Functional Approach Research Articles

Fiscal regimes and debt sustainability in Colombia

ABSTRACT This paper evaluates Colombia’s debt sustainability for the period 1980–2021, using a nonlinear fiscal reaction function approach. We employ a Markov-Switching model with annual data to identify sustainable and unsustainable fiscal regimes. According to this model, we identified an unsustainable fiscal regime during three periods with an average duration of six years − 1980–1985, 1993–1999, and 2015–2021 – while the other periods are identified as a sustainable regime. Although we find evidence of asymmetric behaviour in fiscal responses and the presence of pro-cyclical fiscal policy, Colombia’s long-term fiscal sustainability is verified based on a globally-based fiscal sustainability test. In this context, the government reacts appropriately to increases in debt only in the sustainable regime, but the fiscal response is sufficiently robust to stabilise public debt throughout the entire period. Finally, we also highlight concerns regarding the current state of the global economy, particularly due to an inflationary trend and escalating interest rates, which can compromise long-term fiscal sustainability.

Functional Traits Drive the Changes in Diversity and Composition of Benthic Invertebrate Communities in Response to Hydrological Regulation

Of all the environmental elements that influence the biological communities of rivers, water flow characteristics are undoubtedly the most important. Unfortunately, natural hydrological characteristics are increasingly threatened by human activities, especially in alpine or high mountain areas where there are numerous hydropower plants. In this study, we analysed the impact of hydrological alterations on the macroinvertebrate community of a lowland river in NW Italy. Specifically, we analysed the macroinvertebrate communities of an unaffected site by comparing them with those of a site subject to hydrological alteration. We adopted an approach that is not only taxonomic but also functional, allowing us to study a component of biodiversity that is generally less known. Our results show that the flow-altered site hosted a benthic community with lower species and functional diversity than the control site. Interestingly, we also detected a number of significant differences between the summer and autumn samples. In particular, examination of community-weighted mean (CWM) trait values reveals significant variation in body size, voltinism, substrate, locomotion, feeding habits and other traits between sites and seasons. The integration of taxonomic and functional approaches provides a comprehensive understanding of how human-induced hydrological variations can affect aquatic biodiversity and ecological functions.

Peripheral anchoring groups strategy enables frontier molecular orbital delocalization and fast radiative decay of narrowband ultraviolet emitters for suppressing efficiency roll-off

Ultraviolet organic light-emitting devices with neat film as emissive layer commonly suffer from low brightness, poor color purity, and severe efficiency roll-off owing to the intrinsic molecular properties. Herein we present a peripheral anchoring functional group approach to decorating “space-crowded donor−acceptor−donor” type carbazole-pyridine derivatives, for developing stable and bipolar ultraviolet fluorophores featuring narrowband emission. The introduction of anchoring group not only increases the delocalization of frontier molecular orbital distributions, enhancing the bipolar transport ability, but also confers the moderate rigidity and torsion of molecular conformation that shortens fluorescence lifetimes in aggregation state. Consequently, the non-doped devices with phenylcarbazole and naphthalene modified emit stable ultraviolet emission with the peaks of 395 and 388 nm and the full width at half maximums of 39 and 43 nm. Moreover, the maximum external quantum efficiencies (EQEs) of ∼4.0% and a mitigated efficiency roll-off at the high brightness of 3000 cd m−2 (EQE3000: ∼3.8%) are achieved, which provides an opportunity for ultraviolet OLEDs to realize the applications at high brightness levels.

Dynamic clustering of spatial–temporal rainfall and temperature data over multi-sites in Yemen using multivariate functional approach

Dynamic clustering of spatial–temporal rainfall and temperature data over multi-sites in Yemen using multivariate functional approach

Comparison of two different integration methods for the (1+1)-dimensional Schrödinger-Poisson equation

We compare two different numerical methods to integrate in time spatially delocalized initial densities using the Schrödinger-Poisson equation system as the evolution law. The basic equation is a nonlinear Schrödinger equation with an auto-gravitating potential created by the wave function density itself. The latter is determined as a solution of Poisson's equation modelling, e.g., non-relativistic gravity. For reasons of complexity, we treat a one-dimensional version of the problem whose numerical integration is still challenging because of the extreme long-range forces (being constant in the asymptotic limit). Both of our methods, a Strang splitting scheme and a basis function approach using B-splines, are compared in numerical convergence and effectivity. Overall, our Strang-splitting evolution compares favourably with the B-spline method. In particular, by using an adaptive time-stepper rather large one-dimensional boxes can be treated. These results give hope for extensions to two spatial dimensions for not too small boxes and large evolution times necessary for describing, for instance, dark matter formation over cosmologically relevant scales.

