Miracle-dz/UniFAR-FTUs huggingface dataset:
Cell-derived hexameric β-amyloid: a novel insight into composition, self-assembly and nucleating properties

A key hallmark of Alzheimer’s disease (AD) is the extracellular deposition of amyloid plaques composed primarily of the amyloidogenic amyloid-β (Aβ) peptide. The Aβ peptide is a product of sequential cleavage of the Amyloid Precursor Protein (APP), the first step of which gives rise to a C-terminal Fragment (C99). Cleavage of C99 by γ-secretase activity releases Aβ of several lengths and the Aβ42 isoform in particular has been identified as being neurotoxic. The misfolding of Aβ leads to subsequent amyloid fibril formation by nucleated polymerisation. This requires an initial and critical nucleus for self-assembly. Here, we identify and characterise the composition and self-assembly properties of cell-derived hexameric Aβ42 and show its nucleating properties which are dependent on the Aβ monomer availability. Identification of nucleating assemblies that contribute to self-assembly in this way may serve as therapeutic targets to prevent the formation of toxic oligomers.
DDI2 protease activity controls embryonic development and inflammation via TCF11/NRF1

DDI2 is an aspartic protease that cleaves polyubiquitinated substrates. Upon proteotoxic stress, DDI2 activates the ER-bound transcription factor TCF11/NRF1 (NFE2L1), a master regulator of proteostasis maintenance in mammalian cells, and ensures the expression of rescue factors including proteasome subunits. Here we describe the consequences of DDI2 ablation both in vivo and in cells. Knock-out of DDI2 in mice resulted in embryonic lethality at E12.5 with severe developmental failure. Molecular characterization of the embryos and surrogate DDI2 knock-out cell lines showed insufficient proteasome expression with proteotoxic stress, accumulation of high molecular weight ubiquitin conjugates, and induction of the unfolded protein and integrated stress responses. We also show that DDI2 KO-induced proteotoxic stress causes the cell-autonomous innate immune system to induce a type I interferon signature. These results indicate an important role for DDI2 in the proteostasis network of cells and tissues and in the maintenance of a balanced immune response. Highlights DDI2-deficiency in mice causes severe developmental failure and embryonic lethality at mid-late gestation DDI2-deficiency causes severe proteotoxic stress and proteasome impairment DDI2-deficiency induces the UPR and ISR signaling pathways DDI2-deficient cells survive via STAT3-dependent interferon signaling
Dominant remodelling of cattle rumen microbiome by Schedonorus arundinaceus (tall fescue) KY-31 carrying a fungal endophyte

Tall fescue KY-31 feeds ~20% of the beef cattle in the United States. It carries a fungal endophyte that produces ergovaline, which causes toxicosis in cattle, leading to $2 billion revenue loss annually. The MaxQ cultivar of the grass is non-toxic, but less attractive economically. To develop ways of mitigating the toxicity, the rumen microbiome of cattle consuming KY-31 and MaxQ have been analyzed, principally for identifying ergovaline transforming microorganisms and often using fecal microbiome as a surrogate. We have hypothesized that KY-31 not only causes toxicosis, but also impacts rumen metabolism broadly, and tested the hypothesis by analyzing rumen microbiome compositions of cattle that grazed MaxQ with an intervening KY-31 grazing period with 16S rRNA-V4 element as identifier. We found that KY-31 remodeled the cellulolytic and saccharolytic communities substantially. This effect was not evident at whole microbiome levels but in the compositions of sessile and planktonic fractions. A move from MaxQ to KY-31 lowered the Firmicutes abundance in the sessile fraction and increased it in planktonic part and caused an opposite effect for Bacteroidetes, although the total abundances of these dominant rumen organisms remained unchanged. In the sessile fraction, the abundances of Fibrobacter, which degrades less degradable fibers, and certain cellulolytic Firmicutes such as Pseudobutyrivibrio and Butyrivibrio 2, dropped, and these losses were apparently compensated by increased occurrences of Eubacterium and specific Ruminococcaceae and Lachnospiraceae. In planktonic fraction the Tenericutes’ abundance increased as saccharolytic Bacteroidetes’ level dropped. Several potential ergovaline degraders were enriched. A return to MaxQ restored the original Firmicutes and Bacteroidetes distributions. However, the Fibrobacter and Butyrivibrio 2 abundances remained low and their substitutes maintained significant presence. The rumen microbiome was influenced minimally by animals’ fescue toxicosis and was distinct from previously reported fecal microbiomes in composition. In summary, KY-31 and MaxQ cultivars of tall fescue were digested in the cattle rumen with distinct consortia and the KY-31-specific features were dominant. The study highlighted the importance of analyzing sessile and planktonic fractions separately.
Investigation of the Role of Ionic Liquids in Imparting Electrocatalytic Behavior to Carbon Paste Electrode

