Complex Functions Research Articles

PH-Controlled DNA Switching Circuits with Multi-State Responsiveness for Logic Computation and Control.

Dynamic control of DNA circuit functionality is essential for constructing chemical reaction networks (CRNs) that implement complex functions. The triplex has been utilized for dynamically regulating the diverse functionalities of DNA circuits due to its distinctive pH responsiveness. However, it is challenging for triplexes to independently regulate the functionality of DNA circuits, as various triplexes were often required for DNA circuits to function in complex environments, which adds complexity to the design and control of dynamic circuits. Here, we proposed a pH-controlled multi-state DNA switching circuit construction strategy to realize dynamic regulation among three states through conformational transitions of the triplex. In addition, by leveraging the regulatory role of multi-state DNA switching circuits on the toehold-mediated strand displacement reaction, we constructed switchable DNA circuits for logic computation and control of hybridization chain reaction (HCR). We confirmed that the designed DNA switching circuits exhibited multi-state responsiveness, allowing for different logical operations at varying pH levels and programmable control of the diverse reaction pathways in the HCR. Our strategy offers a convenient approach for the intelligent response and dynamic regulation of large-scale CRNs and DNA nanostructure self-assembly. It promises applications in biosensing, disease detection and drug delivery.

Genome-wide identification of the Sec14 gene family and the response to salt and drought stress in soybean (Glycine max)

BackgroundThe Sec14 domain is an ancient lipid-binding domain that evolved from yeast Sec14p and performs complex lipid-mediated regulatory functions in subcellular organelles and intracellular traffic. The Sec14 family is characterized by a highly conserved Sec14 domain, and is ubiquitously expressed in all eukaryotic cells and has diverse functions. However, the number and characteristics of Sec14 homologous genes in soybean, as well as their potential roles, remain understudied.ResultsIn this study, we identified 77 Sec14 genes in the soybean genome that were unevenly distributed across 19 chromosomes. Based on the classification method used for Arabidopsis Sec14 members, GmSec14s can be categorized into three classes: GmPITP1 to GmPITP37, GmSFH1 to GmSFH25, and GmPATL1 to GmPATL15. Structural analysis of the GmSec14 genes revealed that the SFH subfamily contained more introns than the other subfamilies. A total of 10 conserved protein motifs were detected within GmSec14 proteins, with each subfamily possessing unique motifs. Two tandem duplications and 73 segmental duplications were identified among the GmSec14 genes. Additionally, a large number of cis-acting elements, particularly those related to plant hormones, were abundant in the promoter regions of the GmSec14 genes. Tissue expression analysis of the GmSec14 genes indicated that they exhibited distinct tissue-specific expression patterns. In response to salt stress, multiple genes were found to be either upregulated or downregulated. In contrast, the majority of genes were downregulated under drought stress conditions. Notably, 12 GmSec14 genes exhibited significant alterations in expression following salt or drought stress, suggesting a potential role for these genes in stress response mechanisms. Furthermore, the protein interaction network and miRNA regulation associated with GmSec14s were predicted to elucidate the potential functions of GmSec14 members.ConclusionsThis study provides a systematic and comprehensive examination of the Sec14 gene family in soybean, which will facilitate further functional research into their roles in response to salt and drought tolerance.

Advances in biomaterials-based tissue engineering for regeneration of female reproductive tissues.

The anatomical components of the female reproductive system-comprising the ovaries, uterus, cervix, vagina, and fallopian tubes-interact intricately to provide the structural and hormonal support essential for reproduction. However, this system is susceptible to various detrimental factors, both congenital and acquired, that can impair fertility and adversely affect quality of life. Recent advances in bioengineering have led to the development of sophisticated three-dimensional (3D) models that mimic the complex architecture and functionality of reproductive organs. These models, incorporating diverse cell types and tissue layers, are crucial for understanding physiological processes within the reproductive tract. They offer insights into decidualization, ovulation, folliculogenesis, and the progression of reproductive cancers, thereby enhancing personalized medical treatments and addressing female infertility. This review highlights the pivotal role of tissue engineering in diagnosing and treating female infertility, emphasizing the importance of considering factors like biocompatibility, biomaterial selection, and mechanical properties in the design of bioengineered systems. The challenge of replicating the functionally specialized and structurally complex organs, such as the uterus and ovary, underscores the need for reliable techniques that improve morphological and functional restoration. Despite substantial progress, the goal of creating a fully artificial female reproductive system is still a challenge. Nonetheless, the recent fabrication of artificial ovaries, uteruses, cervixes, and vaginas marks significant advancements toward this aim. Looking forward, the challenges in bioengineering are expected to spur further innovations in both basic and applied sciences, potentially hastening the clinical adoption of these technologies.