Saudi Phatic Communication in Translation: A Cultural and Linguistic Perspective

Adopting a functional approach to translation, this study dives deep into phatic communion expressions, categorizing them in relation to their direct translations in English and identifying culturally equivalent phrases in manual and machine translation. With a newly developed corpus of 157 Saudi Arabic phatic expressions, the study classifies them into eight categories, viz., greetings and rituals, politeness, inquiries about well-being, blessings and good wishes, small talk, acknowledgement and agreement, farewells and departure, and expressions of gratitude and appreciation. The corpus is created from five Arabic language films classified as popular choices on Netflix. The corpus is then translated by 21 final year English Language program students at Shaqra University, KSA, and by Google Translate (GT). Findings show that most frequently phatic expressions are used to express polite and warm introductions, maintaining courteous communication, and for cultural and religious dimensions. Findings also indicate that the Saudi students demonstrated a high degree of communicative translation of the Arabic phatic expressions into English whereas GT output was off the mark and even irrelevant in many instances, making a case for discouraging the use of GT in Saudi translation studies classrooms. The study concludes with pertinent recommendations offering insights that can be useful in fostering understanding and cultural sensitivity among non-Saudis interacting with Saudi individuals, making this study crucial for those in the fields of translation, intercultural communication, and linguistics.

Sampled-data based asynchronous control for persistent dwell-time switched systems: A delay-dependent Lyapunov functional approach

This paper mainly investigates the sampled-data control issue for switched systems with persistent dwell-time under input time delay. Unlike the common controller design, the existence of the delay makes it possible for the subsystem switching to occur during the sampling intervals, which leads to asynchronous problem. By means of the novel functional consisting of piecewise-continuous delay-dependent Lyapunov functional and looped-functionals, some solvability criteria are given under sufficient consideration of the switching frequency. Furthermore, the stability criterion is formulated by the sum of squares program and the global optimal solution is further provided, which exponentially stabilizes the system. Finally, a numerical example as well as an application design of the tunnel diode circuit are studied, both of which demonstrate the proposed method’s validity and feasibility.

‘One-pot’ engineering of 0D carbon-based inorganic nanoarchitectonics for boosting multitasking catalytic activity

Easy-to-make nanostructured materials that exhibit multitasking activity —while reducing the use of hazardous solvents throughout its architectural design— is a must to advance in the so-called Industry 4.0. Herein, a simple and eco-friendly ‘one-pot’ functionalization approach has been devised for synthesizing 0D carbon-based inorganic nanoarchitectonics made of carbon dots (CDs, as core carbon source) carrying two different inorganic building blocks, viz. quantum dots (CdSe@ZnS–QDs) and metal nanoparticles (Pt–NPs). As a proof-of-principle, the multi-catalytic activity of the resulting 0D Pt/QD/CD nanoarchitectonics by means of photoelectrocatalysis and sonocatalysis has been considered and compared with the pristine CD counterpart, demonstrating its suitability for boosting pivotal catalytic tasks like i) the photoelectrogeneration of hydrogen via hydrogen evolution reaction (HER), and ii) the sonodegradation of environmental pollutants (i.e., Rhodamine B) in water. Overall, this chemical approach is general and might be tailored for architecting alternative carbon-based heterostructures to enhance alternative multi-catalytic tasks.

