Fundamental Class Research Articles

Imprinted Hydrogel Nanoparticles for Protein Biosensing: A Review.

Over the past decade, molecular imprinting (MI) technology has made tremendous progress, and the advancements in nanotechnology have been the major driving force behind the improvement of MI technology. The preparation of nanoscale imprinted materials, i.e., molecularly imprinted polymer nanoparticles (MIP NPs, also commonly called nanoMIPs), opened new horizons in terms of practical applications, including in the field of sensors. Currently, hydrogels are very promising for applications in bioanalytical assays and sensors due to their high biocompatibility and possibility to tune chemical composition, size (microgels, nanogels, etc.), and format (nanostructures, MIP film, fibers, etc.) to prepare optimized analyte-responsive imprinted materials. This review aims to highlight the recent progress on the use of hydrogel MIP NPs for biosensing purposes over the past decade, mainly focusing on their incorporation on sensing devices for detection of a fundamental class of biomolecules, the peptides and proteins. The review begins by directing its focus on the ability of MIPs to replace biological antibodies in (bio)analytical assays and highlight their great potential to face the current demands of chemical sensing in several fields, such as disease diagnosis, food safety, environmental monitoring, among others. After that, we address the general advantages of nanosized MIPs over macro/micro-MIP materials, such as higher affinity toward target analytes and improved binding kinetics. Then, we provide a general overview on hydrogel properties and their great advantages for applications in the field of Sensors, followed by a brief description on current popular routes for synthesis of imprinted hydrogel nanospheres targeting large biomolecules, namely precipitation polymerization and solid-phase synthesis, along with fruitful combination with epitope imprinting as reliable approaches for developing optimized protein-imprinted materials. In the second part of the review, we have provided the state of the art on the application of MIP nanogels for screening macromolecules with sensors having different transduction modes (optical, electrochemical, thermal, etc.) and design formats for single use, reusable, continuous monitoring, and even multiple analyte detection in specialized laboratories or in situ using mobile technology. Finally, we explore aspects about the development of this technology and its applications and discuss areas of future growth.

Amberlyst-15 catalysed retro-Claisen condensation of β-diketones with alcohols: A practical approach to synthesize esters and ketoesters

Esters are fundamental class of organic compounds with tremendous industrial applications. They are generally synthesized via the condensation of alcohol with acid. Herein, we report synthesis of esters and keto esters via retro-Claisen condensation of alcohols with β-diketones in presence of Amberlyst-15, a commercially available heterogeneous catalyst. The methodology is applied to synthesize several industrially relevant acetates, such as n-butyl acetate, isobutyl acetate, 2-ethylhexyl acetate and isopropyl acetate in multi-gram scale. When 2-acetyl cyclohexanone or 2-acetyl cyclopentanone were used as β-diketones, long chain keto-esters formed as sole products in excellent yields. The reaction tolerates a wide range of functional groups, such as olefins, alkynes, halides, nitro and esters. Furthermore, the protocol allows late-stage acetylation of naturally occurring alcohols. The methodology provides a practical approach for large scale synthesis of esters using fixed-bed continuous process. The catalyst can be recovered from the reaction mixture and reused up to 5 cycles without significant change in catalytic activity. To the best of our knowledge, this is the first example of a reusable Brønsted acid catalyst used in the synthesis of esters via retro-Claisen type condensation of alcohols and β-diketones.

Chromatic Schultz polynomial of certain graphs

A topological index of a graph $G$ is a real number which is preserved under isomorphism. Extensive studies on certain polynomials related to these topological indices have also been done recently. In a similar way, chromatic versions of certain topological indices and the related polynomials have also been discussed in the recent literature. In this paper, the chromatic versions of the Schultz polynomial and modified chromatic Schultz polynomial are introduced and determined this polynomial for certain fundamental graph classes.

