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Abstract Moiré excitons (MXs) are electron-hole pairs localised by the periodic (moiré) potential forming in two-dimensional heterostructures (HSs). MXs can be exploited, e.g., for creating nanoscale-ordered quantum emitters and achieving or probing strongly correlated electronic phases at relatively high temperatures. Here, we studied the exciton properties of WSe2/MoSe2 HSs from T = 6 K to room temperature using time-resolved and continuous-wave micro-photoluminescence also under a magnetic field. The exciton dynamics and emission lineshape evolution with temperature show clear signatures that MXs de-trap from the moiré potential and turn into free interlayer excitons (IXs) for temperatures above 100 K. The MX-to-IX transition is also apparent from the exciton magnetic moment reversing its sign when the moiré potential is not capable of localising excitons at elevated temperatures. Concomitantly, the exciton formation and decay times reduce drastically. Thus, our findings establish the conditions for a truly confined nature of the exciton states in a moiré superlattice with increasing temperature and photo-generated carrier density.

Abstract Background The nationally determined contribution (NDC) presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United Nations Framework Convention on Climate Change (UNFCCC) on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation (REDD+). In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon (SOC) stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under climate variability due to a lack of information. The objectives of this study were: (i) to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and (ii) to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter-annual climate variability. Methods We used 1040 forest soil samples (0–30 cm) to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covariates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud-based computing platform for subsequent modelling. To determine the biodiversity threats from high inter-annual climate variability, we employed the spatial–temporal satellite-derived indices based on Enhanced Vegetation Index (EVI) and land surface temperature (LST) images from Landsat imagery. Results SOC model (0–30 cm depth) prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C (2.71–2.84 Pg C with a probability of 90%) for a total area of 460,790 km2, where Chaco forests represented 58.4% of total SOC stored, followed by Andean Patagonian forests (16.7%) and Espinal forests (10.0%). SOC stock model was fitted as a function of regional climate, which greatly influenced forest ecosystems, including precipitation (annual mean precipitation and precipitation of warmest quarter) and temperature (day land surface temperature, seasonality, maximum temperature of warmest month, month of maximum temperature, night land surface temperature, and monthly minimum temperature). Biodiversity was influenced by the SOC levels and the forest regions. Conclusions In the framework of the Kyoto Protocol and REDD+, information derived in the present work from the estimate of SOC in native forests can be incorporated into the annual National Inventory Report of Argentina to assist forest management proposals. It also gives insight into how native forests can be more resilient to reduce the impact of biodiversity loss.

Millimeter-wave and Terahertz communications consist of complex analog and mixed-signal transceivers where overall system performance is often limited by the weakest performing subsystem. While analog and mixed-signal integrated circuits have significantly advanced, the future of 5G and 6G transceiver design could be accelerated by including artificial intelligence. In this combination, analog integrated circuit design and operation would harness machine learning to identify, characterize, and act upon variations and anomalies in system performance. Focusing on 5G and 6G, this paper investigates solutions for a unified intelligent integrated transceiver: a conceptual combination of a traditional analog subsystem, a supporting digital subsystem that enables artificial intelligence, and dedicated feedback circuitry or sensors that monitor performance, efficiency, or reliability. Active and passive components and propagation channels are reviewed based on their merits of introducing intelligence. Holistically and for broader applicability, the paper conceptualizes and coins the notion of an “intelligent integrated system (IIS)”, which brings forward a novel unified vision and approach toward context-aware subsystems that dynamically interact with ambient and varying operating conditions. To demonstrate viability, the paper concatenates a select set of measurement results.

