Miracle-dz/UniFAR-FTUs huggingface dataset:
PLEKHM2 Loss of Function Impairs the Activity of iPSC-Derived Neurons via Regulation of Autophagic Flux

Pleckstrin Homology And RUN Domain Containing M2 (PLEKHM2) [delAG] mutation causes dilated cardiomyopathy with left ventricular non-compaction (DCM-LVNC), resulting in a premature death of PLEKHM2[delAG] individuals due to heart failure. PLEKHM2 is a factor involved in autophagy, a master regulator of cellular homeostasis, decomposing pathogens, proteins and other cellular components. Autophagy is mainly carried out by the lysosome, containing degradation enzymes, and by the autophagosome, which engulfs substances marked for decomposition. PLEKHM2 promotes lysosomal movement toward the cell periphery. Autophagic dysregulation is associated with neurodegenerative diseases’ pathogenesis. Thus, modulation of autophagy holds considerable potential as a therapeutic target for such disorders. We hypothesized that PLEKHM2 is involved in neuronal development and function, and that mutated PLEKHM2 (PLEKHM2[delAG]) neurons will present impaired functions. Here, we studied PLEKHM2-related abnormalities in induced pluripotent stem cell (iPSC)-derived motor neurons (iMNs) as a neuronal model. PLEKHM2[delAG] iMN cultures had healthy control-like differentiation potential but exhibited reduced autophagic activity. Electrophysiological measurements revealed that PLEKHM2[delAG] iMN cultures displayed delayed functional maturation and more frequent and unsynchronized activity. This was associated with increased size and a more perinuclear lysosome cellular distribution. Thus, our results suggest that PLEKHM2 is involved in the functional development of neurons through the regulation of autophagic flux.
A 10Gb/s/pin DQS and WCK Built-Out Tester for LPDDR5 DRAM Test

Many solutions for DRAM tests have been proposed to overcome the limitation of the low-performance automatic test equipment (ATE). Built-in-self-tester (BIST) has reduced the test burden for the high-cost ATE [1]. However, the test circuit burdens the area and power consumption of the DRAM, and the required functions not designed in the test circuit are difficult to test. Recently, a built-out tester (BOT) has been proposed to relieve the test circuit overhead in the DRAM and support high-speed tests [2–3]. It has the advantage of boosting maximum test speed with a low-speed ATE and reducing the pin costs of the ATE. Also, it performs myriad functions for DRAM read/write operations as a bridge between the ATE and the DRAM. Currently, as shown in Fig. 1(a), a data (DQ) test speed can be overcome by design for testability (DFT) implantation in the LPDDR5 DRAM. However, a data strobe (DQS) and write clock (WCK) test is difficult for applying DFT implantation.
Aerosol activation characteristics and prediction at the central European ACTRIS research station of Melpitz, Germany

Abstract. Understanding aerosol particle activation is essential for evaluating aerosol indirect effects (AIEs) on climate. Long-term measurements of aerosol particle activation help to understand the AIEs and narrow down the uncertainties of AIEs simulation. However, they are still scarce. In this study, more than 4 years of comprehensive aerosol measurements were utilized at the central European research station of Melpitz, Germany, to gain insight into the aerosol particle activation and provide recommendations on improving the prediction of number concentration of cloud condensation nuclei (CCN, NCCN). (1) The overall CCN activation characteristics at Melpitz are provided. As supersaturation (SS) increases from 0.1 % to 0.7 %, the median NCCN increases from 399 to 2144 cm−3, which represents 10 % to 48 % of the total particle number concentration with a diameter range of 10–800 nm, while the median hygroscopicity factor (κ) and critical diameter (Dc) decrease from 0.27 to 0.19 and from 176 to 54 nm, respectively. (2) Aerosol particle activation is highly variable across seasons, especially at low-SS conditions. At SS=0.1 %, the median NCCN and activation ratio (AR) in winter are 1.6 and 2.3 times higher than the summer values, respectively. (3) Both κ and the mixing state are size-dependent. As the particle diameter (Dp) increases, κ increases at Dp of ∼40 to 100 nm and almost stays constant at Dp of 100 to 200 nm, whereas the degree of the external mixture keeps decreasing at Dp of ∼40 to 200 nm. The relationships of κ vs. Dp and degree of mixing vs. Dp were both fitted well by a power-law function. (4) Size-resolved κ improves the NCCN prediction. We recommend applying the κ–Dp power-law fit for NCCN prediction at Melpitz, which performs better than using the constant κ of 0.3 and the κ derived from particle chemical compositions and much better than using the NCCN (AR) vs. SS relationships. The κ–Dp power-law fit measured at Melpitz could be applied to predict NCCN for other rural regions. For the purpose of improving the prediction of NCCN, long-term monodisperse CCN measurements are still needed to obtain the κ–Dp relationships for different regions and their seasonal variations.
A constitutive theory for shape memory polymers: coupling of small and large deformation

