Miracle-dz/UniFAR-FTUs huggingface dataset:
cGAMP signaling controls a transient surface-associated lifestyle

A newfound signaling pathway employs a GGDEF enzyme with unique activity compared to the majority of homologs associated with bacterial cyclic di-GMP signaling. This system provides a rare opportunity to study how signaling proteins natively gain distinct function. Using genetic knockouts, riboswitch reporters, and RNA-Seq, we show that GacA, the Hypr GGDEF in Geobacter sulfurreducens, specifically regulates cyclic GMP-AMP (3’,3’-cGAMP) levels in vivo to stimulate gene expression associated with metal reduction separate from electricity production. To reconcile these in vivo findings with prior in vitro results that showed GacA was promiscuous, we developed a full kinetic model combining experimental data and mathematical modeling to reveal mechanisms that contribute to in vivo specificity. A 1.4 Å-resolution crystal structure of the Geobacter Hypr GGDEF domain was determined to understand the molecular basis for those mechanisms, including key cross-dimer interactions. Together these results demonstrate that specific signaling can result from a promiscuous enzyme.
Attention-Based Gait Recognition and Walking Direction Estimation in Wi-Fi Networks

Most existing Wi-Fi-based gait recognition systems consider gait cycle detection as a critical process. However, the noise mixed in dynamic measurements obtained from commercial Wi-Fi devices makes it hard to detect gait cycles. Herein, we adopt the attention-based Recurrent Neural Network (RNN) encoder-decoder and propose a cycle-independent human gait recognition and walking direction estimation system, termed AGait, in Wi-Fi networks. For capturing more human walking dynamics, two receivers together with one transmitter are deployed in different spatial layouts. The Channel State Information (CSI) from different receivers are first assembled and refined to form an integrated walking profile. Then, the RNN encoder reads and encodes the walking profile into primary feature vectors. Given a specific gait or direction sensing task, a corresponding and particular attention vector is computed by the decoder and is finally used to predict the target. The attention scheme motivates AGait to learn to adaptively align with different critical clips of CSI data for different tasks. We implement AGait on commercial Wi-Fi devices in three different indoor environments, and the experimental results demonstrate that AGait can achieve average <inline-formula><tex-math notation="LaTeX">$F_1$</tex-math><alternatives><mml:math><mml:msub><mml:mi>F</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:math><inline-graphic xlink:href="xu-ieq1-3012784.gif"/></alternatives></inline-formula> scores of 97.32 to 89.77 percent for gait recognition from a group of 4 to 10 subjects and 97.41 percent for direction estimation from 8 walking directions.
EFFECT OF ABIOTIC FACTORS ON COPEPOD PARASITES FROM BENI-HAROUN DAM (MILA CITY) NORTH- EAST OF ALGERIA.

Copepod parasites are among the highly ubiquitous a nd abundant organisms in the planet, although they cause marked ecological and economic damages in the world, including Algeria. This work was therefore, aimed to study the copepod para sites in gills of 776 individual freshwater fishes belonging to four caught fishes ( Luciobarbus callensis, Carassuis carassuis, Cyprinu s carpio and Abramis brama) from Béni-Haroun dam of Mila city (northeast of Al geria) during four seasons over two years (2015 & 2016). Here, the parasites have b een collected and identified, the epidemiological indices were determined and the effect of water phy sico-chemical parameters on parasites was examined using principal component correlation anal ysis (Statistica, Ver 8). Moreover, the morphoanatomical criteria of 249 collected parasites prom oted us to identify eight species ( Ergasilus sieboldi, Ergasilus peregrinus, Ergasilus briani, Neoergasilu japonicus, Ergasilus megaceros, Neoergasilus longispinosus, Paraergasilus brevigiditus and Lernea cyprinacea ) related to four genera and two families. Thus, the study appears that the effect o f physico-chemical parameters on parasitic infestat ion and number of parasites is positively correlated wi th temperature, dissolved oxygen, orthophosphate, nitrite and ammonium contents, and negatively corre lated with pH and nitrates during summer and autumn.
Enhancement of Antibiotic Activity and Reversal of Resistance in Clinically Isolated Methicillin-Resistant Staphylococcus aureus by Trachyspermum ammi Essential Oil

