Miracle-dz/UniFAR-FTUs huggingface dataset:
A solvent-free process to design low density polyhydroxyalkanoate

The polyhydroxyalkanoates (PHAs) are biobased, biocompatible and biodegradable polyesters. To enhance their biodegradability and flexibility, we develop low density PHAs by an emulsion-templated method without organic solvent. Polycaprolactone (PCL) and castor oil are required to improve the flexibility and to generate the porosity, respectively. To overcome the well-known lack of compatibility between PHA and PCL, pluronic is introduced to improve the miscibility of these polyesters The densities of native PHA and PCL are 1.2 g.cm−3 and the densities decreased to 0.49 g.cm−3 in presence of castor oil (40 wt%). Different PHAs were studied: polyhydroxybutyrate (PHB), polyhydroxybutyrate-co-hydroxyvalerate (PHBHV) and polyhydroxybutyrate-co-hydroxyhexanoate (PHBHHx). The porous PHBHHx based material showed the best colonization by Pseudomonas, followed by the PHBHV and PHB. This colonization only occurred in the surface and no bacterial diffusion was observed inside the material. The biodegradability study in presence of lipase showed that after 8 days, the weight losses are, respectively, 20% and 75% when the densities decreased from 0.82 g.cm−3 to 0.49 g.cm−3. These results showed the importance of the porosity on the biodegradation of PHAs. Graphical Abstract
Impact of NiTb_xFe_2−XO_4 nanofiller in PVDF matrix for the characterization of magnetic, dielectric properties and effectiveness of EMI shielding

This paper reports the influence of the inclusion of terbium-doped nickel ferrite [NiTb_ x Fe_2− x O_4 ( x = 0.1, 0.2, 0.3)] nanofiller in polyvinylidene fluoride (PVDF) matrix for modification of the dielectric and magnetic properties of polymer nanocomposite. The dielectric spectroscopic analysis reveals a significant improvement in permittivity for a certain filler ( x = 0.3) content in the PVDF matrix. The magnetization (M–H) and FC-ZFC studies show a decrement in blocking ( T _b) temperature with high filler loading. Hard ferrimagnetic characteristics predominate over soft ferromagnetic properties at high filler concentrations. The higher saturation magnetization, high retentivity, high coercively and a wider hysteresis loop area are seen in the low-temperature regions. The lower skin depth and better shielding effectiveness give a great platform to the films for the fabrication of electromagnetic shielding (EMI) devices in the high-frequency domain. The light weight of Tb-NFO-PVDF nanocomposite film poses superior advantages against traditional EMI shielding material. Graphical abstract TOC: Represents magnetization plot, ZC & ZFC change with temperature (Inset) and skin depth with frequency plot (Inset).
A CT image matching algorithm based on singular value decomposition

To strengthen the noise immunity of images matching, and enhance the robustness of matching, we advanced an image matching algorithm based on singular value decomposition. Firstly, it fetched the feature point of reference drawing and floating drawing by using Harris Algorithm, and then matched the feature point set of the two drawings with singular value decomposition method. Because of the Orthogonal and similar properties of singular value decomposition, the noise immunity of this algorithm was stronger, and the robustness of matching was higher. The experimental result proves the effectiveness of this algorithm.
Neutron-induced charged-particle reaction studies in nuclear astrophysics with a Micromegas based gaseous detector

Neutron-induced charged-particle reaction studies on various unstable nuclei play an important role in understanding various nucleosynthesis processes occurring in explosive astrophysical scenarios. We are pursuing a novel experimental approach to study neutron-induced charge particle cross-sections for various unstable nuclei at effective temperatures of 1.5-3.5 GK using the 7Li(p, n)7Be reaction as a neutron source with three orders of magnitude higher neutron intensities with respect to currently available neutron time-of-flight facilities. We plan to perform our experiments with a 10-µA proton beam at the Physikalisch Technische Bundesanstalt facility (PTB, Germany), with a Micromegas based gaseous detector being developed.
Stromal Senescence following Treatment with the CDK4/6 Inhibitor Palbociclib Alters the Lung Metastatic Niche and Increases Metastasis of Drug-Resistant Mammary Cancer Cells

