Distinct Properties Research Articles

Correlation-driven multi-level learning for anomaly detection on multiple energy sources

Advanced metering infrastructure (AMI) has been widely used as an intelligent energy consumption measurement system. Electric power was the representative energy source collected by AMI; most existing studies to detect abnormal energy consumption have focused on a single energy source, i.e., power. Recently, other energy sources such as water, gas, and heating have also been actively collected. As a result, it is necessary to develop a unified methodology for anomaly detection across multiple energy sources; however, research efforts have rarely been made to tackle this issue. In this study, we propose a new correlation-driven multi-level learning model for anomaly detection on multiple energy sources. The distinguishing property of the model incorporates multiple energy sources in multi-levels based on the strength of the correlations between them. Our model is scalable to integrate arbitrary new energy sources, with further performance improvement, considering both correlated and non-correlated sources. Through extensive experiments on real-world datasets consisting of three to five energy sources, we demonstrate that the proposed model clearly outperforms the existing multimodal learning and recent time-series anomaly detection models and makes further performance improvement as more energy sources are integrated, showing the scalability of the proposed model.

Eight-Electron Copper Nanoclusters for Photothermal Conversion.

Owing to distinct physicochemical properties in comparison to gold and silver counterparts, atomically precise copper nanoclusters are attracting embryonic interest in material science. The introduction of copper cluster nanomaterials in more interesting fields is currently urgent and desired. Reported in this work are novel copper nanoclusters of [XCu54Cl12(tBuS)20(NO3)12] (X=S or none, tBuSH=2-methyl-2-propanethiol), which exhibit high performance in photothermal conversion. The clusters have been prepared in one pot and characterized by combinatorial techniques including ultraviolet-visible spectroscopy (UV-vis), electrospray ionization mass spectrometry (ESI-MS), and X-ray photoelectron spectroscopy (XPS). The molecular structure of the clusters, as revealed by single crystal X-ray diffraction analysis (SCXRD), shows the concentric three-shell Russian doll arrangement of X@Cu14@Cl12@Cu40. Interestingly, the [SCu54Cl12(tBuS)20(NO3)12] cluster contains 8 free valence electrons in its structure, making it the first eight-electron copper nanocluster stabilized by thiolates. More impressively, the clusters possess an effective photothermal conversion (temperature increases by 71 °C within ~50 s, λex=445 nm, 0.5 W cm-2) in a wide wavelength range (either blue or near-infrared). The photothermal conversion can be even driven under irradiation of simulated sunlight (3 sun), endowing the clusters with great potency in solar energy utilization.

Dynamic-Linearization-Based Predictive Control of a Voltage-Source Inverter

In pursuit of accurate and fast trajectory tracking of power converters, an explicit model is commonly used in the finite control-set model predictive control (FCS-MPC) framework to predict precise behaviors of controlled variables. In reality, however, the model mismatch is inevitable, which causes the inherent challenges of parameter sensitivity and model uncertainties of the FCS-MPC method. This article proposes a dynamic-linearization-based predictive control architecture to circumvent such model dependence while keeping the attractive features of the conventional FCS-MPC method. By integrating the data-driven feature of the dynamic-linearization approach, the detailed model used in the FCS-MPC controller is replaced by a virtual equivalent data model, creating a data-driven predictive control architecture. The suggested method selects optimal control action solely based on the input-output data, exhibiting strong rejection against parameter variations whilst inheriting the distinctive property of the conventional FCS-MPC method. Finally, the proposed design is validated through comparative simulation and experimental results on a three-level neutral-point-clamped inverter.

Holistic-Guided Disentangled Learning With Cross-Video Semantics Mining for Concurrent First-Person and Third-Person Activity Recognition.