Recycled rubber wastes-based polymer composites with flame retardancy and electrical conductivity: Rational design, modeling and optimization

Polymer recycling techniques experience a maturity period of design and application. Rubbers comprise a high proportion of polymer wastes, highly flammable and impossible to re-melt. Polymer composites based on ground tire rubber (GTR) and ethylene-vinyl acetate copolymer (EVA) containing carbon black (CB) (1–50 phr), with variable EVA/GTR weight composition (10/90, 25/75, 50/50, 75/25 and 90/10), and processing temperature (Low: 100 °C and High: 200 °C) were designed applying Design of Experiments (DOE) approach of Optimal Design. The properties and performance features were experimentally evaluated. The tensile strength (TS) and elongation at break (EB) were optimized using Desirability Function (DF) approach. A wide fluidity window (Labeled POOR, GOOD, and EXCELLENT) and mechanical properties were observed. Overall, higher values of EB were assigned to samples processed at 200 °C. Cubic regression modeling and DF optimization of TS and EB indicated unlikely that one expect a TS ≥ 3 MPa, while EB values more than 500% were likely regardless of CB content for EVA-rich composites. The electrical properties of CB/EVA/GTR samples were examined by impedance spectroscopy technique. An interesting relationship was observed between the DC conductivity and the EVA/GTR ratio and processing temperature. GTR-rich samples showed much higher conductivity than EVA-dominated samples, attributed to the presence of CB in the rubber waste, which, together with the added CB, was able to create conduction paths for the transported electrons. Higher processing temperature of 200 °C improved dispersion of the added CB, i.e. a more even distribution of the conductive phase in the matrix. The uniform and evenly dispersed domains of particles were detected by SEM images for highly CB loaded composites. Surprisingly, 50/50 EVA/GTR composites were resilient against flame, while thermally stable ones in TGA measurements were highly CB loaded ones.

Single proxy control.

Negative control variables are sometimes used in nonexperimental studies to detect the presence of confounding by hidden factors. A negative control outcome (NCO) is an outcome that is influenced by unobserved confounders of the exposure effects on the outcome in view, but is not causally impacted by the exposure. Tchetgen Tchetgen (2013) introduced the Control Outcome Calibration Approach (COCA) as a formal NCO counterfactual method to detect and correct for residual confounding bias. For identification, COCA treats the NCO as an error-prone proxy of the treatment-free counterfactual outcome of interest, and involves regressing the NCO on the treatment-free counterfactual, together with a rank-preserving structural model, which assumes a constant individual-level causal effect. In this work, we establish nonparametric COCA identification for the average causal effect for the treated, without requiring rank-preservation, therefore accommodating unrestricted effect heterogeneity across units. This nonparametric identification result has important practical implications, as it provides single-proxy confounding control, in contrast to recently proposed proximal causal inference, which relies for identification on a pair of confounding proxies. For COCA estimation we propose 3 separate strategies: (i) an extended propensity score approach, (ii) an outcome bridge function approach, and (iii) a doubly-robust approach. Finally, we illustrate the proposed methods in an application evaluating the causal impact of a Zika virus outbreak on birth rate in Brazil.

Understanding the role of π-π stacking from red carbon for selective, high stable and anti-external interference detecting ferric ions and cellular imaging

The subcarboxylated carbon (C3O2) is a unique molecule that spontaneously polymerizes into highly conjugated fluorescence structures p(C3O2)n, named “red carbon”. This unique property, combined with its role as aggregation-induced emission luminogens, has allowed for a deeper exploration of their emission mechanism. Herein, both density functional theory calculations and experimental approaches to elucidate the crystal structure of π–π stacking in red carbon, thereby enhancing the fluorescence properties of p(C3O2)n polymer in its aggregated state. The time-dependent density functional theory calculations and experimental observations indicate that the fluorescence of red carbon can be quenched by ferric ions (Fe3+) and subsequently restored by ethylenediaminetetraaceticacid (EDTA). This quenching process follows first-order reaction kinetics. On the basis of the coordination to metal ions from abundant heteroatoms on red carbon, the high sensitivity, quick responsive (1 min), sensitive detection (the lowest detection limit is 0.97 μM) for the Fe3+ were realized in red carbon, which provides inspirations for the design of new turn-on probes with high stability in detecting the Fe3+ in aqueous solution. Crucially, the red carbon as a light-up fluorescence probe can be employed for the Fe3+ sensing in living cells, which enlighten a new perspective for designing non-conjugated fluorescent polymers. This innovative approach opens up new avenues for developing probes that can detect Fe3+ with high precision and reliability in complex biological environments.