Simple Summary CDK4/6 inhibitors (CDKis) are a first-line treatment for metastatic hormone-receptor-positive breast cancer, but resistance frequently develops. One potential resistance mechanism could be induction of cellular senescence in non-tumor tissues. The aim of our study was to identify CDKi-induced changes to host tissues that impact metastasis. Using mouse models, we found that pretreatment with palbociclib can increase metastatic seeding of CDKi-resistant mammary cancer cells in lungs and that this can be mitigated by eliminating senescent host cells. We describe palbociclib-induced gene expression changes in lungs that correlate with this effect and reveal altered intra-lung immune populations. Senescent endothelial cells are identifiable within lung metastases of mice pretreated with palbociclib. Palbociclib-treated primary endothelial cell lines become senescent and increase tumor cell migration and monocyte trans-endothelial invasion. These studies describe how CDKi-induced cellular senescence in host tissues could affect metastasis in breast cancer, which remains a key obstacle to achieving long-term survival. Abstract Background: CDK4/6 inhibitors (CDKi) have improved disease control in hormone-receptor-positive, HER2-negative metastatic breast cancer, but most patients develop progressive disease. Methods: We asked whether host stromal senescence after CDK4/6 inhibition affects metastatic seeding and growth of CDKi-resistant mammary cancer cells by using the p16-INK-ATTAC mouse model of inducible senolysis. Results: Palbociclib pretreatment of naïve mice increased lung seeding of CDKi-resistant syngeneic mammary cancer cells, and this effect was reversed by depletion of host senescent cells. RNA sequencing analyses of lungs from non-tumor-bearing p16-INK-ATTAC mice identified that palbociclib downregulates immune-related gene sets and gene expression related to leukocyte migration. Concomitant senolysis reversed a portion of these effects, including pathway-level enrichment of TGF-β- and senescence-related signaling. CIBERSORTx analysis revealed that palbociclib alters intra-lung macrophage/monocyte populations. Notably, lung metastases from palbociclib-pretreated mice revealed senescent endothelial cells. Palbociclib-treated endothelial cells exhibit hallmark senescent features in vitro, upregulate genes involved with the senescence-associated secretory phenotype, leukocyte migration, and TGF-β-mediated paracrine senescence and induce tumor cell migration and monocyte trans-endothelial invasion in co-culture. Conclusions: These studies shed light on how stromal senescence induced by palbociclib affects lung metastasis, and they describe palbociclib-induced gene expression changes in the normal lung and endothelial cell models that correlate with changes in the tumor microenvironment in the lung metastatic niche.
A Robust Estimate of Continental‐Scale Terrestrial Carbon Sinks Using GOSAT XCO2 Retrievals

Satellite XCO2 retrievals could improve the estimates of surface carbon fluxes, but it remains unknown on what scales these estimates are robust. Here, we use the time‐dependent Bayesian synthesis top‐down method and prior net ecosystem exchanges (NEEs) from 12 terrestrial biosphere models (TBMs) to infer the monthly carbon fluxes of 51 land regions with constraints by GOSAT XCO2 retrievals. We find that the uncertainty (standard deviation of 12 TBMs) reduction rates (uncertainty reduction rate (URR)) decrease significantly at decreasing spatial scales. On the continental‐scale, the mean URR is about 57%, and the annual and seasonal cycle estimates of NEE are rather robust. The evaluation shows that the posterior CO2 concentrations are significantly improved at the continental scale. Our study suggests that the GOSAT XCO2 can only promise a robust continental‐scale NEE estimate, and improving the XCO2 accuracy is an effective way to achieve robust estimates on smaller scales under current spatial coverage.
Towards a curriculum of darkness: re-storying and retribution in youth arts programmes