The popularity of wearable devices has increased the demands for the research on first-person activity recognition. However, most of the current first-person activity datasets are built based on the assumption that only the human-object interaction (HOI) activities, performed by the camera-wearer, are captured in the field of view. Since humans live in complicated scenarios, in addition to the first-person activities, it is likely that third-person activities performed by other people also appear. Analyzing and recognizing these two types of activities simultaneously occurring in a scene is important for the camera-wearer to understand the surrounding environments. To facilitate the research on concurrent first- and third-person activity recognition (CFT-AR), we first created a new activity dataset, namely PolyU concurrent first- and third-person (CFT) Daily, which exhibits distinct properties and challenges, compared with previous activity datasets. Since temporal asynchronism and appearance gap usually exist between the first- and third-person activities, it is crucial to learn robust representations from all the activity-related spatio-temporal positions. Thus, we explore both holistic scene-level and local instance-level (person-level) features to provide comprehensive and discriminative patterns for recognizing both first- and third-person activities. On the one hand, the holistic scene-level features are extracted by a 3-D convolutional neural network, which is trained to mine shared and sample-unique semantics between video pairs, via two well-designed attention-based modules and a self-knowledge distillation (SKD) strategy. On the other hand, we further leverage the extracted holistic features to guide the learning of instance-level features in a disentangled fashion, which aims to discover both spatially conspicuous patterns and temporally varied, yet critical, cues. Experimental results on the PolyU CFT Daily dataset validate that our method achieves the state-of-the-art performance.

Enhanced electromagnetic wave absorption in YAG-modified SiC foam

Electromagnetic technology applications are escalating, leading to increased human exposure to electromagnetic radiation. In addressing the challenges posed by this radiation, electromagnetic wave absorbing materials stand out due to their distinguished properties. This study focused on developing porous fibrous SiC three-dimensional (3D) foams. These were synthesized by freeze-drying SiC nanofiber dispersions followed by high-temperature sintering. Measurements demonstrated that the resulting SiC foams possess a relatively low density, approximating 0.1 g cm−3. Upon microscopic analysis, it became evident that the foam's porous structure is predominantly made up of SiC fibers intermixed with yttrium aluminum garnet granules. These tailored SiC foams delivered outstanding electromagnetic wave absorption characteristics, recording a minimum reflection loss value of −63 dB. Furthermore, an expansive effective absorption bandwidth of 6.9 GHz (spanning from 9.3 to 16.2 GHz) was noted for a sample thickness of 3.15 mm. Several factors contribute to this high absorption efficacy, including multiple reflections and both interface and dipole polarizations. It is also worth noting that the SiC foam displayed commendable oxidation resistance when exposed to elevated temperatures. Cumulatively, these findings underscore the promising potential of porous fibrous SiC 3D foams in electromagnetic wave absorption applications, especially in extreme conditions.

Abelian combinatorial gauge symmetry

Combinatorial gauge symmetry is a principle that allows us to construct lattice gauge theories with two key and distinguishing properties: a) only one- and two-body interactions are needed; and b) the symmetry is exact rather than emergent in an effective or perturbative limit. The ground state exhibits topological order for a range of parameters. This paper is a generalization of the construction to any finite Abelian group. In addition to the general mathematical construction, we present a physical implementation in superconducting wire arrays, which offers a route to the experimental realization of lattice gauge theories with static Hamiltonians.

Measuring Housing Inequality with the Value of Freedom in the Capability Approach: Proposal and Demonstration

ABSTRACT An ongoing question in capability research is how to incorporate the value of freedom into the measurement of inequality. This article proposes an approach to answering this question in the housing domain and its operationalisation. The approach places an evaluation focus to the conditions constraining or expanding housing choices in the dimensions of opportunity, security, and ability. For operationalisation, the study designed a measurement of multidimensional housing disadvantages (MHDs) using the Alkire-Foster method and data from the Netherlands. Indicators include the entitlement to housing tenure options, vulnerability in housing cost payments, and ability to plan finance for housing. The measurement outcome demonstrates that the MHDs measurement can provide information on whose housing choices are more intensely constrained, thus having a lower capability for housing, and whose current housing situation is likely a result of coerced choices. The findings indicate that adults living with housemates or family (latent households), youths, and those with precarious jobs have a significantly lower capability for housing compared to other population groups. This article also compares the freedom-oriented measure of MHDs with functioning-oriented and other conventional measures and discusses its distinguishing properties. This comparison suggests a need to revisit current policy priorities in addressing housing inequality.