In this paper, a survey has been undertaken to clarify the possible reasons for the electrocatalytic activity obtained by the presence of ionic liquid in carbon paste electrode (CPE). For this purpose, the effect of the addition of traces of ionic liquid to conventional CPE was investigated. Fe(CN)63−/4− was used as a probe and two ionic liquids, namely n-octylpyridinum hexafluorophosphate and 1-octyl-3-methylimidazolium hexaflourophosphate were tested for their electrocatalytic activity. The reasons for this electrocatalytic behavior were evaluated and it was found that different factors such as increase in the ionic conduction of the binder, decrease in the resistance of the modified electrode, increase in ion exchange properties of the electrode and the inherent catalytic activity of ionic liquids are responsible for the considerable improved electrochemical response obtained in the presence of traces of ionic liquid.
A midbrain - thalamus - cortex circuit reorganizes cortical dynamics to initiate planned movement

Motor behaviors are often planned long before execution, but only released after specific sensory events. Planning and execution are each associated with distinct patterns of motor cortex activity. Key questions are how these dynamic activity patterns are generated and how they relate to behavior. Here we investigate the multi-regional neural circuits that link an auditory ‘go cue’ and the transition from planning to execution of directional licking. Ascending glutamatergic neurons in the midbrain reticular and pedunculopontine nuclei show short-latency and phasic changes in spike rate that are selective for the go cue. This signal is transmitted via the thalamus to the motor cortex, where it triggers a rapid reorganization of motor cortex state from planning-related activity to a motor command, which in turn drives appropriate movement. Our studies show how brainstem structures can control cortical dynamics via the thalamus for rapid and precise motor behavior.
The composition of northeast pacific fishes in a fish tank examined by eDNA metabarcoding

The taxonomy of fish in the northeast Pacific area has been recently revised using molecular genetic methods, including the development of a reference library of DNA fragments for species identification. Such libraries are the basis for the development of non-invasive, high-throughput methods for monitoring biodiversity using environmental DNA (eDNA). In order to validate this approach, we used a water eDNA metabarcoding technique based on 12S rRNA and COI mitochondrial fragments and assessed the composition of the twenty northeast Pacific fish species held in a fish tank at the Primorsky Aquarium (Vladivostok, Russia). Only the 12S fragment revealed data on fish-related operational taxonomic units (OTUs). Approximately 68% of the reads were classified into two species of the genus Oncorhynchus, whose shredded fillet is used for feeding. According to the taxonomic identification for the rest of the reads, 8 out of 20 fish species in the tank (40%) were identified unambiguously, while two species could not be identified. Ten taxa can be considered conditionally identifiable since they might be concealed behind a conflicting taxonomic identification at the genus or family level. In this case, an improvement of the reference library would provide resolution. We detected contamination, which may be related to both intra-laboratory contaminants occurring during DNA extraction and water intake supplying the fish tank.
Vanadium (IV) benzenedicarboxylate: A novel adsorbent for selective separations

The crystal structure of VOBDC (BDC = 1,4-benzenedicarboxylate) has a 1-dimensional channel system with apertures of ∼8 Å, and shows remarkable flexibility upon adsorption/desorption of various guest molecules in the channels. VOBDC can selectively and rapidly adsorb organic molecules containing sulfur on exposure to a 5% CH_4/He stream with different contents of thiophene or dimethyl sulfide at ambient temperature. Selective uptake of thiophene from liquid octane with thiophene concentrations from 2000 ppmw down to 100 ppmw is also observed. X-ray crystallographic data show that the adsorbed thiophene molecules adopt a herringbone packing arrangement within the channels of VOBDC while adsorbed dimethyl sulfide molecules are disordered among several positions in the channels with the sulfur atoms pointing toward the channel walls. The observed adsorptive capacities for thiophene and dimethyl sulfide are 155 mg and 208 mg sulfur per gram of VOBDC, respectively, consistent with the crystal structure data.
Recognition of a pathogen avirulence (AVR) effector protein by a cognate plant resistance