ABSTRACT Our inquiry considers how minoritized youth counter brutal hegemony by re-imagining their identities through arts. In particular, it explores how minoritized youth draw on dark themes to (re)present their lives in creative production. Since K-12 educational contexts are often viewed as sites of convivial ambience where student depictions of violence are discouraged (Phillips [2012]. “Retribution and Rebellion: Children’s Meaning Making of Justice Through Storytelling.” International Journal of Early Childhood 44: 141–156.), research is needed to explicate how youth engage themes of physical violence, destruction, and even death in storying their lives. Our article is guided by the following questions: How do minoritized youth engage dark themes that disrupt discourses of conviviality in re-storying their lives? Why is a curriculum of darkness important for radical healing? Our illumination of the ways in which minoritized youth explored violence and destruction in their creative work significantly extends the literature on young people’s examination of identity and inequality. Our study brings attention to the need for a curriculum of darkness, where pedagogy might better reflect the dark themes that are culturally relevant (Ladson-Billings [1995]. “Toward a Theory of Culturally Relevant Pedagogy.” American Educational Research Journal 32 (3): 465–491. ) to the identities and lives of minoritized young people.
The ‘Total Transformation Alternation’ in the light of some Middle English data

The ‘Total Transformation Alternation’ (Levin, 1993: 57) has been attested in Modern English only with the Turn Verbs, verbs such as CHANGE, CONVERT, TRANSFORM, and TURN. This paper presents data showing the alternation also to be attested for some of the Middle English Cooking Verbs, including SĒTHEN ‘to simmer’. Since the alternation is not found with all the ME Cooking Verbs, this appears to be evidence against the correlation of lexical semantics with syntax. However, the paper goes on to demonstrate that this alternation is also available to ‘Reduction Verbs’, including Modern English REDUCE. Before REDUCE was used in this sense, Middle English verbs such as SĒTHEN could denote reduction in volume. When they were so used, they could appear in any of the syntactic constructions of this alternation. The paper concludes by reiterating the importance of investigating semantic components, rather than concentrating exclusively on verb classes.
The Nevanlinna's theorems for a class

In an infinite-dimensional Banach space E with a Schauder basis, the Nevanlinna's first and second main theorems are presented using the E-valued generalizing Poisson–Jensen–Nevanlinna formula instead of the classical Poisson–Jensen formula in and using the concept of compact projection in E. §Dedicated to Professor Guochun Wen on the occasion of his 75th birthday.
Federated learning framework integrating REFINED CNN and Deep Regression Forests

Abstract Summary Predictive learning from medical data incurs additional challenge due to concerns over privacy and security of personal data. Federated learning, intentionally structured to preserve high level of privacy, is emerging to be an attractive way to generate cross-silo predictions in medical scenarios. However, the impact of severe population-level heterogeneity on federated learners is not well explored. In this article, we propose a methodology to detect presence of population heterogeneity in federated settings and propose a solution to handle such heterogeneity by developing a federated version of Deep Regression Forests. Additionally, we demonstrate that the recently conceptualized REpresentation of Features as Images with NEighborhood Dependencies CNN framework can be combined with the proposed Federated Deep Regression Forests to provide improved performance as compared to existing approaches. Availability and implementation The Python source code for reproducing the main results are available on GitHub: https://github.com/DanielNolte/FederatedDeepRegressionForests. Contact ranadip.pal@ttu.edu Supplementary information Supplementary data are available at Bioinformatics Advances online.
IoT Capabilities Composition and Decomposition: A Systematic Review