Alloying has been a powerful and practical strategy to widen the palette of physical properties available to semiconductor materials. Thanks to recent advances in the synthesis of van der Waals semiconductors, this strategy can be extended to monolayers (MLs) of transition metal dichalcogenides (TMDs). Due to their extraordinary flexibility and robustness, strain is another powerful means to engineer the electronic properties of two-dimensional (2D) TMDs. In this article, we combine these two approaches in an exemplary metal dichalcogenide chalcogen-alloy, WSSe. Highly strained WSSe MLs are obtained through the formation of micro-domes filled with high-pressure hydrogen. Such structures are achieved by hydrogen-ion irradiation of the bulk material, a technique successfully employed in TMDs and h-BN. Atomic force microscopy studies of the WSSe ML domes show that the dome morphology can be reproduced in terms of the average of the elastic parameters and adhesion energy of the end compounds WSe 2 and WS 2. Micro-photoluminescence measurements of the WSSe domes demonstrate that the exceedingly high strains (ε ∼ 4 %) achieved in the domes trigger a direct-to-indirect exciton transition, similarly to WSe 2 and WS 2. Our findings heighten the prospects of 2D alloys as strain- and composition-engineerable materials for flexible optoelectronics. [ABSTRACT FROM AUTHOR]

The conversion of semimetallic suspended graphene (Gr) to a large-gap semiconducting phase is here realized by controlled adsorption of atomic hydrogen (deuterium) on free-standing nanoporous Gr veils. This approach allows to achieve a very clean and neat adsorption, overcoming any spurious influence associated to the presence of substrates. The effects of local rehybridization from sp2 to sp3 chemical bonding are investigated by combining X-ray photoelectron spectroscopy and high-resolution electron energy-loss spectroscopy (HREELS) with ab-initio based modelling. We find that the hydrogen adatoms on the C sites induce a stretching frequency, clearly identified in the vibrational spectra thanks to the use of the D isotope. Overall, the results are compatible with the predicted fingerprints of adsorption on both sides of Gr corresponding to the graphane configuration. Moreover, HREELS of the deuterated samples shows a sizeable opening of the optical band gap, i.e. 3.25 eV, consistent with the modified spectral density observed in the valence band photoemission. The results are in agreement with ab-initio calculations by GW and Bethe–Salpeter equation approaches, predicting a large quasiparticle gap opening and huge exciton binding energy.

Plateau’s law describes the configuration (joint angles ~120°) of soap bubbles, foams and cellular structures, but its applicability to solid films has not been explored. Here, the authors report the observation of a variant Plateau’s law in networks of nanobubbles made of 2D semiconductors, measuring largely varying joint angles due to the thickness-dependent effective surface tension.

Nowadays, Massive Open Online Courses (MOOCs) are adopted by students worldwide. One of the main critical issues often associated with MOOCs is the dropout phenomenon. In other words, the percentage of students abandoning a MOOC-based study path is considered still too high. Therefore, an increasing number of scientific works, coming from several heterogeneous communities (e.g., computer science, data science, statistics, education) propose approaches trying to mitigate such a problem. The majority of the aforementioned works focus on machine learning methods to define classifiers able to be trained and, subsequently, to predict students who are going to abandon a course before it ends. Among such approaches, the ones achieving the best performance use enriched sets of features (to train their models) and produce results that cannot be used to easily clearly characterize the different behaviors of dropping-out and non-dropping-out students. The present work proposes the design of a novel process to train a set of dropout predictors leveraging on a reduced set of features. The underlying idea is to exploit weekly data in order to classify, with acceptable levels of precision, students who are likely going towards dropout or not. In cases of uncertainty, the classification decision is deferred to the next week, when new data is available. Such an approach, which takes care and is aware of the course timeline, offers several advantages. The first one is the chance to build a real-time educational decision support system able to support decision as sufficient information is available (as the time goes on). The second one is to preserve resources and avoiding wasting them with students erroneously classified at risk of dropout. The third one is to allow explicit characterization of dropout-conducing behavior by using a rule mining approach.