Abstract 5072: Multi-omic, multi-scale characterisation of colorectal cancer defines spatiotemporal patterns of recurrence

Abstract Aim: Patients who undergo intended curative resection of colorectal cancer (CRC) have a 20-25% chance of metachronous recurrence, the site and timing of which are unpredictable and resistant to current treatment. The biological basis for such heterogeneous disease behavior remains to be elucidated. Bulk transcriptomic profiling and subsequently single-cell RNAseq have provided insight in the epithelial subtypes and immune microenvironment. Recently spatially resolved transcriptomic assessment allow molecular profiling of tissue while preserving tissue architecture. Utilizing ST technology we sought to perform deep characterization of a large cohort of patients with primary CRC with the intention to decipher the biological determinants of spatio-temporal patterns of recurrence. Methods: 750 patients who underwent resection of CRC with mature follow up were studied. Bulk transcriptomic, genomic and multiplex immune characterization was performed using a TMA format. Of these, 28 patients were assessed using single cell spatial transcriptomics (Nanostring CosMx Spatial Molecular Imager (SMI, 1000plex gene panel)), 120 tumors underwent regional whole transcriptome profiling of epithelium and TME (Nanostring GeoMx Digital Spatial Profiler using FFPE tissue). We used image analysis and bioinformatics to integrate these complex datasets in over 120000 single-cells in the context of their spatial tissue architecture and clinicopatholgical outcome and recurrence data. Results: Using the CosMx SMI we characterized cells with complete topographic detail and defined 2 unique epithelial cell states defined. Each epithelial state had distinct spatial properties including cell size and morphology, average distance to nearest lymphocyte, neighboring cell types and stromal neighborhood. This epithelial signature was integrated in GeoMx samples and were found to predict recurrence (p<0.05). The Epithelial, Fibroblast and Immune GeoMx transcriptomic compartments were expanded and grouped using unsupervised clustering. Each compartment demonstrated groups of patients where specific spatially derived signatures could predict site and time of recurrence (p<0.05). Conclusions: By maintaining the tissue structure, we have directly measured cellular interactions and captured cells commonly missed during dissociative studies whilst defining novel molecular subtypes of CRC with clinical relevance. Novel platforms such as CosMx allow deeper characterization of unique cell types and cellular interactions that may pave the way for novel therapeutics and precision medicine for patients with CRC. Citation Format: Colin Stuart Wood, Joao Da Silva Filho, Andrew Cameron, Assya Legrini, Holly Leslie, Tengyu Zhang, Yoana Doncheva, Claire Kennedy-Dietrich, Matthias Marti, Joanne Edwards, Paul Horgan, Campbell Roxburgh, Colin Steele, Nigel Jamieson. Multi-omic, multi-scale characterisation of colorectal cancer defines spatiotemporal patterns of recurrence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5072.

Effects of PLA-Type and Reinforcement Content on the Mechanical Behavior of Additively Manufactured Continuous Ramie Fiber-Filled Biocomposites

The present work aimed to examine the tensile and flexural behaviors of biocomposites reinforced with continuous plant fibers, utilizing a range of polylactic acid (PLA) matrix materials and varying fiber content. These biocomposites were fabricated using an in situ-impregnated fused filament fabrication (FFF) technique. The study incorporated three different PLA matrix materials, namely PLA, PLA-Matte (PLA-Ma), and PLA-ST, each with distinct mechanical properties. The effect of different linear densities of continuous ramie yarns on the biocomposites was also investigated. The results show that adding continuous ramie yarn significantly enhances both the tensile and flexural strengths, as well as the modulus, of the matrixes. Furthermore, there was a positive correlation between the content of ramie yarn and the increases in strength and modulus. Moreover, the introduction of ramie yarns altered the fracture behavior of the biocomposites, shifting towards brittle fracture. This change significantly impacted the fracture toughness of the matrixes and resulted in a convergence of elongation at the point of breakage.