Pollinators and plants as ecosystem engineers: post‐dispersal fruits provide new habitats for other organisms

Ecosystem engineering consists of a ubiquitous and fundamental class of interactions where some organisms promote state changes in biotic and abiotic materials which indirectly affect others. Since the concept was created as a counterpoint to traditional flux‐based models, pollinators have never been considered to promote ecosystem engineering because they modulate the supply of resources used by seed/fruit consumers. However, dry fruits may persist in the environment for long periods after seed dispersion as empty structures that are an additional alternative for occupancy. These increase the realized niche of some organisms, being a clear example of biogenic habitats. Here, we demonstrate how pollination may boost ecosystem engineering using an illustrative case study based on a specialized interaction between a bee and an orchid with characteristic capsular fruits. We demonstrate that the orchid is fully dependent on the pollinator to set fruits. Post‐dispersal fruits are voluminous and remain attached to the plant for several years. By investigating the occupation patterns of arthropods, we show that post‐dispersal fruits are highly suitable for occupants when compared to pre‐dispersal and dispersing fruits. Only 13.3% of post‐dispersal fruits were never occupied, 33.3% had organisms inside and 53.3% showed signs of previous occupation. We propose that pollinators are allogenic engineers and plants autogenic, since they promote state changes through their actions and their own physical structure, respectively. Thus, pollination is a case of cooperative ecosystem engineering whereby the effects of the interaction between two or more species expand habitat suitability. Since most plants rely on pollination to set fruits, we suggest that pollination‐mediated engineering constitutes a widespread phenomenon. This offers a new perspective about the effects of pollination in nature, highlighting the importance of pollinators and opening new avenues of investigation of ecosystem dynamics and biodiversity maintenance.

The log product formula

We prove a formula expressing the Log Gromov-Witten Invariants of a product of log smooth varieties $V \times W$ in terms of the invariants of $V$ and $W$. This extends results of F. Qu and Y.P. Lee, who introduced this formula analogously to K. Behrend. The proof requires notions of "log normal cone" and "log virtual fundamental class," as well as modified versions of standard intersection-theoretic machinery adapted to Log Geometry.

Sulfur-based functional groups in agrochemistry.

The element sulfur has an outstanding role in the crop protection chemistry because it is used in its elemental form as a multisite fungicide, but is also part of agrochemicals in the form of aromatic or aliphatic sulfur-containing rings or sulfur-based functional groups. This review gives an exhaustive overview over the latter category. Several fundamental agrochemical compound classes are named after a sulfur-based functionality, such as the dithiocarbamate fungicides and sulfonylurea herbicides. Altogether, 16 different sulfur-based functional groups are presented with their typical synthesis approaches and most important representatives in crop protection. © 2023 Society of Chemical Industry.

A Nonparametric Algorithm for Optimal Stopping Based on Robust Optimization

Optimal stopping is a fundamental class of stochastic dynamic optimization problems with numerous applications in finance and operations management. In “A nonparametric algorithm for optimal stopping based on robust optimization,” the author introduces an approach based on robust optimization for computing near-optimal solutions for computationally demanding stochastic optimal stopping problems with known probability distributions. Through this new use of robust optimization, the paper develops new algorithms for solving stochastic optimal stopping problems that are practical and can outperform state-of-the-art simulation-based algorithms in the context of pricing high-dimensional financial options.

Subgrid Parameterization of Eddy, Meanfield and Topographic Interactions in Simulations of an Idealized Antarctic Circumpolar Current

AbstractThe ocean circulation dynamics can be represented as a high‐dimensional multi‐scale nonlinear system with inhomogenous meanfields and topography. Numerical simulations of the ocean dynamics resolve the large scales of motion on a computational grid, with the unresolved subgrid interactions parameterized. These simulations are highly dependent upon the grid resolution, unless the subgrid terms are appropriately parameterized. There are five fundamental classes of subgrid interactions: eddy‐eddy; eddy‐topographic; eddy‐meanfield; meanfield‐meanfield; and meanfield‐topographic. Scale dependent parameterizations representing each of these interaction classes are presented here in oceanic flows for the first time. Subgrid parameterizations are calculated and validated in baroclinic quasi‐geostrophic simulations of idealized Antarctic Circumpolar Current flows with representative mean currents and ocean floor topography. The parameterization coefficients are derived from the coarse grained statistics of high resolution reference simulations in spectral space. Stochastic and deterministic parameterizations are developed for the eddy‐eddy interactions, and deterministic forms for the remaining classes. The kinetic energy spectra and meanfield resulting from large eddy simulations (LES) adopting these coefficients accurately replicate those of the reference simulation. The eddy‐eddy interactions are dominant, but all classes need to be parameterized for best results. For LES where baroclinic instability is explicitly resolved the stochastic variants out‐perform the deterministic ones across all scales. When baroclinic instability is not explicitly resolved, the stochastic variants out‐perform the deterministic cases at the large scales, but introduce some distortions at the smallest resolved scales. This study provides an assessment of the relevant strengths of the subgrid interaction classes in an idealized yet representative ocean.