At high temperatures, SMPs share attributes like rubber and exhibit long-range reversibility. In contrast, at low temperatures they become very rigid and are susceptible to plastic, only small strains are allowable. But there relatively little literature has considered the unique small stain (rubber phase) and large stain (glass phase) coupling in SMPs when developing the constitutive modeling. In this work, we present a 3D constitutive model for shape memory polymers in both low temperature small strain regime and high temperature large strain regime. The theory is based on the work of Liu et al. [15]. Four steps of SMP’s thermomechanical loadings cycle are considered in the constitutive model completely. The linear elastic and hyperelastic effects of SMP in different temperatures are also fully accounted for in the proposed model by adopt the neo-Hookean model and the Generalized Hooke’s laws.
Potential of Polymer/Fullerene Nanocomposites for Anticorrosion Applications in the Biomedical Field

Initially, this review presents the fundamentals of corrosion-resistant polymer/fullerene nanocomposites. Then, the potential of polymer/fullerene nanocomposites for corrosion resistance in biomedical applications is presented. In particular, anticorrosion biomedical applications of fullerene-based nanomaterials are proposed for antimicrobial applications, drug delivery, bioimaging, etc. According to the literature, due to the low conductivity/anticorrosion features of pristine thermoplastic polymers, conjugated polymers (polyaniline, polypyrrole, polythiophene, etc.) with high corrosion resistance performance were used. Subsequently, thermoplastic/thermosetting polymers were filled with nanoparticles to enhance their anticorrosion properties relative to those of neat polymers. Accordingly, fullerene-derived nanocomposites were found to be effective for corrosion protection. Polymer/fullerene nanocomposites with a fine dispersion and interactions revealed superior anticorrosion performance. The formation of a percolation network in the polymers/fullerenes facilitated their electron conductivity and, thus, corrosion resistance behavior. Consequently, the anticorrosion polymer/fullerene nanocomposites were applied in the biomedical field. However, this field needs to be further explored to see the full biomedical potential of anticorrosion polymer/fullerene nanocomposites.
Histological Methods to Assess Skeletal Muscle Degeneration and Regeneration in Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is a progressive disease caused by the loss of function of the protein dystrophin. This protein contributes to the stabilisation of striated cells during contraction, as it anchors the cytoskeleton with components of the extracellular matrix through the dystrophin-associated protein complex (DAPC). Moreover, absence of the functional protein affects the expression and function of proteins within the DAPC, leading to molecular events responsible for myofibre damage, muscle weakening, disability and, eventually, premature death. Presently, there is no cure for DMD, but different treatments help manage some of the symptoms. Advances in genetic and exon-skipping therapies are the most promising intervention, the safety and efficiency of which are tested in animal models. In addition to in vivo functional tests, ex vivo molecular evaluation aids assess to what extent the therapy has contributed to the regenerative process. In this regard, the later advances in microscopy and image acquisition systems and the current expansion of antibodies for immunohistological evaluation together with the development of different spectrum fluorescent dyes have made histology a crucial tool. Nevertheless, the complexity of the molecular events that take place in dystrophic muscles, together with the rise of a multitude of markers for each of the phases of the process, makes the histological assessment a challenging task. Therefore, here, we summarise and explain the rationale behind different histological techniques used in the literature to assess degeneration and regeneration in the field of dystrophinopathies, focusing especially on those related to DMD.
Pan-retinal ganglion cell markers in mice, rats, and rhesus macaques