Abstract 1909: Advancing a novel tubulin-inhibitor ADC technology: The Adcentrx auristatin platform offers enhanced efficacy and safety profiles compared to vedotin technology

Abstract Auristatins represent an important class of anti-mitotic antibody-drug conjugate (ADC) payloads with potent cytotoxic effects on rapidly dividing cancer cells. Most notably, monomethyl auristatin E (MMAE) stands as the most extensively validated compound, laying the foundation for the vcMMAE (vedotin) linker-payload technology that has contributed to the approval of several ADCs, including brentuximab vedotin, polatuzumab vedotin-piiq, tisotumab vedotin-tftv, and enfortumab vedotin-ejfv. However, while these first-generation ADCs have paved the way for a paradigm shift in cancer treatment away from traditional chemotherapy, there remains a discernible opportunity for improvement in both efficacy and safety. In this context, we introduce the Adcentrx auristatin platform, which substantially expands the therapeutic window of auristatin-ADCs beyond the vedotin technology. Through systematic exploration, we have synthesized >100 proprietary auristatin analogues with a range of distinctive properties. We identified optimized linker-payloads by strategically pairing lead payload candidates with our proprietary i-ConjugationTM, an irreversible, stable cysteine conjugation technology, and fine-tuned linkers. The resulting ADCs with a drug-to-antibody ratio (DAR) of 8 were extremely hydrophilic with excellent in vivo pharmacokinetics, and sustained DAR retention for a period of 21-days. Comparative assessments against vedotin-ADCs revealed that Adcentrx-ADCs demonstrated superior efficacy across multiple targets and indications in various mouse xenograft models. In Sprague-Dawley rats, Adcentrx-ADCs exhibited remarkable tolerability, albeit their high drug loading of 8. In summary, our preclinical studies underscore the significant enhancement in the therapeutic index achieved by the Adcentrx auristatin platform. Furthermore, this technology presents a promising alternative mode of action to camptothecins, exhibiting tolerance to targets expressed in non-proliferative normal tissues but without the burden of severe dose-limiting toxicities such as interstitial lung disease. Citation Format: Dong Jun Lee, Sabine Rottmann, Anna Wang, Peter P. Challita, Andrew M. Hau, Wes Sisson, Mario M. Kuo, Kris Zhang, Monica Leung, Alexis Mahloch, Erin Nye, Paul Datta, Sam Janssen, Felipe Acosta, Oscar Betancourt, Maria Shahmoradgoli, Alexander Chu-Kung, MaoJun Guo, Pia M. Challita-Eid, Hui Li. Advancing a novel tubulin-inhibitor ADC technology: The Adcentrx auristatin platform offers enhanced efficacy and safety profiles compared to vedotin technology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1909.

Photon-counting CT of degenerative changes and rupture of silicone breast implants: a pilot study

BackgroundAccurate assessment of breast implants is important for appropriate clinical management. We evaluated silicone properties and diagnostic accuracy for characterizing silicone implants and detecting degenerative changes including rupture in photon-counting computed tomography (PCCT).MethodsOver 16 months, we prospectively included patients with silicone implants and available breast magnetic resonance imaging (MRI) who received thoracic PCCT performed in prone position. Consensus reading of all available imaging studies including MRI served as reference standard. Two readers evaluated all implants in PCCT reconstructions for degenerative changes. In a subgroup of implants, mean density of silicone, adjacent muscle, and fat were measured on PCCT reconstructions. Contrast-to-noise ratios (CNRs) were calculated for implant-to-muscle and implant-to-fat.ResultsAmong 21 subjects, aged 60 ± 13.1 years (mean ± standard deviation) with 29 implants PCCT showed the following: high accuracy for linguine sign, intraimplant fluid (all > 0.99), peri-implant silicone (0.95), keyhole sign (0.90), and folds of the membrane (0.81); high specificity for linguine sign, intraimplant fluid, keyhole sign, folds of the membrane (all > 0.99), and peri-implant silicone (0.98); and high sensitivity for linguine sign and intraimplant fluid (all > 0.99). In a subgroup of 12 implants, the highest CNR for implant-to-muscle was observed on virtual unenhanced reconstructions (20.9) and iodine maps (22.9), for implant-to-fat on iodine maps (27.7) and monoenergetic reconstructions (31.8).ConclusionsOur findings demonstrate that silicone breast implants exhibit distinct contrast properties at PCCT, which may provide incremental information for detection of degenerative changes and rupture of implants.Relevance statementThoracic photon-counting computed tomography is a promising modality for the diagnostic assessment of silicone breast implants.Key points• Thoracic photon-counting computed tomography demonstrates unique contrast properties of silicone breast implants.• Iodine map reconstructions reveal strong contrast-to-noise ratios for implant-to-muscle and implant-to-fat.• Thoracic photon-counting computed tomography shows high diagnostic accuracy in detecting implant degeneration and rupture.Trial registrationGerman Clinical Trials Register number DRKS00028997, date of registration 2022–08-08, retrospectively registered.Graphical