BackgroundBreast cancer during pregnancy (PrBC) is a rare condition known for its aggressive clinical behavior. The presence of tumor-infiltrating lymphocytes (TILs) has been shown to have a significant impact on the prognosis of these patients. Despite some biological characteristics of the tumor that may differ depending on the gestational age, little is known about the dynamics of the immune landscape within the tumor microenvironment (TME) in PrBC. Therefore, in this study, our objective was to gain comprehensive insights into the relationship between gestational age at breast cancer diagnosis and the composition of the TME.Methodsn = 108 PrBC were selected from our institutional registry and categorized based on the gestational age by trimester. For all cases, TILs were profiled according to the International TILs Working Group recommendations, and subtyped by CD4, CD8, and forkhead box P3 (FOXP3) immunohistochemistry. PD-L1 was tested according to the combined positive score (CPS) using the IHC 22C3 pharmDx assay, with a cutoff value of ≥10 for positivity. The statistical approach encompassed Fisher’s and Chi-squared tests, with appropriate adjustments for multiple comparisons, logistic regression models, and survival analyses based on the Kaplan–Meier method.ResultsThe proportion of patients with poorly differentiated (G3) neoplasms increased as the gestational age advanced (first trimester, n = 25, 56.8%; second trimester, n = 27, 69.2%; third trimester, n = 21, 87.5%; p = 0.03). The histologic subtypes as well as the hormone receptor (HR) and HER2 status did not show significant changes across different pregnancy trimesters. In the HR+/HER2– subtype, there was a higher proportion of tumors with high/moderate TILs in the early phases of pregnancy, similar to FOXP3 expression (TILs: first trimester, n = 10, 35.7%; second trimester, n = 2, 10.5%; third trimester, n = 0; p = 0.02; FOXP3: first trimester, n = 10, 40%; second trimester, n = 3, 15.8%; third trimester, n = 0; p = 0.03). The median follow-up for our cohort was 81 months. Patients who relapsed after a breast cancer diagnosis during the first trimester were more frequently PD-L1-negative, unlike those with no disease recurrence (n = 9, 100% vs. n = 9, 56.3%; p = 0.03; hormone therapy and n = 9, 100% vs. n = 7, 53.9%; p = 0.02; chemotherapy). No statistically significant differences were seen among the three trimesters in terms of survival outcome.ConclusionThe TME dynamics of HR+/HER2− PrBC vary based on gestational age, suggesting that immune tolerance expression during later gestational age could explain the increased aggressiveness of tumors diagnosed at that stage.

Highly aligned multi-wall carbon nanotubes were investigated with scanning electron microscopy (SEM), Raman spectroscopy and X-ray photoelectron spectroscopy (XPS) before and after bombardment performed using noble gas ions of different masses (argon, neon and helium), in an ultra-high-vacuum (UHV) environment. Ion irradiation leads to change in morphology, deformation of the carbon (C) honeycomb lattice and different structural defects in multi-wall carbon nanotubes. One of the major effects is the production of bond distortions, as determined by micro-Raman and micro-X-ray photoelectron spectroscopy. We observe an increase in sp3 distorted bonds at higher binding energy with respect to the expected sp2 associated signal of the carbon 1s core level, and increase in dangling bonds. Furthermore, the surface damage as determined by the X-ray photoelectron spectroscopy carbon 1s core level is equivalent upon bombarding with ions of different masses, while the impact and density of defects in the lattice of the MWCNTs as determined by micro-Raman are dependent on the bombarding ion mass; heavier for helium ions, lighter for argon ions. These results on the controlled increase in sp3 distorted bonds, as created on the multi-wall carbon nanotubes, open new functionalization prospects to improve and increase atomic hydrogen uptake on ion-bombarded multi-wall carbon nanotubes.