Univocal identification of retinal ganglion cells (RGCs) is an essential prerequisite for studying their degeneration and neuroprotection. Before the advent of phenotypic markers, RGCs were normally identified using retrograde tracing of retinorecipient areas. This is an invasive technique, and its use is precluded in higher mammals such as monkeys. In the past decade, several RGC markers have been described. Here, we reviewed and analyzed the specificity of nine markers used to identify all or most RGCs, i.e., pan-RGC markers, in rats, mice, and macaques. The best markers in the three species in terms of specificity, proportion of RGCs labeled, and indicators of viability were BRN3A, expressed by vision-forming RGCs, and RBPMS, expressed by vision- and non-vision-forming RGCs. NEUN, often used to identify RGCs, was expressed by non-RGCs in the ganglion cell layer, and therefore was not RGC-specific. γ-SYN, TUJ1, and NF-L labeled the RGC axons, which impaired the detection of their somas in the central retina but would be good for studying RGC morphology. In rats, TUJ1 and NF-L were also expressed by non-RGCs. BM88, ERRβ, and PGP9.5 are rarely used as markers, but they identified most RGCs in the rats and macaques and ERRβ in mice. However, PGP9.5 was also expressed by non-RGCs in rats and macaques and BM88 and ERRβ were not suitable markers of viability.
Screening Bambara Groundnut (Vigna subterranea L. Verdc) Genotypes for Drought Tolerance at the Germination Stage under Simulated Drought Conditions

Bambara groundnut (Vigna subterranea L. Verdc) is grown by smallholders and subsistence farmers in the marginal parts of sub-Saharan Africa. This legume is native to Africa and is cultivated throughout semi-arid sub-Saharan Africa. It is hardy and has been recognized as a nutritious food source in times of scarcity. Drought can negatively affect the germination or establishment of seedlings in the early stages of crop growth. Drought can limit the growing season of certain crops and create conditions that encourage the invasion of insects and diseases. Drought can also lead to a lack of crop yield, leading to rising food prices, shortages, and possibly malnutrition in vulnerable populations. A drought-tolerant genotype can be identified at the germination stage of Bambara groundnut by screening for drought-tolerance traits, and this knowledge can be applied to Bambara crop improvement programs to identify drought-tolerant traits during early growth phases. As an osmolyte, polyethylene glycol (PEG 6000) reduced water potential and simulated drought stress in Bambara groundnut seeds of different genotypes. Osmolytes are low-molecular-weight organic compounds that influence biological fluid properties. In this study, 24 Bambara groundnut genotypes were used. Data were collected on seed germination percentage (G%), germination velocity index (GVI), mean germination time (MGT), root dry mass (RDM), root fresh mass (RFM), and seven drought tolerance indices: mean productivity (MP), tolerance index (TOL), geometric mean productivity (GMP), stress susceptibility index (SSI), yield index (YI), yield stability index (YSI), stress tolerance index (STI) as well as seed coat color measurements. The data were applied to the mean observation of genotypes under simulated drought conditions (Ys) and the mean observation of genotypes under controlled conditions (Yp). Germination%, germination velocity index (GVI), mass germination time (MGT), and root fresh mass (RFM) differed significantly (p < 0.001) between the two stress conditions. Bambara genotypes Acc 82 and Acc 96 were found to be the most drought-tolerant.
The evolution of aggressive and amicable play fighting in primates: a phylogenetic perspective

ABSTRACT Play fighting involves competing for an advantage, which can be derived from behavior typical of conspecific aggression, predation, sexual and other affinitive contexts. Here the phylogenetic distribution of aggressive play fighting (involving biting) and amicable play fighting (involving grooming and mounting) in juveniles of 48 species of primates was analyzed. Both aggressive and amicable play fighting were likely equally present in ancestral primates, and then some lineages either maintained that pattern or exaggerated the use of one type relative to the other. In species engaging in both types of play, the ancestral pattern is for them to remain distinct, with sequences of one type not transforming into sequences of the other type. In two genera, mixing types of play was exaggerated, with rapid bidirectional transitions between aggressive and amicable play. These findings suggest that different types of play evolved independently and their combination is a secondarily evolved, derived state.
The effects of mutual coupling using a linear array of thin dipoles of finite length