Background and objectives: Methicillin-resistant Staphylococcus aureus (MRSA) has resulted in a worldwide threat due to the virulence and broad distribution in the hospital and community. Novel antibiotics are required to combat the emergence of multidrug-resistant bacteria such as MRSA. In the present study, the antibacterial activity of Trachyspermum ammi essential oil alone and in combination with fifteen antibiotics of different classes against a standard and five clinical strains of MRSAs was investigated. Methods: Chemical composition of the essential oil was investigated by using gas chromatography-mass spectrometry (GC-MS). The possible synergistic interaction of several antibiotics in combination with essential oil was screened by disc diffusion method. Interaction of the essential oil and the candidate antibiotic was investigated by checkerboard assay. Results: The essential oil was rich in thymol (74.2%), p-cymene (16%), and γ-terpinene (7.1%). Combination of sub-inhibitory concentrations of essential oil with vancomycin or gentamicin increased their inhibition zones against MRSA ATCC 33591 and clinically isolated MRSAs. All of the clinically isolated MRSAs were resistant to gentamicin, while combination of gentamicin with the essential oil caused augmentation of the antibacterial activity and 4 to 520-fold decrease in gentamicin minimum inhibitory concentrations was observed against different MRSA strains with fractional inhibitory concentration indices ranging from 0.50 to 0.75. Combination of essential oil with ciprofloxacin or imipenem increased the inhibition zones against some clinically isolated MRSAs. Conclusion: Combination of sub-inhibitory concentrations of T. ammi essential oil and gentamicin could be considered as a new choice for treatment of infectious diseases caused by MRSA strains.
Improving the Performance of VGG Through Different Granularity Feature Combinations

Convolutional neural networks have achieved amazing success in many areas in recent years, and VGG is a widely used convolutional neural network model. However, it has some limitations, such as a large number of parameters, which take up significant memory and thus restrict its application in resource-constrained scenarios such as mobile devices and embedded systems. In convolutional neural network models, the different number of convolutional layers can extract different granularity features, which represent the different levels of importance in the image recognition process. Here, we propose a new VGG architecture with different granularity feature combinations that combine different granularity features from block1, block2, block3, block4, and block5 in VGG. Each block is followed by a local fully connected layer to reduce the dimensionality of the coarse and fine features, and five different granularity features are combined as the input of the first global fully connected layer. By combining the features of different blocks, it can increase information flow from a lower layer directly to a fully connected layer and increase feature reuse without adding too many connections. The addition of five local fully connected layers means an increase in parameters, so we reduce the neuron number in two global fully connected layers to reduce the number of parameters. The well-known datasets CIFAR-10 and MNIST were used to evaluate the network’s classification performance. The experimental results show that the proposed model achieves better training and testing performance than traditional VGGs and reduces the number of parameters.
A circuit of protein-protein regulatory interactions enables polarity establishment in a bacterium

Asymmetric cell division generates specialized daughter cells that play a variety of roles including tissue morphogenesis in eukaryotes and pathogenesis in bacteria. In the gram-negative bacterium Caulobacter crescentus, asymmetric localization of two biochemically distinct signaling hubs at opposite cell poles provides the foundation for asymmetric cell division. Through a set of genetic, synthetic biology and biochemical approaches we have characterized the regulatory interactions between three scaffolding proteins. These studies have revealed that the scaffold protein PodJ functions as a central mediator for organizing the new cell signaling hub, including promoting bipolarization of the central developmental scaffold protein PopZ. In addition, we identified that the old pole scaffold SpmX serves as a negative regulator of PodJ subcellular accumulation. These two scaffold-scaffold regulatory interactions serve as the core of an integrated cell polarization circuit that is layered on top of the cell-cycle circuitry to coordinate cell differentiation and asymmetric cell division.
Analysis of Sequential Conversions of Convertible Bonds: A Recurrent Survival Approach