Measurement(s) Bark thickness • Leaf area • Leaf aluminium (Al) content per leaf dry mass • Specific leaf area • Leaf calcium (Ca) content per leaf dry mass • Leaf carbon (C) content per leaf dry mass • Leaf carbon (C) isotope signature (delta 13 C) • Leaf compoundness • Leaf dry mass per leaf fresh mass (leaf dry matter content, LDMC) • Leaf magnesium (Mg) content per leaf dry mass • Leaf nitrogen (N) content per leaf dry mass • Leaf nitrogen (N) isotope signature (delta 15 N) • Leaf phosphorus (P) content per leaf dry mass • Leaf potassium (K) content per leaf dry mass • Leaf texture (sclerophylly, physical strength, toughness) • leaf thickness • Plant growth form • Stem conduit cross-sectional area (vessels and tracheids) • Stem conduit density (vessels and tracheids) • Sapwood specific conductivity Technology Type(s) bark gauge • Scanner Device • inductively-coupled plasma atomic emission spectroscopy • Calculated from area and mass • CN analyzer • Isotope analyzer • in vivo visual assessment • Ratio of fresh to dry mass • punch tester • micrometer • optical analysis of cross sections with specific software • weight and volume measurement • estimated with equations from wood anatomy Factor Type(s) Country • Lat • Long • Elevation • Collection_year Sample Characteristic - Organism Tracheophyta Sample Characteristic - Environment Andean ecosystems • cloud forest • tropical upper montane forest • tropical lower montane forest • Paramo • Andes Sample Characteristic - Location South America • Venezuela • Colombia • Ecuador • Peru • Bolivia • Argentina

Purpose: Assessment of agricultural advisory services is crucial to improve their quality and effectiveness. Farmer Field Schools (FFS) have been adapted to meet context specific needs in crop or farm management. This article investigates whether the diversity of FFS interventions is reflected in the assessment methods used to evaluate them. Design/Methodology/Approach: Through a systematic review of peer-reviewed literature we identified 180 articles and selected 34 that assessed FFS. Implementation was characterised based on farmers' participation and FFS topics. Assessment methods were analysed using a causal chain of inputs, outputs, outcomes, and impacts. Findings: Our results showed three types of FFS: (1) technology transfer; (2) consultative participation at cropping system level; and, (3) consultative or collaborative participation at farm level. Fifteen studies did not describe FFS implementation at all. Out of the 34 assessments, 23 focused on inputs (knowledge) and outputs (changes in practices, agricultural or economic performance) for farmers. Only six studies assessed long-term impacts of FFS. Theoretical implications: We found a paradox between the shift from a technology transfer to a participatory advisory services paradigm, and the implementation and assessment of FFS, which do not mirror this shift. Assessment methods remain based on assumed technology transfer, which is not suitable for the evaluation of participatory approaches and their results, including in terms of capacity to innovate. Practical implications: Assessing FFS as a collective and farmer-centered experiential learning approach requires appropriate evaluation methods that account for the diversity of contexts, FFS implementation, and the changes they generate. Originality/Value: The diversity of FFS has rarely been analysed to date. This article proposes a typology to go beyond FFS as a catch-all term and to guide their assessment.

The design and implementation of targeted policies and programmes are crucial to addressing climate challenges. In this study, we sought to understand the means by and extent to which the Central American Climate-Smart Agriculture Strategy (EASAC) has contributed to addressing the specific climate challenges facing the regional agricultural sector. We applied a theory-based evaluation and contribution analysis to examine this policy and identified 252 changes at the national and regional levels that align with the EASAC theory of change (ToC). Contribution analysis revealed that none of the 23 changes we assessed could be attributed solely to the EASAC; however, it contributed directly, in combination with other actors and institutions, to 10 such changes. Our results question the efficacy of non-binding regional policies, such as the EASAC, in influencing national policy changes and highlight the dependency of climate policy implementation on international cooperation in the Central American Integration System region. Intersectoral and actor coordination, the availability of technical and research expertise, and research input appear critical to the successful implementation of regional climate policy. Key policy insights Theory-based assessments and contribution analyses are relevant and rigorous tools that can be effectively applied to climate policy. They enable a deeper understanding and more effective management of climate governance. International organizations play crucial roles in translating international agreements into policies, particularly in Central America, where public climate finance remains limited. Such organizations are responsible for developing and funding policies that align with these agreements. Many changes aligned with the EASAC ToC framework have been observed, reflecting the dynamic process of up-scaling regional climate-smart agriculture. Most changes have been focused on policy formulation and adjustment, with fewer related to establishing alliances and platforms for dialogue. The EASAC strategy of targeting non-binding regional governance to influence national governments is inherently limited and may be ineffective on its own. [ABSTRACT FROM AUTHOR]