Author list 6 Noureddine Lazar, Carl H. Mesarich, Yohann Petit-Houdenot, Nacera Talbi, Ines Li de la 7 Sierra-Gallay, Emilie Zélie, Karine Blondeau, Jérôme Gracy, Bénédicte Ollivier, Françoise 8 Blaise, Thierry Rouxel, Marie-Hélène Balesdent, Alexander Idnurm, Herman van 9 Tilbeurgh ¥ and Isabelle Fudal ¥ 10 11 1 Institute for Integrative Biology of the Cell (I2BC), Université Paris-Saclay, CEA, CNRS, 12 Gif-sur-Yvette, France 13
Preparative separation of isoflavones in plant extract of Pueraria lobata by high performance counter-current chromatography

Five isoflavones, puerarin, daidzin, daidzein, 3′-hydroxy-puerarin and 3′-methoxy-puerarin were isolated and purified simultaneously from Pueraria lobata for the first time by high performance counter-current chromatography (HPCCC) using a system consisting of hexane–ethyl acetate–n-butanol–ethanol–water (0.5 : 2 : 1 : 0.5 : 3.5, v/v/v/v/v). In total, 155 mg of puerarin, 41 mg of daidzin, 12 mg of 3′-hydroxy-puerarin, 6 mg of 3′-methoxy-puerarin and 106 mg of daidzein were purified from 5.1 g of the ethyl acetate extract of P. lobata; the purities of the five isoflavones as determined by high performance liquid chromatography (HPLC) were 98.77%, 96.53%, 97.59%, 90.21% and 98.36%, respectively. The structures of the five compounds were identified by their retention time and the electrospray ionization multi-stage tandem mass spectrometry (ESI-MSn) in the positive ion mode, and confirmed by 1H-NMR experiments. The characteristic ESI-MS fragmentation patterns of the five compounds are discussed.
EFFECTS OF WILDFIRE ON DENSITIES OF SECONDARY CAVITY-NESTING BIRDS IN PONDEROSA PINE FORESTS OF NORTHERN ARIZONA

Many catastrophic wildfires burned throughout forests in Arizona during the spring and summer of 1996 owing to severely dry conditions. One result of these fires was a loss of preexisting tree cavities for reproduction. In ponderosa pine (Pinus ponderosa) forests most cavities are found in dead trees; therefore, snags are a very important habitat component for cavity-nesting species. Thls study focused on the impacts of wildfire on bird populations within 3 ponderosa pine forests throughout northern Arizona. We present preliminary results from the first bird breeding season following the fires. We randomly established points throughout areas that represented 3 burn severities: severely burned, moderately burned, and unburned. We conducted fixed-radius point counts and nest searches throughout the breeding season. Secondary cavity-nesters as a group did not show significant differences in relative abundance among 3 categories of fire severity. When analyzed at the species level, however, the wildfires did affect the relative abundance of 2 secondary cavity-nesting species, western bluebirds and mountain chickadees. We found no secondary cavity-nests in severely burned areas, most likely due to the lack of cavities after the fire.
Nitro-Group–Directed Selective Dealkylation

Abstract Nitro-substituted phenolic ethers were successfully selectively dealkylated. The directing effect of the nitro group is supported by the excellent regioselectivities and good yields. These reactions demonstrate that the complexation of AlCl3 with the phenolic nitro group is stronger than with the phenolic ether alone. The mechanism for the selective dealkylation directed by the nitro group is proposed.
Towards Exploiting Geometry and Time for Fast Off-Distribution Adaptation in Multi-Task Robot Learning