The spillover effect of export on total factor productivity of enterprises: panel data approach in Vietnam

PurposeThis study addresses the empirical results of the spillover effect with export as the primary economic activity that enhances local businesses' total factor productivity (TFP). A learning mechanism is expected to be generated and used as the basis for the policy implication.Design/methodology/approachThis study adopted the Cobb–Douglas function and multiple estimation approaches, including the generalized method of moments, the Olley–Pakes and the Levinsohn–Petrin estimation techniques. The findings were estimated based on the panel data of a Vietnamese local businesses survey conducted by the General Statistics Office of Vietnam (GSO) from 2010 to 2019.FindingsThe results showed that the highest TFP belongs to the businesses in the Southeast region, the Mekong Delta region, the mining industry and the foreign-invested enterprises. The lowest impacted TFP are businesses in the Northwest region and agricultural, forestry and fishery sectors. In addition, the estimated results also show that the positive spillover effect on TFP is shown through forward and backward linkage. The negative spillover effect is expressed through the backward and horizontal channels.Research limitations/implicationsThis study offers original empirical evidence on the learning mechanisms via which exports contribute to productivity improvement in a developing Asian economy, so making a valuable contribution to the existing academic literature in this domain. The findings of this research make a valuable contribution to the advancement of understanding on the many ways via which spillover effects manifest such as horizontal, forward, backward and supplied-backward linkage.Practical implicationsThe study's findings indicate that it is advisable for governments to give priority to the development and improvement of forward and supply chain linkages between exporters and local suppliers. This approach is recommended in order to optimize the advantages derived from export spillovers. At the organizational level, it is imperative for enterprises to strengthen their technological and managerial skills in order to efficiently incorporate knowledge spillovers that originate from overseas partners and trade counterparts.Originality/valueThis study sheds new evidence on the export spillover effect on productivity in emerging economies, with Vietnam as the case study. The paper contributes to the research's originality by adopting novel methodological aspects to estimate local businesses' impact on total factor productivity.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0373

Multidimensional welfare indices and the IPCC 6th Assessment Report scenarios

The IPCC's 6th assessment report (AR6) has provided a wide range of variables and scenarios that meet climate targets of varying ambition. Many variables reported in the AR6 affect human welfare through climate change and mitigation, including but not limited to economic output, the natural environment, human health, and food and energy supply. In some of these dimensions, trade-offs exist between better performance in welfare-relevant dimensions and reaching more ambitious climate targets. Here, we apply recent advances in the theoretical multidimensional measurement of welfare, like the Human Development Index, to the AR6 database. The welfare metric is based on a welfare function approach, simple to apply, and intuitive. We apply a range of specifications of the welfare metric, aiming to derive robust rankings of climate policy targets that perform best in terms of the multidimensional welfare index. Across a large range of weights on welfare-relevant variables, we find that lower temperature is associated with higher welfare in 2100 unless there is a high weight on food supply.

Estimation with extended sequential order statistics: A link function approach

AbstractThe model of extended sequential order statistics (ESOS) comprises of two valuable characteristics making the model powerful when modelling multi‐component systems. First, components can be assumed to be heterogeneous and second, component lifetime distributions can change upon failure of other components. This degree of flexibility comes at the cost of a large number of parameters. The exact number depends on the system size and the observation depth and can quickly exceed the number of observations available. Consequently, the model would benefit from a reduction in the dimension of the parameter space to make it more readily applicable to real‐world problems. In this article, we introduce link functions to the ESOS model to reduce the dimension of the parameter space while retaining the flexibility of the model. These functions model the relation between model parameters of a component across levels. By construction the proposed ‘link estimates’ conveniently yield ordered model estimates. We demonstrate how those ordered estimates lead to better results compared to their unordered counterparts, particularly when sample sizes are small.

Multiple Hypothesis Dropout: Estimating the Parameters of Multi-Modal Output Distributions

In many real-world applications, from robotics to pedestrian trajectory prediction, there is a need to predict multiple real-valued outputs to represent several potential scenarios. Current deep learning techniques to address multiple-output problems are based on two main methodologies: (1) mixture density networks, which suffer from poor stability at high dimensions, or (2) multiple choice learning (MCL), an approach that uses M single-output functions, each only producing a point estimate hypothesis. This paper presents a Mixture of Multiple-Output functions (MoM) approach using a novel variant of dropout, Multiple Hypothesis Dropout. Unlike traditional MCL-based approaches, each multiple-output function not only estimates the mean but also the variance for its hypothesis. This is achieved through a novel stochastic winner-take-all loss which allows each multiple-output function to estimate variance through the spread of its subnetwork predictions. Experiments on supervised learning problems illustrate that our approach outperforms existing solutions for reconstructing multimodal output distributions. Additional studies on unsupervised learning problems show that estimating the parameters of latent posterior distributions within a discrete autoencoder significantly improves codebook efficiency, sample quality, precision and recall.