Neutrophil Engulfment in Cancer: Friend or Foe?

Neutrophils, the most abundant circulating white blood cells, are essential for the initial immune response to infection and injury. Emerging research reveals a dualistic function of neutrophils in cancer, where they can promote or inhibit tumor progression. This dichotomy is influenced by the tumor microenvironment, with neutrophils capable of remodeling the extracellular matrix, promoting angiogenesis, or alternatively inducing cancer cell death and enhancing immune responses. An intriguing yet poorly understood aspect of neutrophil–cancer interactions is the phenomenon of neutrophil engulfment by cancer cells, which has been observed across various cancers. This process, potentially mediated by LC3-associated phagocytosis (LAP), raises questions about whether it serves as a mechanism for immune evasion or contributes to tumor cell death through pathways like ferroptosis. This review examines current knowledge on neutrophil development, their roles in cancer, and the mechanisms of LAP in neutrophil engulfment by tumor cells. We discuss how manipulating LAP impacts cancer progression and may represent a therapeutic strategy. We also explore neutrophils’ potential as delivery vehicles for cancer therapeutic agents. Understanding the complex functions of tumor-associated neutrophils (TANs) and the molecular mechanisms underlying LAP in cancer may open new avenues for effective therapeutic interventions and mitigate potential risks.

Single-cell chromatin accessibility landscape profiling reveals the diversity of epigenetic regulation in the rat nervous system

The mammalian nervous system controls complex functions through highly specialized and interacting structures. Single-cell sequencing can provide information on cell-type-specific chromatin structure and regulatory elements, revealing differences in chromatin organization between different cell types and their potential roles of these differences in brain function. Here, we generated a chromatin accessibility dataset through single-cell ATAC-seq of 174,593 high-quality nuclei from 16 adult rat brain regions. We identified cell subtypes of both neuronal and non-neuronal cells with highly specific distributions and characterized gene regulatory elements associated with cell type-specific regions. To further investigate the gene regulatory network involved in spinal cord regeneration, we integrated our scATAC-seq data with published single-nucleus RNA-seq data from the spinal cord, and we identified more detailed regeneration related elements by drawing GRNs centered on the transcription factor Jun in the OPC. We also performed similar integration analyses in the midbrain. Our findings provide a solid foundation for the comprehensive dissection of the molecular architecture of the mammalian nervous system.

High-stable multifunctional dynamically reconfigurable artificial synapses based on hybrid graphene/ferroelectric field-effect transistors

In response to the challenges posed by traditional computing architectures in handling big data and AI demands, neuromorphic computing has emerged as a promising alternative inspired by the brain's efficiency. This study focuses on three-terminal synaptic transistors utilizing graphene and P(VDF-TrFE) to achieve dynamic reconfigurability between excitatory and inhibitory response modes, which are crucial for mimicking biological functions. The devices operate by applying different top gate spikes (±25 V and ±10 V) to modulate the polarization degree of P(VDF-TrFE), thereby regulating the carrier type and concentration in the graphene channel. This results in the effective realization of enhancement and inhibition processes in two neural-like states: excitatory and inhibitory modes, accompanied by good neural plasticity with paired-pulse facilitation and spike-time-dependent plasticity. With these features, the synaptic devices achieve brain-like memory enhancement and human-like perception functions, exhibiting excellent stability, durability over 1000 cycles, and a long retention period exceeding 10 years. Additionally, the performance of the artificial neural network is evaluated for handwritten digit recognition, achieving a high recognition accuracy of 92.28%. Our study showcases the development of highly stable, dynamically reconfigurable artificial synaptic transistors capable of emulating complex neural functions, providing a foundation for emerging neuromorphic computing systems and AI technologies.