We explore possible methods for multi-task transfer learning which seek to exploit the shared physical structure of robotics tasks. Specifically, we train policies for a base set of pre-training tasks, then experiment with adapting to new off-distribution tasks, using simple architectural approaches for re-using these policies as black-box priors. These approaches include learning an alignment of either the observation space or action space from a base to a target task to exploit rigid body structure, and methods for learning a time-domain switching policy across base tasks which solves the target task, to exploit temporal coherence. We find that combining low-complexity target policy classes, base policies as black-box priors, and simple optimization algorithms allows us to acquire new tasks outside the base task distribution, using small amounts of offline training data.
Backpropagation Free Transformers

This works focuses on evaluating whether the neural network transformer architecture can be learned in a more biologically plausible manner than is currently done using backpropagation. We identify three main problems with the biological plausibility of backpropagation-based learning, the weight transport problem , the global loss problem and the asymmetry problem , and prescribe methods aimed at addressing these issues. We show how these methods can be extended to deep and complex networks like transformers and we evaluate their effectiveness as a function of network depth. Our experiments demonstrate learning for large neural networks in natural language processing, which is a novel application of backpropagation free methods.
Identification of Tomato Leaf Disease Detection using Pretrained Deep Convolutional Neural Network Models

In this paper, we proposed a plant leaf disease identification model based on a Pretrained deep convolutional neural network (Deep CNN). The Deep CNN model is trained using an open dataset with 10 different classes of tomato leaves We observed that overall architectures which can increase the best performance of the model. The proposed model was trained using different training epochs, batch sizes and dropouts. The Xception has attained maximum accuracy compare with all other approaches. After an extensive simulation, the proposed model achieves classification accuracy better. This accuracy of the proposed work is greater than the accuracy of all other Pretrained approaches. The proposed model is also tested with respect to its consistency and reliability. The set of data used for this work was collected from the plant village dataset, including sick and healthy images. Models for detection of plant disease should predict the disease quickly and accurately in the early stage itself so that a proper precautionary measures can be applied to avoid further spread of the diseases. So, to reduce the main issue about the leaf diseases, we can analyze distinct kinds of deep neural network architectures in this research. From the outcomes, Xception has a constantly improving more to enhance the accuracy by increasing the number of epochs, without any indications of overfitting and decreasein quality. And Xception also generated a fine 99.45% precision in less computing time.
Cost assessment of mozzarella cheese analogues prepared using different types of casein

Three types of Mozzarella cheese analogues (MCAs) had been prepared using acid casein (AC), rennet casein (RC) and blend of them and cost of the analogues were compared with natural Mozzarella cheese (NMC) of reputed brand available in the market. Acid casein based MCA (ACMCA) was cheapest among all owing to lower cost of acid casein than rennet casein; similarly rennet casein based MCA (RCMCA) was costliest among all due to higher cost of rennet casein while the cost of MCA prepared using blend of RC and AC (ARCMCA) was in between. The raw materials cost was 82.87, 83.98 and 83.37 per cent of the total product cost for ACMCA, RCMCA and ARCMCA respectively. The total costing was Rs. 178.60, Rs. 191.00 and Rs. 184.00 for ACMCA, RCMCA and ARCMCA respectively for products prepared in the present study. The cost of ACMCA, RCMCA and ARCMCA was 38.42, 34.14 and 36.56 per cent cheaper respectively as compared to NMC.
High pressure phase transitions in Mg1–xCaxO: Theory

We have analysed a B1 → B2 structural phase transitions in Mg1–xCaxO solid solutions and their ground state properties by using first principle density functional theory and charge transfer interaction potential (CTIP) approach. The effects of exchange‐correlation interactions are handled by the generalized gradient approximation with Perdew–Burke–Ernzerhof type parameterization. CTIP approach includes the long range modified Coulomb with charge transfer interactions and short range part of this model includes the van der Waals as well as Hafemeister Flygare type overlap repulsive interactions. The study observes a linear variation of calculated transition pressure, bulk modulus and lattice parameter of Mg1−xCaxO as a function of Ca composition. The observed results for the end point members are in agreement to their experimental counterparts and the deviations have been discussed.
Integrating Human Body MoCaps into Blender using RGB Images