Labor market monopsony power in the manufacturing sector of four Sub‐Saharan African countries

AbstractWe estimate labor market monopsony power among manufacturing firms in four Sub‐Saharan African countries using a parametric production function approach on panel dataset. Pooled estimate suggests that wages are approximately 38 percent of the marginal revenue product of labor, implying a labor supply elasticity of 0.62. Nonparametric robustness checks indicate these results are robust to concerns over parametric model misspecification. Departure from competitive labor market leads to approximately 50.80 percent higher employer rent, 75.61 percent lower employee rent, and 15.95 percent deadweight loss. Overall, our results are suggestive of monopsonistic labor markets.

Assessment of Persian export pomegranate quality: A reliable non-destructive method based on spectroscopy and chemometrics

The present study investigated the feasibility of visible near-infrared (Vis-NIR) spectroscopy method as a low-cost, quick and reliable method for the prediction of qualitative characteristics (fruit juice percentage, soluble solids, acidity, taste index and vitamin C) of an export variety of Persian pomegranate. For this purpose, pomegranate samples were first analyzed by Vis-NIR spectroscopy, followed by destructive reference methods for quality determination. Subsequently, the data from Vis-NIR were evaluated with different pre-processing methods, among which the combination of the Savitzky–Golay (SG) smoothing model and standard normal variation (SNV) normalization model, generates the best outcomes in predicting six desired qualitative characteristics by partial least square regression (PLSR) model. Fruit juice percentage and pH presented the best prediction models with a correlation coefficient (rP) of 0.98 for both, and root mean square errors of prediction (RMSEP) equal to 0.036 and 0.041, respectively. The values of rp for all desired parameters in this study were higher than 0.95, which pointed to the excellent accuracy of the PLSR models in the prediction of pomegranate qualitative features. It can be concluded from the present study that, Vis-NIR spectroscopy using the PLSR model as a non-destructive functional approach is capable of verifying the quality of Persian export variety pomegranate as an online technique with the aim of grading products before the export phase in order to augment the product marketability.

Bioactivity assessment of organophosphate flame retardants via a dose-dependent yeast functional genomics approach

Organophosphate flame retardants (OPFRs) have been widely detected in multiple environment media and have many adverse effects with complex toxicity mechanisms. However, the early molecular responses to OPFRs have not been fully elucidated, thereby making it difficult to assess their risks accurately. In this work, we systematically explored the point of departure (POD) of biological pathways at genome-wide level perturbed by 14 OPFRs with three substituents (alkyl, halogen, and aryl) using a dose-dependent functional genomics approach in Saccharomyces cerevisiae at 24 h exposure. Firstly, our results demonstrated that the overall biological potency at gene level (PODDRG20) ranged from 0.013 to 35.079 μM for 14 OPFRs, especially the tributyl phosphate (TnBP) exhibited the strongest biological potency with the least PODDRG20. Secondly, we found that structural characteristics of carbon number and logKow were significantly negatively correlated with POD, and carbon number and logKow also significantly affected lipid metabolism associated processes. Thirdly, these early biological pathways of OPFRs toxification were found to be involved in lipid metabolism, oxidative stress, DNA damage, MAPK signaling pathway, and amino acid and carbohydrate metabolism, among which the lipid metabolism was the most sensitive molecular response perturbed by most OPFRs. More importantly, we identified one resistant mutant strain with knockout of ERG2 (YMR202W) gene participated in steroid biosynthesis pathway, which can serve as a key yeast strain of OPFRs toxification. Overall, our study demonstrated an effective platform for accurately assessing OPFRs risks and provided a basis for further green OPFRs development.