Повышение конкурентоспособности отечественного сельхозмашиностроения посредством управления рисками

The study of competitiveness and risk management issues is currently relevant for many industries and areas of functioning of the agro-industrial complex, including agricultural engineering. The article calculates the level of losses of agricultural engineering enterprises caused by the disparity of economic relations in the agro-industrial complex. Based on this, an assessment is given of the direct and reverse impact of local and industry risks on the functioning of agricultural engineering enterprises, which made it possible to develop a prototype of a risk management system at agricultural engineering enterprises. The study identified the prerequisites for the formation of a harmonious and effective organizational and economic mechanism for the functioning of agricultural engineering enterprises based on a set of scientific approaches. The authors developed a conceptual scheme of the risk management system at agricultural engineering enterprises. The study resulted in proposals for improving the instruments of state regulation of the risk management system of an enterprise in the industry.

MODE: A Web Application for Interactive Visualization and Exploration of Omics Data.

Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as "omics") data allow researchers to find biomarkers or molecular targets or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data are multidimensional, and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries do not allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to sort and filter plots by categorical or numerical variables called metas. MODE allows users to build and share these displays with several options for plot design and meta selection. The MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.

Dual-Mode ZnO/SnSe Heterojunction Devices with Integrated Bipolar Response Photodetectors and Artificial Optoelectronic Synapses for in-Sensor Computing.

Optoelectronic synapse devices (OESDs) inspired by human visual systems enable to integration of light sensing, memory, and computing functions, greatly promoting the development of in-sensor computing techniques. Herein, dual-mode integration of bipolar response photodetectors (PDs) and artificial optoelectronic synapses based on ZnO/SnSe heterojunctions are presented. The function of the fabricated device can be converted between the PDs and OESDs by modulating the light intensity. As a PD, the polarity of the output current can be switched by tuning the laser wavelength and intensity, which is attributed to the competition between the photovoltaic and photothermoelectric effects in the ZnO/SnSe heterojunction. As an OESD, the device exhibits versatile photonic synaptic characteristics at low light intensity based on the defect-dominant carrier trapping/de-trapping processes, including short/long-term plasticity and learning experience behaviors. More importantly, benefitting from the outstanding synaptic responses, logic functions including "AND" and "OR" are implemented through the in-sensor computing architecture. This work supplies a novel route to realize complex functionality in one device and offers effective strategies for developing in-sensor computing.

3D active-matrix multimodal sensor arrays for independent detection of pressure and temperature.

Pressure and temperature sensing simultaneously and independently is crucial for creating electronic skin that replicates complex sensory functions of human skin. Thin-film transistor (TFT) arrays with sensors have enabled cross-talk-free spatial sensing. However, the thermal dependence of charge transport in semiconductors has resulted in interference between thermal and pressure stimuli. We develop multimodal sensor arrays based on three-dimensional integration of an active matrix to detect temperature and pressure independently. Our approach includes a calibrated compensation to decouple temperature and pressure signals. An individual pixel device consists of a TFT-based pressure sensor layered above a TFT-based temperature sensor. The detected temperature is used to compensate for the thermal effect on TFT-based pressure sensors. We develop large-area sensor arrays to enable accurate detection of two-dimensional pressure and temperature, leveraging these technologies to demonstrate advanced robotic grippers. The grippers stably grasp and lift a cup regardless of temperature, proving their possibility in skin-like electronic applications.

Computational Reconstruction of the Volatility Term Structure in the General Hull–White Model

Volatility recovery is of paramount importance in contemporary finance. Volatility levels are heavily used in risk and portfolio management. We employ the Hull–White one- and two-factor models to describe the market condition. We computationally recover the volatility term structure as a piecewise-linear function of time. For every maturity, a cost functional, defined as the squared differences between theoretical and market prices, is minimized and the respective linear part is reconstructed. On the last time steps, before each maturity, the derivative price is decomposed in order to make the minimization problem analytically solvable. The procedure works fast since only scalar values are obtained on each minimization. However, the predictor–corrector nature of the algorithm allows for the precise recovery of very complex volatility functions. An implicit scheme is used to solve the PDEs on bounded domains. The computational simulations with artificial and real data show that the proposed algorithm is stable, accurate and efficient.