As billions of IoT devices join the Internet, researchers and innovators increasingly explore IoT capabilities achieved via service composition or reuse of existing capabilities via service decomposition. Many systematic literature reviews (SLRs) were produced on this subject; however, two issues remain to be addressed: i) a reference taxonomy of the different aspects of IoT capabilities composition and decomposition is needed, and ii) many formal questions (e.g., standards role, formal representations applications, state-space explosion countermeasures, etc.), technical questions (e.g., composition process types and automation levels synergies, service decomposition categories, the role of AI/ML, etc.), and QoS questions (e.g., privacy, interoperability, and scalability challenges and solutions, etc.) remain unanswered. We introduce this work by discussing notions of IoT capabilities composition and decomposition in a layered IoT architecture while highlighting the strengths and weaknesses of existing SLRs. We identify unanswered questions through gaps in related work and motivate these questions using the PICOC methodology. We explain the search methodology and organize the topic questions using the proposed reference taxonomy. The identified research questions are answered, and trends and gaps that need additional attention from the research community are highlighted. This effort benefits city planners and end-users of IoT systems as it contributes to a better understanding of the role of composition and decomposition of IoT capabilities in building value-added services or reusing existing ones for resource optimization. For researchers, this effort contributes a reference taxonomy for the topic and sheds light on important questions while highlighting corresponding trends and gaps requiring further attention.
Optoelectronic measurement of semiconductor surfaces and interfaces with femtosecond optics

The basic concepts and preliminary applications of optically induced electromagnetic radiation from semiconductor surfaces and interfaces by using femtosecond optics are discussed. This submillimeter‐wave radiation provides a novel optoelectronic technique to study semiconductor electronic surface and interface properties with a contactless approach. The amplitude and phase of the electromagnetic radiation from the semiconductor surfaces depend on carrier mobility, impurity doping concentration, and strength and polarity of the static internal field. A large selection of bulk, epitaxial layer and superlattice samples from III‐V, II‐VI and group‐IV semiconductors has been tested. The orientation and strength of the static built‐in fields of a wide range of semiconductor surfaces, such as surface depletion, metal/semiconductor Schottky, p‐n junction and strain‐induced piezoelectric fields, can be determined and estimated.
Semantic-visual shared knowledge graph for zero-shot learning

Almost all existing zero-shot learning methods work only on benchmark datasets (e.g., CUB, SUN, AwA, FLO and aPY) which have already provided pre-defined attributes for all the classes. These methods thus are hard to apply on real-world datasets (like ImageNet) since there are no such pre-defined attributes in the data environment. The latest works have explored to use semantic-rich knowledge graphs (such as WordNet) to substitute pre-defined attributes. However, these methods encounter a serious “role=“presentation”>domain shift” problem because such a knowledge graph cannot provide detailed enough semantics to describe fine-grained information. To this end, we propose a semantic-visual shared knowledge graph (SVKG) to enhance the detailed information for zero-shot learning. SVKG represents high-level information by using semantic embedding but describes fine-grained information by using visual features. These visual features can be directly extracted from real-world images to substitute pre-defined attributes. A multi-modals graph convolution network is also proposed to transfer SVKG into graph representations that can be used for downstream zero-shot learning tasks. Experimental results on the real-world datasets without pre-defined attributes demonstrate the effectiveness of our method and show the benefits of the proposed. Our method obtains a +2.8%, +0.5%, and +0.2% increase compared with the state-of-the-art in 2-hops, 3-hops, and all divisions relatively.
Therapeutic potential of small extracellular vesicles derived from mesenchymal stem cells for spinal cord and nerve injury

Neural diseases such as compressive, congenital, and traumatic injuries have diverse consequences, from benign mild sequelae to severe life-threatening conditions with associated losses of motor, sensory, and autonomic functions. Several approaches have been adopted to control neuroinflammatory cascades. Traditionally, mesenchymal stem cells (MSCs) have been regarded as therapeutic agents, as they possess growth factors and cytokines with potential anti-inflammatory and regenerative effects. However, several animal model studies have reported conflicting outcomes, and therefore, the role of MSCs as a regenerative source for the treatment of neural pathologies remains debatable. In addition, issues such as heterogeneity and ethical issues limited their use as therapeutic agents. To overcome the obstacles associated with the use of traditional agents, we explored the therapeutic potentials of extracellular vesicles (EVs), which contain nucleic acids, functional proteins, and bioactive lipids, and play crucial roles in immune response regulation, inflammation reduction, and cell-to-cell communication. EVs may surpass MSCs in size issue, immunogenicity, and response to the host environment. However, a comprehensive review is required on the therapeutic potential of EVs for the treatment of neural pathologies. In this review, we discuss the action mechanism of EVs, their potential for treating neural pathologies, and future perspectives regarding their clinical applications.
The Singular-Vector Structure of the Atmospheric Global Circulation