2-Layer k-Planar Graphs Density, Crossing Lemma, Relationships And Pathwidth

Abstract The $2$-layer drawing model is a well-established paradigm to visualize bipartite graphs where vertices of the two parts lie on two horizontal lines and edges lie between these lines. Several beyond-planar graph classes have been studied under this model. Surprisingly, however, the fundamental class of $k$-planar graphs has been considered only for $k=1$ in this context. We provide several contributions that address this gap in the literature. First, we show tight density bounds for the classes of $2$-layer $k$-planar graphs with $k\in \{2,3,4,5\}$. Based on these results, we provide a Crossing Lemma for $2$-layer $k$-planar graphs, which then implies a general density bound for $2$-layer $k$-planar graphs. We prove this bound to be almost optimal with a corresponding lower bound construction. Finally, we study relationships between $k$-planarity and $h$-quasiplanarity in the $2$-layer model and show that $2$-layer $k$-planar graphs have pathwidth at most $k+1$ while there are also $2$-layer $k$-planar graphs with pathwidth at least $(k+3)/2$.

The extracellular matrix landscape in salivary gland carcinomas is defined by cellular differentiation via expression of three distinct protein modules.

The extracellular matrix (ECM) is an integral part of the tumor microenvironment of carcinomas. Even though salivary gland carcinomas (SGCs) display a range of tumor cell differentiation and distinct extracellular matrices, their ECM landscape has not been characterized in depth. The ECM composition of 89 SGC primaries, 14 metastases, and 25 normal salivary gland tissues was assessed using deep proteomic profiling. Machine learning algorithms and network analysis were used to detect tumor groups and protein modules that explain specific ECM landscapes. Multimodal in situ studies to validate exploratory findings and to infer a putative cellular origin of ECM components were applied. We revealed two fundamental SGC ECM classes which align with the presence or absence of myoepithelial tumor differentiation. We describe the SGC ECM through three biologically distinct protein modules that are differentially expressed across ECM classes and cell types. The modules have a distinct prognostic impact on different SGC types. Since targeted therapy is rarely available for SGC, we used the proteomic expression profile to identify putative therapeutic targets. In summary, we provide the first extensive inventory of ECM components in SGC, a difficult-to-treat disease that encompasses tumors with distinct cellular differentiation. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

A Theoretical Framework for Implementable Nucleic Acids Feedback Systems.

Chemical reaction networks can be utilised as basic components for nucleic acid feedback control systems' design for Synthetic Biology application. DNA hybridisation and programmed strand-displacement reactions are effective primitives for implementation. However, the experimental validation and scale-up of nucleic acid control systems are still considerably falling behind their theoretical designs. To aid with the progress heading into experimental implementations, we provide here chemical reaction networks that represent two fundamental classes of linear controllers: integral and static negative state feedback. We reduced the complexity of the networks by finding designs with fewer reactions and chemical species, to take account of the limits of current experimental capabilities and mitigate issues pertaining to crosstalk and leakage, along with toehold sequence design. The supplied control circuits are quintessential candidates for the first experimental validations of nucleic acid controllers, since they have a number of parameters, species, and reactions small enough for viable experimentation with current technical capabilities, but still represent challenging feedback control systems. They are also well suited to further theoretical analysis to verify results on the stability, performance, and robustness of this important new class of control systems.

The Log Product Formula in Quantum K-theory

AbstractWe prove a formula expressing the K-theoretic log Gromov-Witten invariants of a product of log smooth varieties $V \times W$ in terms of the invariants of V and W. The proof requires introducing log virtual fundamental classes in K-theory and verifying their various functorial properties. We introduce a log version of K-theory and prove the formula there as well.

Nonnoetherian singularities and their noncommutative blowups

We establish a new fundamental class of varieties in nonnoetherian algebraic geometry related to the central geometry of dimer algebras. Specifically, given an affine algebraic variety X and a finite collection of non-intersecting positive dimensional algebraic sets Y_i \subset X , we construct a nonnoetherian coordinate ring whose variety coincides with X except that each Y_i is identified as a distinct positive dimensional closed point. We then show that the noncommutative blowup of such a singularity is a noncommutative desingularization, in a suitable geometric sense.