This study uses recurrent survival analysis technique to show that higher spread of conversion-stock prices and higher buy-back ratio of stock repurchase provide the CBs’ debt-like signals of Constantinides and Grundy (1989); while lower risk-free rate, higher capital expenditures, higher non-management institutional ownership and higher total asset value provide the CBs’ equity-like signals of Stein (1992). While the equity-like signals might accelerate the rate of sequential conversions and weaken the CBs’ risk-mitigating effect in the presence of risk-shifting potential, this study shows that this can happen only in a financially healthy firm with higher free cash flow. For financially distressed firms, the CBs’ risk-mitigating effect is maintained.
A Gradient Crystal Plasticity Theory Based on an Extended Energy Balance

An overview of different methods for the derivation of extended continuum models is given. A gradient plasticity theory is established in the context of small deformations and single slip by considering the invariance of an extended energy balance with respect to Euclidean transformations, where the plastic slip is considered as an additional degree of freedom. Thermodynamically consistent flow rules at the grain boundary are derived. The theory is applied to a two- and a three-phase laminate.
A Non-Invasive Flexible Glucose Monitoring Sensor Using a Broadband Reject Filter

In this paper, a novel, highly accurate, non-invasive glucose-monitoring sensor that is based on a flexible broadband reject filter is presented. The filter topology comprises a tapered feed line at a top layer that excites four open loop resonators on the bottom layer. The broadband reject response is achieved by relying on a modified log-periodic distribution of the open loop resonators. The embedded resonators are reduced in size and are designed to exhibit an enhanced sensitivity to track the variations of the glucose level across the 1.25–2.65 GHz frequency span. The proposed flexible filter is tested within in-vitro, ex-vivo and in-vivo setups. A high correlation between the scattering parameters of the proposed sensor and the variations in glucose levels is attained. Regression models are developed using experimental data obtained from healthy patients that are subjected to glucose tolerance tests. Results demonstrate less than 4% mean absolute relative difference between the reference and estimated glucose levels, and the predicted glucose levels lie 100% within the clinically acceptable zones as shown by the Clarke Error Grid analysis.
Outage Probability and Ergodic Capacity of User Clustering and Beamforming MIMO-NOMA Relay System With Imperfect CSI Over Nakagami-$m$ Fading Channels

Although the theory of nonorthogonal multiple access (NOMA) has been widely investigated, so far, there is a lack of applying beamforming into NOMA systems. In this article, we propose a multiple-input and multiple-output (MIMO)-NOMA system, where all users in the whole system are divided into multiple clusters to reduce the inner interference. Next, the superpositioned signals at base station are beamed to the relays, and then, the relays communicate with the users through superposition coding in the power domain. We derive the exact expressions of the outage probability of each user and the ergodic capacity (EC) of each cluster in both cases, i.e., perfect successive interference cancellation (SIC) and imperfect SIC, taking into account the Nakagami-$m$ fading channels and imperfect channel state information (CSI). We also compare the outage performance and the EC of our proposed MIMO-NOMA relay system with an orthogonal multiple access (OMA) relay system. Monte Carlo simulations are used validate the derived mathematical expressions. Numerical results show that the outage performance and the EC of each user and the whole system are reduced remarkably due to the imperfect CSI but get better as the fading severity is less. Moreover, the EC of our proposed MIMO-NOMA relay system is higher than that of the OMA relay system.
Decoding Hand Motor Imagery Tasks Within the Same Limb From EEG Signals Using Deep Learning