Abstract The local phase-space instability Of the atmospheric global circulation is Characterized by its (nonmodal) singular vectors. The formalism of singular vector analysis is described. The relations between singular vectors, normal modes, adjoint modes, Lyapunov vectors, perturbations produced by the so-called breeding method, and wave pseudomomentum are outlined. Techniques to estimate the dominant part of the singular spectrum using large-dimensional primitive equation models are discussed. These include the use of forward and adjoint tangent propagators with a Lanczos iterative algorithm. Results are described, based first on statistics of routine calculations made between December 1992 and August 1993, and second on three specific case studies. Results define three dominant geographical areas of instability in the Northern Hemisphere: the two regions of storm track cyclogenesis, and the North African subtropical jet Singular vectors can amplify as much as tenfold over 36 hours, and in winter ther.
Spectral anomalies of pulsed Hermite–Gaussian beams focused by a dispersive aperture lens

Starting from the Huygens–Fresnel diffraction integral, the recurrence expressions for the power spectra of pulsed Hermite–Gaussian (H–G) beams focused by a dispersive aperture lens are derived and the spectral anomalies of pulsed H–G beams in the focused field are studied. Numerical results are given to illustrate the dependence of spectral anomalies’ behavior on the pulse parameters, truncation parameter and material dispersion of the lens. The potential applications of spectral anomalies of ultrashort pulsed beams in information encoding and information transmission are considered.
Dynamics of two-step reversible enzymatic reaction under fractional derivative with Mittag-Leffler Kernel

Chemical kinetics is a branch of chemistry that is founded on understanding chemical reaction rates. Chemical kinetics relates many aspects of cosmology, geology, and even in some cases of, psychology. There is a need for mathematical modelling of these chemical reactions. Therefore, the present research is based on chemical kinetics-based modelling and dynamics of enzyme processes. This research looks at the two-step substrate-enzyme reversible response. In the two step-reversible reactions, substrate combines with enzymes which is further converted into products with two steps. The model is displayed through the flow chart, which is then transformed into ODEs. The Atangana-Baleanu time-fractional operator and the Mittag-Leffler kernel are used to convert the original set of highly nonlinear coupled integer order ordinary differential equations into a fractional-order model. Additionally, it is shown that the solution to the investigated fractional model is unique, limited, and may be represented by its response velocity. A numerical scheme, also known as the Atangana-Toufik method, based on Newton polynomial interpolation technique via MATLAB software, is adopted to find the graphical results. The dynamics of reaction against different reaction rates are presented through various figures. It is observed that the forward reaction rates increase the reaction speed while backward reaction rates reduce it.
Amino acid substitutions in human growth hormone affect secondary structure and receptor binding

The interaction between human Growth Hormone (hGH) and hGH Receptor (hGHR) has basic relevance to cancer and growth disorders, and hGH is the scaffold for Pegvisomant, an anti-acromegaly therapeutic. For the latter reason, hGH has been extensively engineered by early workers to improve binding and other properties. We are particularly interested in E174 which belongs to the hGH zinc-binding triad; the substitution E174A is known to significantly increase binding, but to now no explanation has been offered. We generated this and several computationally-selected single-residue substitutions at the hGHR-binding site of hGH. We find that, while many successfully slow down dissociation of the hGH-hGHR complex once bound, they also slow down the association of hGH to hGHR. The E174A substitution induces a change in the Circular Dichroism spectrum that suggests the appearance of coiled-coiling. Here we show that E174A increases affinity of hGH against hGHR because the off-rate is slowed down more than the on-rate. For E174Y (and certain mutations at other sites) the slowdown in on-rate was greater than that of the off-rate, leading to decreased affinity. The results point to a link between structure, zinc binding, and hGHR-binding affinity in hGH.