Abstract 6359: Development of PSMA x CD3 T-cell engagers using an integrated, functional approach

Abstract In this study, we used a functional approach to generate CD3 T-cell engager (TCE) molecules targeting prostate-specific membrane antigen (PSMA). We present data on the robust in vitro characterization of T-cell activity and selection of molecules for further assessment. TCE function is dictated by the interplay between multiple factors that form the immune synapse, including binding kinetics, binding geometry, and epitopes of the CD3- and tumor-binding arms. To diversify immune synapse parameters, we engineer hundreds of bispecific molecules from highly diverse parental antibodies, and employ a high-throughput process to select molecules with desired functional properties. We applied this approach to engineer CD3 TCEs targeting PSMA. PSMA is an attractive target for the treatment of castration-resistant prostate cancer due to its high expression in prostate cancer cells and low relative expression in other tissues. We discovered hundreds of diverse, fully human PSMA-binding antibodies using high-throughput single B-cell screening and selected human/cynomolgus cross-reactive binders with a broad range of affinities and epitopes. We paired these with human/cynomolgus cross-reactive CD3-binding antibodies from our TCE platform to generate 180 bispecific PSMA x CD3 TCEs. CD3-binding antibodies covered several orders of magnitude of affinity (nanomolar to micromolar) and included binders specific for different CD3 subunits. We used high-throughput T-cell dependent cellular cytotoxicity (TDCC) and cytokine release assays to identify molecules with desired functional profiles. Bispecifics selected for further assessment had functional profiles spanning a range of properties that have been observed in clinical molecules, including potent killing and low cytokine release. To profile T-cell properties that are associated with anti-tumor immune responses, we subjected selected molecules to a battery of additional in vitro functional assessments, including proliferation, cytokine and chemokine production, and TDCC using cynomolgus T cells. Results demonstrate that a functional approach that begins with highly diverse CD3- and tumor-binding antibodies can generate promising TCEs with minimal need for protein engineering and optimization. Citation Format: Valentine de Puyraimond, Matt Mai, Alaa Amash, Nathalie Blamey, Gabrielle Conaghan, Jessica Fernandes Scortecci, Allison Goodman, Ahn Lee, Irene Yu, Franziska von Bank, Kate Caldwell, Lauren Clifford, Ingrid Knarston, Kelly Bullock, Melissa Cid, Cindy-Lee Crichlow, Lindsay Devorkin, Fiona Dickson, Patrick Farber, Stefan Hannie, Courteney Lai, Vivian Li, Stephanie K. Masterman, Iwona Niemietz, Philippe Pouliot, Ping Xiang, Bryan C. Barnhart, Raffi Tonikian. Development of PSMA x CD3 T-cell engagers using an integrated, functional approach [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 6359.

OsRR26, a type-B response regulator, modulates salinity tolerance in rice via phytohormone-mediated ROS accumulation in roots and influencing reproductive development.

OsRR26 is a cytokinin-responsive response regulator that promotes phytohormone-mediated ROS accumulation in rice roots, regulates seedling growth, spikelet fertility, awn development, represses NADPH oxidases, and negatively affects salinity tolerance. Plant two-component systems (TCS) play a pivotal role in phytohormone signaling, stress responses, and circadian rhythm. However, a significant knowledge gap exists regarding TCS in rice. In this study, we utilized a functional genomics approach to elucidate the role of OsRR26, a type-B response regulator in rice. Our results demonstrate that OsRR26 is responsive to cytokinin, ABA, and salinity stress, serving as the ortholog of Arabidopsis ARR11. OsRR26 primarily localizes to the nucleus and plays a crucial role in seedling growth, spikelet fertility, and the suppression of awn development. Exogenous application of cytokinin led to distinct patterns of reactive oxygen species (ROS) accumulation in the roots of both WT and transgenic plants (OsRR26OE and OsRR26KD), indicating the potential involvement of OsRR26 in cytokinin-mediated ROS signaling in roots. The application of exogenous ABA resulted in varied cellular compartmentalization of ROS between the WT and transgenic lines. Stress tolerance assays of these plants revealed that OsRR26 functions as a negative regulator of salinity stress tolerance across different developmental stages in rice. Physiological and biochemical analyses unveiled that the knockdown of OsRR26 enhances salinity tolerance, characterized by improved chlorophyll retention and the accumulation of soluble sugars, K+ content, and amino acids, particularly proline.