SPAYK: An environment for spiking neural network simulation

In research areas such as mobile robotics and computer vision, energy and computational efficiency have become critical. This has greatly increased interest in high-efficiency neuromorphic hardware and spiking neural networks. Because neuromorphic hardware is not yet widely available, spiking neural network studies are conducted by simulations. There are numerous simulators available today, each designed for a specific purpose. In this paper, a novel and open source package (SPAYK) for simulating spiking neural networks is presented. SPAYK has been proposed to speed up spiking neural network research. In the majority of simulators, networks are expressed with differential equations and require advanced neuroscience knowledge since such simulators are generally designed for brain and neuroscience research. SPAYK, on the other hand, is specifically designed as a framework to easily design spiking neural networks for practical problems. SPAYK is an easy-to-use Python package. There are three fundamental classes in the core: the model class for creating neuron groups, the organization class for simulating tissues, and the learning class for synaptic plasticity. While developing and testing the SPAYK environment, various experiments were carried out. This study includes three of these experiments. In the first experiment, we investigated the behavior of a group of Izhikevich neurons for visual stimuli. Also, a single Izhikevich neuron has been trained to respond to a particular label in a supervised manner with synaptic plasticity. In the second experiment, a well-known experiment was repeated to validate SPAYK. In this experiment, a neuron trained by synaptic plasticity can recognize repetitive patterns in a spike train. In the third experiment, a similar neuron was simulated with stimuli with multiple labels adapted from the MNIST dataset. It has been shown that the neuron can classify a particular label by synaptic plasticity. All these experiments and the SPAYK environment are presented as open-source tools.

A new light on the FKMM invariant and its consequences

“Quaternionic” vector bundles are the objects that describe topological phases of quantum systems subjected to an odd time-reversal symmetry (class AII). In this work, we prove that the Furuta–Kametani–Matsue–Minami (FKMM) invariant provides the correct fundamental characteristic class for the classification of “Quaternionic” vector bundles in dimension less than or equal to three (low dimension). The new insight is provided by the interpretation of the FKMM invariant from the viewpoint of the Bredon equivariant cohomology. This fact, along with basic results in equivariant homotopy theory, allows us to achieve the expected result.

Filtered simplicial homology, graph dissimilarity and überhomology

We introduce a filtration on the simplicial homology of a finite simplicial complex X using bi-colourings of its vertices. This yields two dual homology theories closely related to discrete Morse matchings on X. We give an explicit expression for the associated graded object of these homologies when X is the matching complex of the Tait graph of a plane graph G, in terms of subgraphs determined by certain matchings on the dual of G. We then use one of these homologies, in the case where X is a graph, to define a conjecturally optimal dissimilarity pseudometric for graphs; we prove various results for this dissimilarity and provide several computations. We further show that, by organising the horizontal homologies of a simplicial complex in the poset of its colourings, we obtain a triply graded homology theory which we call überhomology. This latter homology is not a homotopy invariant, but nonetheless encodes both combinatorial and topological information on X. For example, we prove that if X is a subdivision, the überhomology vanishes in its lowest degree, while for an homology manifold it coincides with the fundamental class in its top degree. We compute the überhomology on several classes of examples and infinite families and prove some of its properties; namely that, in its extremal degrees, it is well-behaved under coning and taking suspension. We then focus on the case where X is a simple graph and prove a detection result. Finally, we define some singly graded homologies for graphs obtained by specialising the überhomology in certain bi-degrees, provide some computations and use computer-aided calculations to make some conjectures.

The Fine-Grained Complexity of CFL Reachability

Many problems in static program analysis can be modeled as the context-free language (CFL) reachability problem on directed labeled graphs. The CFL reachability problem can be generally solved in time O ( n 3 ), where n is the number of vertices in the graph, with some specific cases that can be solved faster. In this work, we ask the following question: given a specific CFL, what is the exact exponent in the monomial of the running time? In other words, for which cases do we have linear, quadratic or cubic algorithms, and are there problems with intermediate runtimes? This question is inspired by recent efforts to classify classic problems in terms of their exact polynomial complexity, known as fine-grained complexity. Although recent efforts have shown some conditional lower bounds (mostly for the class of combinatorial algorithms), a general picture of the fine-grained complexity landscape for CFL reachability is missing. Our main contribution is lower bound results that pinpoint the exact running time of several classes of CFLs or specific CFLs under widely believed lower bound conjectures (e.g., Boolean Matrix Multiplication, k -Clique, APSP, 3SUM). We particularly focus on the family of Dyck- k languages (which are strings with well-matched parentheses), a fundamental class of CFL reachability problems. Remarkably, we are able to show a Ω( n 2.5 ) lower bound for Dyck-2 reachability, which to the best of our knowledge is the first super-quadratic lower bound that applies to all algorithms, and shows that CFL reachability is strictly harder that Boolean Matrix Multiplication. We also present new lower bounds for the case of sparse input graphs where the number of edges m is the input parameter, a common setting in the database literature. For this setting, we show a cubic lower bound for Andersen’s Pointer Analysis which significantly strengthens prior known results.