Influence of deposition potential and substrate characteristics on the photovoltaic conversion efficiency of p-SnS absorbing layers

In this study, thin films of tin sulfide (SnS) deposited on indium-doped tin oxide (ITO) and fluorine-doped tin oxide (FTO) substrates using Sn-S electrodeposition were systematically investigated. Notably, a novel non-toxic sulfur precursor was employed, emphasizing its role in ensuring the safety and environmental friendliness of the synthesis process. The research was focused on the influence of deposition potential and substrate type on the physical properties of SnS films. X-ray diffraction (XRD) analysis disclosed distinct peaks corresponding to orthorhombic SnS phase planes (101), (111), and (040). Scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDX) revealed a uniform distribution of essential components, particularly notable at −0.7 V on ITO and −0.9 V on FTO substrates. Raman spectroscopy identified characteristic peaks at 90 cm−1 and 222 cm−1. UV–visible spectrophotometry highlighted alterations in the optical band gap of SnS films on ITO (1.93 eV to 1.57 eV) and FTO (2.13 eV to 1.98 eV). Mott-Schottky analysis revealed consistent p-type conductivity behavior in the SnS layer, while both ITO and FTO layers exhibited n-type conductivity behavior. This characterization underscores the distinct electronic properties of each layer, providing valuable insights for the development of advanced optoelectronic devices. Electrochemical Impedance Spectroscopy (EIS) results demonstrated a significant reduction in charge transfer resistance (Rct) of SnS films on ITO at −0.7 V. The solar cell efficiency of the SnS absorber layer reached 2.2% on ITO at −0.7 V, contrasting with 1.47% on FTO at −0.9 V.

Boron Complexes of Tridentate Acyl Pyridylhydrazones

AbstractSince the development of the chemistry and applications of boron dipyrromethene dyes (BODIPYs), numerous other platforms based on boron complexes of N‐donor ligands have emerged as molecular optoelectronic materials. By tailoring the structure of the ligand bound to boron, the optical and electronic properties of a compound can be precisely tuned for unique properties, such as aggregation‐induced emission (AIE) in the case of boron difluoride hydrazones (BODIHYs). We examine the impact of modifying the typical bidentate hydrazone ligand structure used to prepare BODIHYs to enable a tridentate coordination mode to produce boron complexes of tridentate acyl pyridylhydrazones. This change allows for the use of arylboronic acids as sources of boron and facilitates the inclusion of complex organic components at the boron centre, including the formation of dye‐dye conjugates. The synthesized compounds exhibit distinct optical and electronic properties when compared to BODIHYs, such as reversible electrochemical reduction and up to a >300 nm pseudo‐Stokes shift in the solid state, all of which were supported by density functional theory calculations.

