to commonly used antibiotics.
Spatio-Temporal Meta Learning for Urban Traffic Prediction

Predicting urban traffic is of great importance to intelligent transportation systems and public safety, yet is very challenging in three aspects: 1) complex spatio-temporal correlations of urban traffic, including spatial correlations between locations along with temporal correlations among timestamps; 2) spatial diversity of such spatio-temporal correlations, which varies from location to location and depends on the surrounding geographical information, e.g., points of interests and road networks; and 3) temporal diversity of such spatio-temporal correlations, which is highly influenced by dynamic traffic states. To tackle these challenges, we proposed a deep meta learning based model, entitled ST-MetaNet<inline-formula><tex-math notation="LaTeX">$^+$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mo>+</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="pan-ieq1-2995855.gif"/></alternatives></inline-formula>, to <italic>collectively</italic> predict traffic in all locations at the same time. ST-MetaNet<inline-formula><tex-math notation="LaTeX">$^+$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mo>+</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="pan-ieq2-2995855.gif"/></alternatives></inline-formula> employs a sequence-to-sequence architecture, consisting of an encoder to learn historical information and a decoder to make predictions step by step. Specifically, the encoder and decoder have the same network structure, consisting of meta graph attention networks and meta recurrent neural networks, to capture diverse spatial and temporal correlations, respectively. Furthermore, the weights (parameters) of meta graph attention networks and meta recurrent neural networks are generated from the embeddings of geo-graph attributes and the traffic context learned from dynamic traffic states. Extensive experiments were conducted based on three real-world datasets to illustrate the effectiveness of ST-MetaNet<inline-formula><tex-math notation="LaTeX">$^+$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mo>+</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="pan-ieq3-2995855.gif"/></alternatives></inline-formula> beyond several state-of-the-art methods.
Viral activity in relation to Emiliania huxleyi blooms: a mechanism of DMSP release?

The role of viral activity with respect to bloom dynamics and production of dissolved dimethylsulfoniopropionate (DMSP) and dimethylsulfide (DMS) was investigated in Norwegian coastal waters and in sea water mesocosms during blooms of the coccolithophorid Emiliania huxleyi (Lohm.) Hay & Mohler. In coastal waters the collapse of the E. huxleyi bloom was accompanied by a simultaneous increase in large virus-like particles (LVLP) and there was a significant inverse relationship between cell-specific calcification rate and LVLP abundance. Results from the mesocosm study indicate that the viral actlv~ty may either prevent or termlnate the development of E. huxleyi blooms. No significant relationships were found between the abundance of LVLPs and the concentrations of dissolved DMSP and DMS in the field or in the mesocosms. This may be explained by the relatively small size of the E. huxlep blooms (maximum cell concentration of 11 X 106 I-') and bacterial degradation of DMSP and DMS, which may have been sufficient to prevent the accumulation of sulfur compounds released after lysis of the cells.
Performance Prospects of Deeply Scaled Spin-Transfer Torque Magnetic Random-Access Memory for In-Memory Computing

In recent years, Spin-Transfer-Torque Magnetic Random Access Memory (STT-MRAM) has been considered as one of the most promising non-volatile memory candidates for in-memory computing. However, system-level performance gains using STT-MRAM for in-memory computing at deeply scaled nodes have not been assessed with respect to more mature memory technologies. In this letter, we present perpendicular magnetic tunnel junction (pMTJ) STT-MRAM devices at 28nm and 7nm. We evaluate the system-level performance of convolutional neural network (CNN) inference with STT-MRAM arrays in comparison to Static Random Access Memory (SRAM). We benchmark STT-MRAM and SRAM in terms of area, leakage power, energy, and latency from 65nm to 7nm technology nodes. Our results show that STT-MRAM keeps providing <inline-formula> <tex-math notation="LaTeX">$\sim 5\times $ </tex-math></inline-formula> smaller synaptic core area, <inline-formula> <tex-math notation="LaTeX">$\sim 20\times $ </tex-math></inline-formula> less leakage power, and <inline-formula> <tex-math notation="LaTeX">$\sim 7\times $ </tex-math></inline-formula> less energy than SRAM when both devices are scaled from 65nm to 7nm. With the emerging need for low power computation for a broad range of applications such as internet-of-things (IoT) and neural network (NN), STT-MRAM can offer energy-efficient and high-density in-memory computing.
Factors affecting resource use variation for an abundant coastal fish predator, Lutjanus apodus, in a bahamian wetland system