Hydrogenation of Carboxylic Acids, Esters, and Related Compounds over Heterogeneous Catalysts: A Step toward Sustainable and Carbon-Neutral Processes

The catalytic hydrogenation of esters and carboxylic acids represents a fundamental and important class of organic transformations, which is widely applied in energy, environmental, agricultural, and pharmaceutical industries. Due to the low reactivity of the carbonyl group in carboxylic acids and esters, this type of reaction is, however, rather challenging. Hence, specifically active catalysts are required to achieve a satisfactory yield. Nevertheless, in recent years, remarkable progress has been made on the development of catalysts for this type of reaction, especially heterogeneous catalysts, which are generally dominating in industry. Here in this review, we discuss the recent breakthroughs as well as milestone achievements for the hydrogenation of industrially important carboxylic acids and esters utilizing heterogeneous catalysts. In addition, related catalytic hydrogenations that are considered of importance for the development of cleaner energy technologies and a circular chemical industry will be discussed in detail. Special attention is paid to the insights into the structure-activity relationship, which will help the readers to develop rational design strategies for the synthesis of more efficient heterogeneous catalysts.

Optimizing Parallel Task Execution for Multi-Agent Mission Planning

Multi-agent systems have received a tremendous amount of attention in many areas of research and industry, especially in robotics and computer science. With the increased number of agents in missions, the problem of allocation of tasks to agents arose, and it is one of the most fundamental classes of problems in robotics, formally known as the Multi-Robot Task Allocation (MRTA) problem. MRTA encapsulates numerous problem dimensions, and it aims at providing formulations and solutions to various problem configurations, i.e., complex multi-agent missions. One dimension of the MRTA problem has not caught much of the research attention. In particular, problem configurations including Multi-Task (MT) robots have been neglected. However, the increase in computational power, in robotic systems, has allowed the utilization of parallel task execution. This in turn had the benefit of allowing the creation of more complex robotic missions; however, it came at the cost of increased problem complexity. Our contribution to the aforementioned domain can be grouped into three categories. First, we model the problem using two different approaches, Integer Linear Programming and Constraint Programming. With these models, we aim at filling the gap in the literature related to the formal definition of MT robot problem configuration. Second, we introduce the distinction between physical and virtual tasks and their mutual relationship in terms of parallel task execution. This distinction allows the modeling of a wider range of missions while exploiting possible parallel task execution. Finally, we provide a comprehensive performance analysis of both models, by implementing and validating them in CPLEX and CP Optimizer on the set of problems. Each problem consists of the same set of test instances gradually increasing in complexity, while the percentage of virtual tasks in each problem is different. The analysis of the results includes exploration of the scalability of both models and solvers, the effect of virtual tasks on the solvers’ performance, and overall solution quality.

Rising of Muslim Women in Colonial India: A Case Study of Mohtarma Fatima Jinnah

This qualitative study deals with the social and political status of 20th century colonial Muslim women under the British Raj. The 20th century has witnessed many symbols of the struggle and progress of females in their socio-political and professional life. Many movements were initiated by indigenous people to address the women question; a number of reforms took place to enhance women status by British government. As a result, women emerged as professional ladies and participated with men in every field of life. At that time with many prominent Muslim women Fatima Jinnah also steps forward to empower Muslim Women of colonial India. After the establishment of Pakistan, as Madr e Millet, she continued her services to give power to women in their professions and their political participation in newly established country. She also had to face criticism from fundamental class of Pakistan but she continued her struggle till her death. The hurdles and problems for women to participate in politics due to the patriarchal social structure still exist in present time, which need to be addressed by political and constitutional reforms.