Coordination‐mediated atomic metal catalysts for cascaded transformation of β‐O‐4 dimeric model compound into quinoline

AbstractHere, we report the fabrication of atomic‐metal catalysts for the facile cascaded transformation of lignin β‐O‐4 dimeric model compound into quinoline. A series of dual‐metal single‐atom (SA) moieties (MaC4 and Mb2N6, where Ma and Mb represent two different metal SAs, C and N represent carbon and nitrogen atoms, respectively) are integrated on N‐doped carbons with designed compositions and coordination configurations. Characterizations indicate the homogeneous distribution of uniform and modifiable SA sites, over which the electron distribution is significantly polarized due to synergistic interactions. The distinctive physicochemical properties of catalysts afford attractive performances in the cascaded synthesis of quinoline from lignin β‐O‐4 dimeric model compound through cascaded transformation. In a continuous flow instrument, CuC4/Co2N6@NC furnishes 93.7% yield of 2‐phenylquinoline with a space‐time yield of 75.7 g gcat h−1. Control experiments and density functional theory calculations reveal the synergistic interactions between CuC4 and Co2N6 endow the catalyst with high efficiency in cascaded transformation.

Luminescent Properties Variation Caused by Metal Cations Effect on the Deep Energy Levels in Cu(I) and Ag(I) Complexes

AbstractIn this work, a donor‐acceptor (D‐A) type ligand is prepared to construct Cu(I) and Ag(I) complexes. These complexes possess similar molecular structures, distributions of molecular orbitals, and distributions of electrons and holes in excited states. However, they exhibit distinct photophysical properties, such as luminescent spectra and transient photo‐luminescent decay spectra. Through analysis of deep‐lying molecular orbitals in a tetrahedral field, it is determined that the variation in d‐p π conjugation between the metal cation's d‐orbitals and the π orbitals of the electron‐acceptor part of the D‐A ligand is the reason for the different photophysical properties. This research contributes to an in‐depth understanding of the role of metal ions in luminescent complexes, providing insights from the perspective of coordination chemistry.

Topological domain characteristics during the transition from ferroelectric to antiferroelectric in hexagonal manganites

Hexagonal manganites can exhibit the low-symmetry ferroelectric (FE) P63cm and partially undistorted anti-ferroelectric (PUA) P-3c1 states. The two states are accompanied by distinct sixfold vortex domain structures. The transition from the FE P63cm and PUA P-3c1 states (FE-PUA transition) is an effective means to control domain structures with distinct FE properties, which is of rich physical properties and potential applications. The FE-PUA transition can only be achieved by doping Ga on the Mn site of InMnO3, but the actual transition path and the associated domain structure evolution are still unclear. Namely, whether this transition goes through an intermediate P3c1 state remains an issue. In this work, we start from the Landau phenomenological theory to investigate the FE-PUA transition by directly tracking the domain structure evolution. The emerging 12-fold vortex domain structure at the intermediate stage of this transition indicates that this transition is not direct, and its actual path follows the P63cm → P3c1 → P-3c1 sequence, demonstrating the essential role of the intermediate P3c1 state. Besides, a pinning effect as a by-product is also discussed. This work comprehensively illustrates the characteristics of domain structure evolution during the FE-PUA transition, refining our understanding of the whole phase transition and topological physics associated with vortex domain structures in hexagonal manganites.

Quantitative evaluation of gut microbiota composition in pancreatic cancer: A pooled study.

Prior research has demonstrated a positive association between the composition of gut microbiota and the incidence of pancreatic cancer. Nevertheless, a thorough quantitative and systematic evaluation of the distinct properties of gut microbiota in individuals diagnosed with pancreatic cancer has yet to be conducted. The objective of this study is to examine alterations in the diversity of intestinal microbiota in individuals diagnosed with pancreatic cancer. Search for relevant literature published before July 2023 in 4 databases: PubMed, Embase, Web of Science, and Cochrane Library, without any language restrictions. A total of 12 studies were included, including 535 patients with pancreatic cancer and 677 healthy controls. Analysis was conducted on 6 phyla, 16 genera, and 6 species. The study found significant and distinctive changes in the α-diversity of gut microbiota, as well as in the relative abundance of multiple gut bacterial groups at the phylum, genus, and species levels in pancreatic cancer patients. Overall, there are certain characteristic changes in the gut microbiota of pancreatic cancer patients. However, further research is warranted to elucidate the specific mechanism of action and the potential for treatment.