Motor imagery (MI) tasks of different body parts have been successfully decoded by conventional classifiers, such as LDA and SVM. On the other hand, decoding MI tasks within the same limb is a challenging problem with these classifiers; however, it would provide more options to control robotic devices. This work proposes to improve the hand MI tasks decoding within the same limb in a brain-computer interface using convolutional neural networks (CNNs); the CNN EEGNet, LDA, and SVM classifiers were evaluated for two (flexion/extension) and three (flexion/extension/grasping) MI tasks. Our approach is the first attempt to apply CNNs for solving this problem to our best knowledge. In addition, visual and electrotactile stimulation were included as BCI training reinforcement after the MI task similar to feedback sessions; then, they were compared. The EEGNet achieved maximum mean accuracies of 78.46% (±12.50%) and 76.72% (±11.67%) for two and three classes, respectively. Outperforming conventional classifiers with results around 60% and 48%, and similar works with results lower than 67% and 75%, respectively. Moreover, the electrical stimulation over the visual stimulus was not significant during the calibration session. The deep learning scheme enhanced the decoding of MI tasks within the same limb against the conventional framework.
Infestation of Helicoverpa armigera (Hubner) on Bajra, Pennisetum glaucum (L) in Anand district of Gujarat, India

A heavy incidence of Helicoverpa armigera was noticed on bajra crop during flowering as well as milking stage at Borsad taluka of Anand district in Gujarat. The incidence of larva/ear head was observed during the survey which showed more than four larvae per plant from the different village area during summer season. Due to infestation of ear head worm in bajra, the flowering and ear heads stages are heavily damaged which leads to the pollens and seeds are feeding by the early and later instar larvae (3rd to 5th instar larvae) of H. armigera. The bajra crop was showed reduction in grain formation and yield of crop as compared to earlier years as per the farmers view. During these summer season, the heavy infestation of H. armigera in bajra crop to almost all the areas of Borsad taluka of Anand district which showed habitat and behavioral change in the rigid noctuid pest.
Trichoderma asperelloides enhances local and systemic acquired resistance response under low nitrate nutrition in Arabidopsis

Nitrogen (N) is essential for growth, development and defense but, how low N affects defense and the role of Trichoderma in enhancing defense under low nitrate is not known. Low nitrate fed Arabidopsis plants displayed reduced growth and compromised local and systemic acquired resistance responses when infected with both avirulent and virulent Pseudomonas syringae DC3000. These responses were enhanced in the presence of Trichoderma. The mechanism of increased local and systemic acquired resistance mediated by Trichoderma involved increased N uptake and enhanced protein levels via modulation of nitrate transporter genes. The nrt2.1 mutant is compromised in local and systemic acquired resistance responses suggesting a link between enhanced N transport and defense. Enhanced N uptake was mediated by Trichoderma elicited nitric oxide (NO). Low NO producing nia1,2 mutant and nsHb+ over expressing lines were unable to induce nitrate transporters and thereby compromised defense in the presence of Trichoderma under low N suggesting a signaling role of Trichoderma elicited NO. Trichoderma also induced SA and defense gene expression under low N. The SA deficient NahG transgenic line and the npr1 mutant were also compromised in Trichoderma-mediated local and systemic acquired resistance responses. Collectively our results indicated that the mechanism of enhanced plant defense under low N mediated by Trichoderma involves NO, ROS, SA production as well as the induction of NRT and marker genes for systemic acquired resistance. One-sentence summary Trichoderma enhances local and systemic acquired resistance under low nitrate nutrition
A survey of the damage caused by the Callosobruchusmaculatus (F.) on different legume seeds sold in Njikoka Local Government Area, Anambra State, Nigeria

— Callsobruchus maculatus (F.) commonly called cowpea weevil is a major pest of stored leguminous seeds. The level of damage caused by C. maculatus (F.) on five different legumes on sale in Njikoka L.G. A. , Anambra State was studied for a period of six weeks. The legume seeds were Vigna unguiculata var. brown (Brown cowpea) and Vigna unguiculata var. white (White cowpea), Glycine max (Soya beans), Vigna subterranea (Bambara nuts) and Cajanus cajan (Pigeon pea). They were purchased randomly from local traders at Orie-Agu market in Abagana, Anambra State. Clean seeds without infestation were selected for the study. One hundred grammes (100g) of each legume seeds were used. The weevils used for the study were reared in the laboratory. The F1 generation was used to infest the clean legume seeds. The weevils were introduced in different male to female ratios and containers covered with white muslin cloth to allow aeration. The experimental setup was left to stand on the laboratory bench while weight loss and emergence holes were observed at two week intervals for a period of six weeks. The treatments with the higher male to female ratios of weevils showed highest damage to legume seeds (15.08 ± 0.93). V. unguiculata-Cowpea (var. white) was the highest damaged seeds (13.88 ± 1.00), while G. max – soya beans were least damaged (2.24 ± 1.36). The damage done by the weevils on the different legume seeds were statistically significant (P<0.05) using Analysis of Variance (ANOVA) and Post Hoc tests. Damaged seeds could lead to serious economic losses for both the farmers and the country. Early harvest, good storage practices and facilities to reduce the attack of these pests on legume seeds is recommended.
Identifying the Determinants of Innovation Capability With Machine Learning and Patents