—Reducing the complexity and cost of a Motion Capture (MoCap) system has been of great interest in recent years. Unlike other systems that use depth range cameras, we present an algo-rithm that is capable of working as a MoCap system with a single Red-Green-Blue (RGB) camera, and it is completely integrated in an off-the-shelf rendering software. This makes our system easily deployable in outdoor and unconstrained scenarios. Our approach builds upon three main modules. First, given solely one input RGB image, we estimate 2D body pose; the second module estimates the 3D human pose from the previously calculated 2D coordinates, and the last module calculates the necessary rotations of the joints given the goal 3D point coordinates and the 3D virtual human model. We quantitatively evaluate the ﬁrst two modules using synthetic images, and provide qualitative results of the overall system with real images recorded from a webcam.
RESPONSE OF TOMATO LYCOPERSICON ESCUIENTUM MILL. AND SOIL MICROBIAL ACTIVITY TO GLOMUS MOSSEAE, TRICHODERMA HARZIANUM AND CHEMICAL FERTILIZATION

Mycorrhizal fungi, Trichoderma and chemical fertilizer have a desirable affect on tomato yield. However, the concern to eliminate the chemical fertilization and depends on microbes inoculations is still clouded. A field experiment was carried out into greenhouses in the AlSeyahi area, Babil Governorate to find out the role of biofertilization and chemical fertilizers on increasing microbial activity and tomato productivity. The split-plot design was used with three replicates, where the main plot included chemical fertilization 0%, 50% and 100% of the recommended doses. The subplot was included four types of bio-fertilization, control (C), Mycorrhizal (M), Trichoderma (T) and the mixture between Mycorrhizal fungi and Trichoderma (MT). Results showed that there was a significant increase in the microbial activity, bacterial and fungal cell numbers, nitrogen and phosphorus content and the total yield at the 100% and 50% of the recommended doses. Moreover, M led to a significant increase in the number of bacteria (41.7 x 10 colony-forming unit CFU/ g dry soil), and Mycorrhizal infection rate (80.02%). In addition, in MT treatment, the percentage of organic carbon increased by 0.39%, and the number of fungal cells were significantly higher than others (22.4 x 10 CFU/ g dry soil). The highest total yield was at MT (121.667 t.ha). In conclusion, the combination of Mycorrhizal fungi with Trichoderma at 50% of the recommended doses increased the total yield (151.67 ton. ha) and consequences on the reduction of soil contamination.
Technology Adoption and Employee’s Job Performance: An Empirical Investigation

Technology innovation has an important influence on employee’s job performance where it helps to reduce human error, increase productivity, and increase the speed of communication. Many organizations are facing difficulties in choosing suitable technology adoption strategies with the hope to improve efficiency and enhance employee performance to be competitive in the market. Hence, the purpose of this research is to investigate the relationship between technology adoption drivers and employee job performance in the Malaysian Manufacturing Industry. Several dimensions for employee job performance were considered in this research namely job stress, motivation, and workload. In addition, the mediating effect of perceived job insecurity was also evaluated on the relationship between technology adoption and employee job performance. Employing a quantitative research method, data was collected from 370 respondents through a structured online survey questionnaire. The findings indicated that job satisfaction and motivation to be statistically significant while the workload was failed to be retained in the research. Additionally, there was no statistical evidence for the mediating effect of job insecurity in the research. It is envisaged that these findings will provide incremental insights into the existing body of knowledge while providing some directions to the organization in determining the right set of drivers inculcating technology adoption for improved job performance.
A Review of the Role of Social Media for the Cultural Heritage Sustainability

During the last 20 years, with the development of Information and Communication Technologies (ICTs), an emerging interest has appeared in Digital Community Engagement (DCE) in the process of cultural heritage management. Due to a growing need to involve a broader community in the Historic Urban Landscape approach, social media are considered one of the most important platforms to promote the public participation process of urban heritage conservation in the context of rapid urbanization. Despite the growing literature on DCE, which has delivered a general overview of different digital technologies and platforms to enhance heritage conservation, little research has been done on taking stock of the utilization of social media in this process. This study aims to fill the research gap by providing a more comprehensive picture of the functionalities of social media platforms and their impacts on sustainable urban development through a systematic literature review. As a result, 19 out of 248 DCE relevant articles are selected as objects to illustrate the contribution of social media. The study identified the characteristics of these applied social media tools, explores their roles and influences in cases. The article concludes that social media offers a platform for a wider range of stakeholders to have a voice in the decision process of cultural heritage management, and it should be widely applied to encourage citizens from all over the world.