Lipocalin 2 in Obesity and Diabetes: Insights into Its Role in Energy Metabolism

Background: Lipocalin 2 (LCN2), also known as neutrophil gelatinase-associated lipocalin, is a 25 kDa protein involved in immune defense, inflammation, and metabolism. Results: LCN2 is widely expressed across various tissues, including immune cells, bone, adipose tissue, liver, kidneys, lung, spleen, and epithelial cells, and exhibits sex- and fat depot-specific expression patterns. Structurally, LCN2 contains a hydrophobic lipid-binding pocket and glycosylation sites, enabling it to interact with diverse ligands and form dimers. In innate immunity, LCN2 plays a critical role by sequestering iron-laden siderophores, thereby restricting bacterial growth. Beyond its role in infection control, LCN2 is implicated in metabolic inflammation and diseases such as obesity and diabetes. Recent research has highlighted a pivotal role for LCN2 in mitochondrial phospholipid metabolism and mitochondrial function. In metabolic diseases and mitochondrial metabolism, LCN2 appears to display paradoxical effects. While some studies link it to improved insulin sensitivity, glucose regulation, and mitochondrial function, others associate it with insulin resistance, obesity, and mitochondrial dysfunction. These inconsistencies may arise from differences in experimental conditions and study populations. Conclusions: This review provides an up-to-date summary of LCN2’s multifaceted roles in obesity, diabetes, energy balance, and mitochondrial function, emphasizing its context-dependent effects. LCN2 appears to have dual roles, exerting both protective and detrimental outcomes depending on the physiological or pathological context, sex, cell types, and experimental conditions. Further research is necessary to unravel its complex functions and resolve conflicting findings, particularly in metabolic disorders.

Ligands of CD6: roles in the pathogenesis and treatment of cancer.

Cluster of Differentiation 6 (CD6), an established marker of T cells, has multiple and complex functions in regulation of T cell activation and proliferation, and in adhesion of T cells to antigen-presenting cells and epithelial cells in various organs and tissues. Early studies on CD6 demonstrated its role in mediating cell-cell interactions through its first ligand to be identified, CD166/ALCAM. The observation of CD6-dependent functions of T cells that could not be explained by interactions with CD166/ALCAM led to discovery of a second ligand, CD318/CDCP1. An additional cell surface molecule (CD44) is being studied as a potential third ligand of CD6. CD166, CD318, and CD44 are widely expressed by both differentiated cancer cells and cancer stem-like cells, and the level of their expression generally correlates with poor prognosis and increased metastatic potential. Therefore, there has been an increased focus on understanding how CD6 interacts with its ligands in the context of cancer biology and cancer immunotherapy. In this review, we assess the roles of these CD6 ligands in both the pathogenesis and treatment of cancer.

Nucleophilic Functionalization of a Cationic Pentaphosphole Complex-A Systematic Study of Reactivity.

The systematic nucleophilic functionalization of the cationic pentaphosphole ligand complex [Cp*Fe(η4-P5Me)][OTf] (A) with group 16/17 nucleophiles is reported. This method represents a highly reliable and versatile strategy for the design of novel transition-metal complexes featuring twofold substituted end-deck cyclo-P5 ligands, bearing unprecedented hetero-element substituents. By the reaction of A with classical group 16 nucleophiles, complexes of the type [Cp*Fe(η4-P5MeE)] (E=OEt (1), OtBu (2), SPh (3), SePh (4)) are obtained. By transferring this protocol to group 17 nucleophiles, the highly sensitive complexes [Cp*FeP5(η4-P5MeX)] (X=F (5), Cl (6), Br (7), I (8)) could be isolated. All products show exclusively 1,1'-substitution at the cyclo-P5 ring. Interestingly, further studies on the reactivity of the halogenated species revealed their ability to undergo ring-opening reactions with cyclic ethers such as THF and ethylene oxide yielding [Cp*FeP5(η4-P5MeOC4H8X)] (X=Br (9), I (10)) or [Cp*FeP5(η4-P5MeOC2H4X)] (X=Br (11), I (12)), respectively. Furthermore, the use of acyclic ethers such as dimethoxyethane led to the formation of [Cp*FeP5(η4-P5MeOC2H4OCH3)] (13) mediated by C-O bond cleavage, followed by subsequent P-O bond formation, as further enlightened by DFT calculations.