Innovation capability (IC) is a fundamental firms’ strategic asset to sustain competitive advantage. In this article, relying on patent data, patents forward citations are used as proxy of IC and the main patents numerical and categorical variables are considered as proxy of IC determinants. The main purpose of this article is to understand which patents features are relevant to predict IC, i.e., which are the determinants of IC within patents. Three different algorithms of machine learning, widely applied to model real-world phenomena, regularized least squares, deep neural networks, and random forest are applied for this investigation. Results show that the most important patent features useful to predict IC refer to internal determinants, such as the technological scope of the company (technological domains and International Patent Classification classes), the backward citations, and technical concepts. Some external variables are also relevant, such as the family size, a time-related variable, and the timespan between the youngest and oldest patent of the family. Implications from this article concern two perspectives. From a methodological perspective, the study shows the usefulness of machine learning approaches in simplifying the decision-making process as they reduce the number of variables to be considered to investigate the company’s IC and they provide accurate and easily interpretable result. From a managerial standpoint, this article points out the few and relevant patent variables to be considered when dealing with patents and IC.
Who Can Work from Home?

In response to the COVID-19 pandemic, many states have adopted stay-at-home orders, rendering a large segment of the workforce unable to continue doing their jobs. These policies have distributional consequences, as workers in some occupations may be better able to continue their work from home. I identify the segments of the U.S. workforce that can plausibly work from home by linking occupation data from O*NET to the American Community Survey. I find that lower-wage workers are up to three times less likely to be able to work from home than higher-wage workers. Those with lower levels of education, younger adults, ethnic minorities, and immigrants are also concentrated in occupations that are less likely to be performed from home.
Factors Influencing Good Governance in Forest Management and Protection: A Case Study of Mt. Elgon Forest Reserve, Kenya

Despite the socio-economic and environmental benefits of forests globally, these ecosystems have been degraded due to poor governance. Effective governance in the forest sector calls for the identification of concrete elements within the administrative sector by systematically analysing the current situation and direct efforts towards improving the systems. A functional governing system would promote positive changes and progress by identifying challenges and gaps and come up with guidelines geared towards strengthening global co-operation. Our study explored the various factors influencing effective governance in forest management and protection in Kenya, using the case of Mt. Elgon Forest Reserve. Purposive sampling design was used to collect data through structured questionnaires and interactive interviews among forest managers, forest adjacent communities and other relevant stakeholders. The study shows that majority of the local communities living adjacent to the forest have been sensitized about forest conservation, however, the capacity building did not entail technical forestry operations. This has hampered effective involvement of the communities in forest management. Majority of the forest management staff are well trained in forest management and therefore could implement sustainable management strategies, however, due to insufficient fund, these strategies could not be fully implemented. Most of the members of the local communities are not economically empowered and mainly derive their livelihood from the forest leading to overexploitation. This strains sustainable utilization of the forest resources. Cultural practices such as livestock grazing and living within the forest are hampering sustainable management of the forest. The study suggests that successful management of the forest is limited by inadequate involvement of local communities. This has led to apathy and degradation of the forest by members who feel that their views are not sort in the management of the forest. The study recommends multi-sectoral planning and representation of sectors involved in forest management and conservation Keywords: participatory forest management, forest adjacent communities, forest products, sustainable forest management DOI: 10.7176/JESD/11-12-06 Publication date: June 30th 2020