Subjective memory decline (SMD) might represent the preclinical phase of Alzheimer's disease (AD), and has been reported in epileptic amnesia associated with accelerated long-term forgetting (ALF). We investigated ALF in SMD subjects by means of RAVLT recall and recognition and ROCF recall after 1-week retention and compared with a control group. Two-way ANOVAs for RAVLT and ROCF were conducted, and stepwise regression analysis was administered considering EMQ and DASS-21 as factors. SMD subjects performed significantly worse than controls at 1-week delay on RAVLT recall and recognition, but not on ROCF, and not associated with depression or memory complaints. SMD patients showed ALF, which is usually associated with temporomesial dysfunctions, representing a cognitive marker to assess objectively memory problems in SMD, and to undisclose initial neurodegenerative disease involving temporal structures usually compromised in AD. Therefore, SMD might no longer be "subjective," but rather a specific and defined clinical entity. [ABSTRACT FROM AUTHOR]

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Patterns of species diversity have been associated with changes in climate across latitude and elevation. However, the ecological and evolutionary mechanisms underlying these relationships are still actively debated. Here, we present a complementary view of the well-known tropical niche conservatism (TNC) hypothesis, termed the multiple zones of origin (MZO) hypothesis, to explore mechanisms underlying latitudinal and elevational gradients of phylogenetic diversity in tree communities. The TNC hypothesis posits that most lineages originate in warmer, wetter, and less seasonal environments in the tropics and rarely colonize colder, drier, and more seasonal environments outside of the tropical lowlands, leading to higher phylogenetic diversity at lower latitudes and elevations. In contrast, the MZO hypothesis posits that lineages also originate in temperate environments and readily colonize similar environments in the tropical highlands, leading to lower phylogenetic diversity at lower latitudes and elevations. We tested these phylogenetic predictions using a combination of computer simulations and empirical analyses of tree communities in 245 forest plots located in six countries across the tropical and subtropical Andes. We estimated the phylogenetic diversity for each plot and regressed it against elevation and latitude. Our simulated and empirical results provide strong support for the MZO hypothesis. Phylogenetic diversity among co-occurring tree species increased with both latitude and elevation, suggesting an important influence on the historical dispersal of lineages with temperate origins into the tropical highlands. The mixing of different floras was likely favored by the formation of climatically suitable corridors for plant migration due to the Andean uplift. Accounting for the evolutionary history of plant communities helps to advance our knowledge of the drivers of tree community assembly along complex climatic gradients, and thus their likely responses to modern anthropogenic climate change.

This work describes a resonance Raman study performed in the domes of monolayer MoS2 using 23 different laser excitation energies covering the visible and near-infrared (NIR) ranges. The multiple excitation results allowed us to investigate the exciton–phonon interactions of different phonons (A′1, E′, and LA) with different excitonic optical transitions in biaxially strained monolayer MoS2. The analysis of the intensities of the two first-order peaks, A′1 and E′, and the double-resonance 2LA Raman band as a function of the laser excitation furnished the values of the energies of the indirect exciton and the direct excitonic transitions in the strained MoS2 domes. It was noticed that the out-of-plane A′1 phonon mode is significantly enhanced only by the indirect exciton I and the C exciton, whereas the in-plane E′ mode is only enhanced by the C exciton of the MoS2 dome, thus revealing the weak interaction of these phonons with the A and B excitons in the strained MoS2 domes. On the other hand, the 2LA Raman band is significantly enhanced at the indirect exciton I and by the A (or B) exciton but not enhanced by the C exciton, thus showing that the LA edge phonons that participate in the double-resonance process in MoS2 have a weak interaction with the C exciton.