The effects of mutual coupling on the direction finding accuracy of a linear array of dipole elements are studied. An approximative expression of the measured voltages when a plane wave is incident upon the array is derived using mutual impedances. The direction finding accuracy is then investigated by calculating the Cramer-Rao lower bound. It is found that a known coupling does not affect the estimation performance much. In the case of an unknown coupling, the estimation procedure can be simplified by using only a few off-diagonal elements of the coupling matrix. Depending on how many parameters are included, the RMS error can actually be smaller than the CRB for the case when all off-diagonals are estimated.
Effects of Bifidobacterium with the Ability of 2′-Fucosyllactose Utilization on Intestinal Microecology of Mice

In breast milk, 2′-Fucosyllactose (2′FL) is the most abundant breast milk oligosaccharide and can selectively promote the proliferation of bifidobacteria. This study aimed to explore the effect of ifidobacterial with different utilization capacities of 2′FL on the intestinal microecology of mice. Furthermore, the effects of ifidobacterial with different 2′FL utilization capabilities on mice gut microbiota under the competitive pressure of 2′FL as a carbon source were explored. Compared with the control group, 2′FL, Bifidobacterium (B.) bifidum M130R01M51 + 2′FL, B. longum subsp. Longum CCFM752, and CCFM752 + 2′FL treatments significantly decreased the food intake. Moreover, the water intake, body weight, and fecal water content in all groups showed no significant difference compared with the control group. The combination of B. longum subsp. longum CCFM752 and 2′FL can significantly increase the levels of pro-inflammatory and anti-inflammatory factors. B. bifidum M130R01M51 and mixed strains combined with 2′FL significantly increased the contents of acetic acid and isobutyric acid. The results showed that B. bifidum M130R01M51, B. breve FHuNCS6M1, B. longum subsp. longum CCFM752, and B. longum subsp. infantis SDZC2M4 combined with 2′FL significantly increased the species richness of the gut microbiota. Moreover, B. longum subsp. longum CCFM752 and B. longum subsp. infantis SDZC2M4 significantly increased the abundance of Faecalibaculum and Bifidobacterium, respectively. In conclusion, exploring the impact on intestinal microecology can provide theoretical guidance for the development of personalized prebiotics for different bifidobacteria, which has the potential to improve the ecological imbalance of infant gut microbiota.
Cognitive Load and Social Media Advertising

Abstract Social media engagement requires cognitive resources, which subsequently impact the advertisements consumers see while browsing. For the most part, however, advertising practitioners and scholars still study social media ads and messages as if they will receive users’ full attention and cognition. This study has two main contributions. First, we demonstrate that the use of social media induces a measurable degree of cognitive load, presumably because the variety of networking and media components requires users to hold multiple evaluation schemas in working memory. Second, we show that while under cognitive load, participants rely on cues (e.g., number of likes and comments) that trigger heuristics to influence purchase intentions. However, product involvement was found to serve as a boundary condition wherein those under cognitive load did not rely on cues when they had higher involvement with the advertised product. Drawing on the limited capacity model of motivated mediated message processing (LC4MP), this research tests the proposed hypotheses using a pilot study and three experimental studies to provide converging evidence for the influence of social media use on heuristics and subsequent purchase intentions. Analysis of thought elicitation further supports our proposed effect of cognitive load on consumer decision making. Theoretical and practical implications are discussed.
Optimization of Neural Tree Based on an Improved Quantum Particle Swarm Optimization

In the model of flexible neural tree (FNT), parameters are usually optimized by particle swarm optimization algorithm (PSO). Because PSO has many shortcomings such as being easily trapped in local optimal solution and so on, an improved algorithm based on quantum-behaved particle swarm optimization (QPSO) is presented. It is combined with the factor of speed, gather and disturbance, so as to be used to optimize the parameters of FNT. This paper applies the improved quantum particle swarm optimization algorithm to the neural tree, and compares it with the standard particle swarm algorithm in the optimization of FNT. The result shows that the proposed algorithm is with a better expression, thus improves the performance of the FNT.
Brown midrib mutant and genome‐wide association analysis uncover lignin genes for disease resistance in maize