Automated polynomial formal verification using generalized binary decision diagram patterns.

With the ongoing digitization, digital circuits have become increasingly present in everyday life. However, as circuits can be faulty, their verification poses a challenging but essential challenge. In contrast to formal verification techniques, simulation techniques fail to fully guarantee the correctness of a circuit. However, due to the exponential complexity of the verification problem, formal verification can fail due to time or space constraints. To overcome this challenge, recently Polynomial Formal Verification (PFV) has been introduced. Here, it has been shown that several circuits and circuit classes can be formally verified in polynomial time and space. In general, these proofs have to be conducted manually, requiring a lot of time. However, in recent research, a method for automated PFV has been proposed, where a proof engine automatically generates human-readable proofs that show the polynomial size of a Binary Decision Diagram (BDD) for a given function. The engine analyses the BDD and finds a pattern, which is then proven by induction. In this article, we formalize the previously presented BDD patterns and propose algorithms for the pattern detection, establishing new possibilities for the automated proof generation for more complex functions. Furthermore, we show an exemplary proof that can be generated using the presented methods.This article is part of the theme issue 'Emerging technologies for future secure computing platforms'.

Association between diffusion tensor imaging measurements and cognitive performances in people with multiple sclerosis: A systematic review and meta-analysis.

Alterations in structural connectivity of brain networks have been linked to complex cognitive functions in people with multiple sclerosis (PwMS). However, a definitive consensus on the optimal diffusion tensor imaging (DTI) markers as indicators of cognitive performance remains incomplete and inconclusive. This systematic review and meta-analysis aimed to explore the evidence on the correlation between DTI metrics and cognitive functions in PwMS. A comprehensive literature search was conducted across PubMed/MEDLINE, Embase, Scopus, and the Web of Science up to March 2024 to identify studies reporting the correlation between DTI metrics and cognitive functions. Cognitive function was assessed using the Symbol Digit Modalities Test (SDMT), California Verbal Learning Test (CVLT), and Brief Visuospatial Memory Test-Revised (BVMT-R). The pooled correlation coefficients were estimated using R software version 4.4.0 with the random effect model. Out of 1952 studies, 38 studies on 2055 PwMS fulfilled the inclusion criteria. The meta-analysis indicated that the SDMT exhibited the greatest correlation with corpus callosum fractional anisotropy (FA) (r = 0.54, 95 % CI: 0.4 to 0.66, p-value < 0.001, I2 = 34.1 %, p-heterogeneity = 0.19) and mean diffusivity (MD) (r = -0.48, 95 % CI: 0.61 to -0.33, p-value < 0.001, I2 = 0 %, p-heterogeneity = 0.77), white matter FA (r = 0.39, 95 % CI: 0.24 to 0.52, p-value < 0.001, I2 = 0 %, p-heterogeneity = 0.1), and fornix FA (r = 0.35, 95 % CI: 0.12 to 0.54, p-value = 0.003, I2 = 50.7 %, p-heterogeneity = 0.18) and MD (r = -0.35, 95 % CI: 0.49 to -0.19, p-value < 0.001, I2 = 0 %, p-heterogeneity = 0.5). DTI measurements, including corpus callosum FA and MD, white matter FA, and fornix FA and MD, represent the indicators of cognitive performance in PwMS. Nonetheless, these findings warrant cautious interpretation due to the restricted kinds of cognitive tests and methodological variability across studies.

4D-printed programmable sample-/eluent-actuated solid-phase extraction device for trace metal analysis.