Studies of fishes' resource use reflect important ecological interactions, and provide insight into the structure of aquatic food webs. Individuals within species are often assumed to have an equivalent ecological role despite increasing evidence that among-individual variation in resource use within populations is common. Such intraspecific variation in resource use can be a result of ontogenetic-based diet shifts, differences in individual feeding behavior within age groups (i.e., individual specialization), and temporal variation in resource pools. We examined trophic interactions in schoolmaster, Lutjanus apodus (Walbaum, 1972), over multiple seasons and across size classes in a Bahamian wetland system. Using combined stable isotope and stomach content analyses, we found that, as with many other fishes, subadults fed at higher trophic levels than juveniles, likely because of a shift from feeding predominantly on lower trophic-level prey taxa (e.g., crabs) to higher trophic-level prey taxa (e.g., teleosts). Despite a considerable overlap in stable isotope values between subadults and juveniles, stable isotope and stomach content data suggest a switch from feeding predominantly within mangrove prop roots as juveniles to foraging increasingly in adjacent seagrass beds as subadults. Niche width and degree of individual dietary specialization varied among years, suggesting important levels of temporal variation. In sum, individual snapper do not use resources homogeneously, and we outline some of the factors, including predation risk, increase piscivory, and temporal differences in resource use, that underlie this variation.
Acetolactate synthase activity and chlorsulfuron sensitivity of wheat cultivars

Differences were observed in the sensitivity of three wheat (Triticum aestivum L.) cultivars to chlorsulfuron. Shoot dry weight was reduced by foliar applications of chlorsulfuron to a greater extent in cv. Rongotea than in cvs Lancer and Kotare. There was no difference between these cultivars in the specific activity of acetolactate synthase (ALS) enzyme extracted from leaves or roots. Moreover, chlorsulfuron inhibited ALS from the wheat cultivars to the same extent in vitro. ALS measurement in vivo showed that after 15 h of incubating excised leaf tissues with chlorsulfuron, there was a greater reduction in ALS enzyme activity in Rongotea than in the other cultivars. Furthermore, I day after a foliar application of chlorsulfuron, in vitro ALS activity in leaves was reduced more in Rongotea than in Lancer or Kotare. Recovery of the enzyme activity following chlorsulfuron application was quicker in Kotare than in Lancer or Rongotea. It is concluded that differences in sensitivity of these wheat cultivars to chlorsulfuron are not due to differential ALS sensitivity or level, but may be due to differential rates of herbicide metabolism.
Energy-Aware Scheduling for Broadcast Erasure Channels With Two Energy Harvesting Receivers

A feedback-based coding algorithm is studied for broadcast packet erasure channels (BPECs) with energy harvesting receivers. A probabilistic algorithm is outlined, which is able to achieve the capacity region of two-user BPECs. The probabilistic algorithm is carefully studied from the optimization perspective. In this paper, we take into account the energy levels of receivers. Two new feedback schemes are proposed to reduce the energy consumption of receivers and we explain the advantage of each feedback scheme. We formulate the problem of maximizing the minimum weighted throughput of receivers for each feedback scheme. After several convexifications, we make the formulated optimizations tractable and propose an algorithm to solve the problems globally without compromising optimality. Once optimization problems are solved, we propose an energy-aware scheduling for packet broadcasting. Finally, a packet header design is proposed to enable utilization of the energy-aware scheduling. Simulation results verify that to achieve the optimal throughput, network-coding is necessary.
Characteristic of Cl− current induced by ATP in bovine aortic endothelial cells

Patch‐clamp whole‐cell recording techniques were used to study ATP‐induced Cl‐ current and the effects of Cl‐ channel blockers on NO release in bovine aortic endothelial cells. ATP evoked an outward rectified Cl‐ current with a reversal potential of −29±3 mV. This outward rectified Cl‐ current was dependent on Ca2+ influx, but not Ca2+ release. In Ca2+‐free medium, ATP did not produce the Cl‐ current; however, subsequent addition of Ca2+ to the medium evoked an ATP‐induced outward rectified Cl‐ current. Furosemide, glibenclamide, and DIDS inhibited ATP‐activated Cl‐ current in a concentration‐dependent manner with maximal inhibition of 88±4%, 93±1%, and 79±3%, respectively. The IC50 values of furosemide, glibenclamide, and DIDS were 6.2±2.6, 29.6±12.3, and 21.0±13.4 µM, respectively. These effects of Cl‐ channel blockers matched those on NO release from endothelial cells. Our data suggest that ATP‐induced Ca2+ entry followed by increased [Ca2+]i activates Ca2+‐activated Cl‐ channels which mediate NO release from endothelial cells. Drug Dev. Res. 58:53–56, 2003. © 2003 Wiley‐Liss, Inc.