Brown midrib (BMR) maize (Zea mays L.) harbors mutations that result in lower lignin levels and higher feed digestibility, making it a desirable silage market class for ruminant nutrition. Northern leaf blight (NLB) epidemics in upstate New York highlighted the disease susceptibility of commercially grown BMR maize hybrids. We found the bm1, bm2, bm3, and bm4 mutants in a W64A genetic background to be more susceptible to foliar fungal (NLB, gray leaf spot [GLS], and anthracnose leaf blight [ALB]) and bacterial (Stewart's wilt) diseases. The bm1, bm2, and bm3 mutants showed enhanced susceptibility to anthracnose stalk rot (ASR), and the bm1 and bm3 mutants were more susceptible to Gibberella ear rot (GER). Colocalization of quantitative trait loci (QTL) and correlations between stalk strength and disease traits in recombinant inbred line families suggest possible pleiotropies. The role of lignin in plant defense was explored using high‐resolution, genome‐wide association analysis for resistance to NLB in the Goodman diversity panel. Association analysis identified 100 single and clustered single‐nucleotide polymorphism (SNP) associations for resistance to NLB but did not implicate natural functional variation at bm1–bm5. Strong associations implicated a suite of diverse candidate genes including lignin‐related genes such as a β‐glucosidase gene cluster, hct11, knox1, knox2, zim36, lbd35, CASP‐like protein 8, and xat3. The candidate genes are targets for breeding quantitative resistance to NLB in maize for use in silage and nonsilage purposes.
Biocomposite Materials Based on Poly(3-hydroxybutyrate) and Chitosan: A Review

One of the important directions in the development of modern medical devices is the search and creation of new materials, both synthetic and natural, which can be more effective in their properties than previously used materials. Traditional materials such as metals, ceramics, and synthetic polymers used in medicine have certain drawbacks, such as insufficient biocompatibility and the emergence of an immune response from the body. Natural biopolymers have found applications in various fields of biology and medicine because they demonstrate a wide range of biological activity, biodegradability, and accessibility. This review first described the properties of the two most promising biopolymers belonging to the classes of polyhydroxyalkanoates and polysaccharides—polyhydroxybutyrate and chitosan. However, homopolymers also have some disadvantages, overcome which becomes possible by creating polymer composites. The article presents the existing methods of creating a composite of two polymers: copolymerization, electrospinning, and different ways of mixing, with a description of the properties of the resulting compositions. The development of polymer composites is a promising field of material sciences, which allows, based on the combination of existing substances, to develop of materials with significantly improved properties or to modify of the properties of each of their constituent components.
Toward a Holistic Framework for Human-Robot Coordination

The number of robotic systems in the world is growing rapidly. However, most industrial robots are isolated in caged environments for the safety of users. There is an urgent need for human-in-the-loop collaborative robotic systems since robots are very good at performing precise and repetitive tasks but lack the cognitive ability and soft skills of humans. To fill this need, a key challenge is how to enable a robot to interpret its human co-worker’s motion and intention. This research addresses this challenge by developing a collaborative human-robot interface via innovations in computer vision, robotics, and system integration techniques. This work integrates a holistic framework of cameras, motion sensors, and a 7-degree-of-freedom robotic manipulator controlled by vision data processing and motion planning algorithms implemented in the open-source robotics middleware Robot Operating System (ROS).
APPLICATION OF SPECTRAL METHODS TO THERMAL ANALYSIS OF NANOSCALE ELECTRONIC DEVICES

The transient thermal characteristics of nanoscale electronic devices operating at very high frequencies are studied by spectral methods. At such scales microscopic phenomena resulting from phonon collisions and phonon scattering become important. A device, consisting of an array of MOSFET transistors on silicon substrate, is considered as a test case. Thermal transport is represented by a reduced form of the Boltzmann transport equation: the thermal wave model or hyperbolic heat equation. The results indicate that spectral methods can be used effectively for the accurate prediction of the short-time transient effects in nanoscale devices. Such effects are amplified by a sharp increase in the operating voltage and the corresponding heat generation rate.