Climatic zoning of yerba mate and climate change projections: a CMIP6 approach.

Yerba mate (Ilex paraguariensis) is renowned for its nutritional and pharmaceutical attributes. A staple in South American (SA) culture, it serves as the foundation for several traditional beverages. Significantly, the pharmaceutical domain has secured numerous patents associated with this plant's distinctive properties. This research delves into the climatic influence on yerba mate by leveraging the CMIP6 model projections to assess potential shifts brought about by climate change. Given its economic and socio-cultural significance, comprehending how climate change might sway yerba mate's production and distribution is pivotal. The CMIP6 model offers insights into future conditions, pinpointing areas that are either conducive or adverse for yerba mate cultivation. Our findings will be instrumental in crafting adaptive and mitigative strategies, thereby directing sustainable production planning for yerba mate. The core objective of this study was to highlight zones optimal for Ilex paraguariensis cultivation across its major producers: Brazil, Argentina, Paraguay, and Uruguay, under CMIP6's climate change forecasts. Our investigation encompassed major producing zones spanning the North, Northeast, Midwest, Southeast, and South of Brazil, along with the aforementioned countries. A conducive environment for this crop's growth features air temperatures between 21 to 25°C and a minimum precipitation of 1200mm per cycle. We sourced the current climate data from the WorldClim version 2 platform. Meanwhile, projections for future climatic parameters were derived from WorldClim 2.1, utilizing the IPSL-CM6A-LR model with a refined 30-s spatial resolution. We took into account four distinct socio-economic pathways over varying timelines: 2021-2040, 2041-2060, 2061-2081, and 2081-2100. Geographic information system data aided in the spatial interpolation across Brazil, applying the Kriging technique. The outcomes revealed a majority of the examined areas as non-conducive for yerba mate cultivation, with a scanty 12.25% (1.5 million km2) deemed favorable. Predominantly, these propitious regions lie in southern Brazil and Uruguay, the present-day primary producers of yerba mate. Alarming was the discovery that forthcoming climatic scenarios predominantly forecast detrimental shifts, characterized by escalating average air temperatures and diminishing rainfall. These trends portend a decline in suitable cultivation regions for yerba mate.

Naphthalene diimide-Annulated Heterocyclic Acenes: Synthesis, Electrochemical and Semiconductor Properties and their Multifaceted Applications.

Acenes and Naphthalene Diimides (NDIs) stand as distinguished classes of organic compounds, each possessing unique and intriguing properties that have garnered significant attention across various scientific disciplines. Acenes, characterized by linearly fused aromatic rings, have captivated researchers due to their diverse electronic structures and promising applications in materials science. On the other hand, NDIs, known for their distinctive electron-accepting properties, exhibit remarkable versatility in fields ranging from organic electronics, supramolecular to spin chemistry. In this review, we navigate through the fascinating realms of both acenes and NDIs before converging our focus on the highly diverse and distinctive subgroup of NDI-annulated heterocyclic acenes. This potentially important subgroup, has emerged as a subject of intense investigation, encapsulating their fascinating synthesis, optical and electrochemical characteristics, and multifaceted applications that span the realms of chemistry, physics, and biology. Through the exploration of their synthetic strategies, unique properties, and diverse applications, this review aims to offer a comprehensive understanding of the pivotal role played by NDI-based heterocyclic acenes in contemporary multidisciplinary research and technological innovation.

Exploring Hyponyms: Taxonomic Structure and Semantic Features

The article examines the concept of hyponyms, focusing on their taxonomic structure and semantic features. It delves into the hierarchical relationship between hyponyms and hypernyms, exploring how specific terms are classified under broader categories. Additionally, it investigates the distinguishing characteristics and properties that differentiate hyponyms within specific domains, providing insights into their organization and semantic differentiation based on taxonomic structure.