To integrate valves, manifolds, and solid-phase extraction (SPE) columns into a compact device is technically difficult. Four-dimensional printing (4DP) technologies, employing stimuli-responsive materials in three-dimensional printing (3DP), are revolutionizing the fabrication, functionality, and applicability of stimuli-responsive analytical devices that can show time-dependent shape programming to enable more complex geometric designs and functions. However, 4D-printed stimuli-responsive actuators and valves utilized to control flowing streams in SPE applications remain rare. The tunable stimuli-responsive 4D-printed flow control actuators and valves with the capability of the programmable actuation can be used to manipulate flowing streams and simplify the automation of a conventional SPE scheme. We employed digital light processing three-dimensional printing (3DP), bisphenol A ethoxylate dimethacrylate-based photocurable resins, and 2-carboxyethyl acrylate (CEA)-incorporated flexible photocurable resins to fabricate an SPE column positioned between two [H+]-responsive flow-actuated needle valves. The two valves sequentially close after loading an alkaline sample (pH>pKa of CEA) due to swelling of the stem. Subsequently, they sequentially open upon loading an acidic eluent (pH<pKa of CEA; deswelling of the stem). The optimized device enabled a semi-automatic SPE scheme for Mn, Co, Ni, Cu, Zn, Cd, and Pb ions and showed competitive performance when coupled with inductively coupled plasma mass spectrometry-with the method detection limits ranging from 0.5 to 5.9ngL-1. We validated the reliability and applicability of this method by analyzing the metal ions in reference materials (CASS-4, SLRS-5, 1643f, and Trace Elements Urine L-2) and spike analyses of natural water and human urine samples. To the best of our knowledge, our device is the first demonstration of an SPE scheme performed by the programmable actuation of 4D-printed stimuli-responsive flow control valves, highlighting the analytical applicability of the tunable stimuli-responsive 4D-printed parts and the promising capability of 4DP technologies in advancing conventional sample pretreatment devices.

IDH-mutant glioma risk stratification via whole slide images: Identifying pathological feature associations.

This article aims to develop and validate a pathological prognostic model for predicting prognosis in patients with isocitrate dehydrogenase (IDH)-mutant gliomas and reveal the biological underpinning of the prognostic pathological features. The pathomic model was constructed based on whole slide images (WSIs) from a training set (N= 486) and evaluated on internal validation set (N= 209), HPPH validation set (N= 54), and TCGA validation set (N= 352). Biological implications of PathScore and individual pathomic features were identified by pathogenomics set (N= 100). The WSI-based pathological signature was an independent prognostic factor. Incorporating the pathological features into a clinical model resulted in a pathological-clinical model that predicted survival better than either the pathological model or clinical model alone. Ten categories of pathways (metabolism, proliferation, immunity, DNA damage response, disease, migrate, protein modification, synapse, transcription and translation, and complex cellular functions) were significantly correlated with the WSI-based pathological features.

View from above: Farmland infrastructure and its impacts on agricultural landscapes

&lt;p&gt;Agricultural landscapes are shaped by the interaction between natural elements and human activities. The development of farmland infrastructure has directly added man-made objects or indirectly altered the production capacity, thereby impacting these landscapes. Earth Observation (EO), primarily satellite imagery, plays a crucial role in observing and monitoring the Earth’s surface and provides a valuable tool for understanding the pattern and structure of agricultural landscapes by offering information on land cover types. However, due to the varied and complex types, shapes, sizes, and functionalities of farmland infrastructure, the approaches and methods for observing its characteristics are limited. This limitation further obstructs the understanding of its impacts on agricultural landscapes. In this paper, we summarize the challenges and opportunities in exploring farmland infrastructure using EO and aim to comprehensively understand the interaction between natural elements and human activities in shaping agricultural landscapes.&lt;/p&gt;

Interactive infill topology optimisation guided by user drawn patterns

ABSTRACT Widespread use of topology optimisation as a design tool for additive manufacturing faces major inhibiting obstacles, such as high computational costs and complexity, concern for other failure modes, and manufacturability. Interactive infill topology optimisation presents an alternative approach to circumvent some of these barriers. The novel contribution of the present work prompts the user to draw a tailored infill pattern, specify regions of interest to locate the infill, and control how strictly the pattern is replicated in the material layout of the design using appearance constraints. This approach improves engineering metrics not directly included in the optimisation formulation by incorporating the user’s engineering experience, thereby avoiding increased computational costs, parameter tuning, and numerical artifacts associated with complex objective functions and constraints. Two 2D benchmark examples increase the linear buckling resistance and energy absorption, respectively, and a 2.5D example minimises compliance while reducing the quantity of overhang supports for additive manufacturing.