Miracle-dz/UniFAR-FTUs huggingface dataset:
Fully automated image-based estimation of postural point-features in children with cerebral palsy using deep learning

The aim of this study was to provide automated identification of postural point-features required to estimate the location and orientation of the head, multi-segmented trunk and arms from videos of the clinical test ‘Segmental Assessment of Trunk Control’ (SATCo). Three expert operators manually annotated 13 point-features in every fourth image of 177 short (5–10 s) videos (25 Hz) of 12 children with cerebral palsy (aged: 4.52 ± 2.4 years), participating in SATCo testing. Linear interpolation for the remaining images resulted in 30 825 annotated images. Convolutional neural networks were trained with cross-validation, giving held-out test results for all children. The point-features were estimated with error 4.4 ± 3.8 pixels at approximately 100 images per second. Truncal segment angles (head, neck and six thoraco-lumbar–pelvic segments) were estimated with error 6.4 ± 2.8°, allowing accurate classification (F1 > 80%) of deviation from a reference posture at thresholds up to 3°, 3° and 2°, respectively. Contact between arm point-features (elbow and wrist) and supporting surface was classified at F1 = 80.5%. This study demonstrates, for the first time, technical feasibility to automate the identification of (i) a sitting segmental posture including individual trunk segments, (ii) changes away from that posture, and (iii) support from the upper limb, required for the clinical SATCo.
Strange Bedfellows: The Alliance Theory of Political Belief Systems

Abstract What explains the contents of political belief systems? A widespread view is that they derive from abstract values, like equality, tolerance, and authority. Here, we challenge this view, arguing instead that belief systems derive from political alliance structures that vary across nations and time periods. When partisans mobilize support for their political allies, they generate patchwork narratives that appeal to ad-hoc, and often incompatible, moral principles. In the first part of the paper, we explain how people choose their allies, and how they support their allies using propagandistic tactics. In the second part, we show how these choices and tactics give rise to political alliance structures, with their strange bedfellows, and the idiosyncratic contents of belief systems. If Alliance Theory is correct, then we need a radically different approach to political psychology—one in which belief systems arise not from deep-seated moral values, but from ever-shifting alliances and rivalries.
Exchange-Rate Policy after a Decade of "Floating"

This paper integrates exchange-rate policy into a model of exchange- rate behavior, and examines the data econometrically to infer hypotheses about policy behavior in the 1970s. The model shows how unanticipated movements in money, the current account, and relative price levels will cause first a jump in the exchange rate, and then a movement along a "saddle path" to the new long run equilibrium. Here the role of "news" in moving the exchange rate is clear. The model is used to analyze the options available to the central bank that wants to reduce the jump in the exchange rate following a real or monetary disturbance. The distinction is made between monetary policy and sterilized intervention, and a regime in which the domestic interest rate is used as the policy variable is also studied. Systems of vector autoregressions (VARs) for each of four countries -- the U.S., the U.K., Germany, and Japan -- are estimated, and the correlations among their residuals are studied. These represent the "innovations," or "news" in the time series. A clear pattern emerges in these correlations, in which policy in the U.S. and to a lesser extent Japan, drives exchange rates, and policy in Germany and the U.K. reacts. It appears that U.S. monetary policy is essentially determined by domestic considerations, with the exchange rate moving as a consequence. In Japan, interest rates are varied in response to movement in the current-account and relative price levels, and the effects on the exchange rate are partially neutralized by sterilized intervention. Germany and the U.K. react to movements in their exchange rates by moving interest rates, and sterilized intervention.
Can I Help You With?: Infrequent Users Experiences of Intelligent Personal Assistants

Intelligent Personal Assistants (IPAs) are widely available on devices such as smartphones. However, most people do not use them regularly. Previous research has studied the experiences of frequent IPA users. Using qualitative methods we explore the experience of infrequent users: people who have tried IPAs, but choose not to use them regularly. Unsurprisingly infrequent users share some of the experiences of frequent users, e.g. frustration at limitations on fully hands-free interaction. Significant points of contrast and previously unidentified concerns also emerge. Cultural norms and social embarrassment take on added significance for infrequent users. Humanness of IPAs sparked comparisons with human assistants, juxtaposing their limitations. Most importantly, significant concerns emerged around privacy, monetization, data permanency and transparency. Drawing on these findings we discuss key challenges, including: designing for interruptability; reconsideration of the human metaphor; issues of trust and data ownership. Addressing these challenges may lead to more widespread IPA use.
mpact of single and dual modifications on physicochemical roperties of japonica and indica rice starches

The japonica (JR) and indica (IR) rice starches were modified by acetylation, hydroxypropylation, crosslinking, and dual modification (cross-linked acetylation and cross-linked hydroxypropylation) and the effects of single and dual chemical modifications of JR and WR on the physicochemical properties were investigated. The JR had a greater substitution degree of acetyl or hydroxypropyl groups than IR. The dual-modified JR showed broader gelatinization temperature range than corresponding single-modified starches, but narrower it in IR. The dual-modified JR and IR showed higher pasting temperature and lower breakdown than their corresponding single-modified starches. The dual modification with JR and
Modelling and Forecasting of Usd/Try Exchange Rate Using ARMA-GARCH Approach

Accurately predicting the exchange rate prices helps investors to obtain maximum profit from their exchange rate investments as well as to help firms conducting business with exchange rates to manage their trading based on these predictions. Therefore, the prediction of exchange rate prices is crucial for both investors and companies engaged in exchange rates. In this study, ARMA (Autoregressive Moving Average) models combined with various GARCH (Generalized Autoregressive Conditional Heteroscedasticity) models are applied to model exchange rate prices. For this purpose, ARMA-GARCH (M) models are investigated in order to determine the effect of volatility on exchange rate prices as well as ARMA-GARCH models in which the errors are distributed both symmetrically and skewed. It is concluded that the best fitted model which is determined based on the goodness of fit and estimation accuracy performance criteria, is firstly ARMA-NAGARCH model which can model asymmetric and non-linear structures and secondly ARMA-GJRGARCH model. However, since the performance of ARMA-GARCH (M) models is lower than ARMA-GARCH models, the effect of volatility on exchange rate prices is found to be weak.
Evidence on the costs and benefits of bond IPOs

This paper investigates whether it is costly for nonfinancial firms to enter the public bond market, and whether firms benefit from their bond IPOs. We find that both gross spreads and ex ante credit spreads are higher for IPO bonds, suggesting that firms pay higher underwriting costs on their first public bond. We also find that underpricing in the secondary market is higher for IPO bonds, further suggesting that it is costly to enter the public bond market. The costs of entering the public bond market are economically meaningful and are higher for risky firms. We investigate the benefits from entering the public bond market, by looking at the costs firms pay to raise external funding subsequently to their bond IPOs. Our results show that these benefits exist, but they accrue only to safe firms. These firms benefit from a reduction both in the interest rates they pay on bank loans and the costs they incur to issue private bonds after they enter the public bond market. Together with our the previous findings, these results lend support to the thesis that bond IPOs are unique.
The Aquila Digital Community The Aquila Digital Community

The epidemic of Zika in the Western hemisphere has led to intense investigation of all species important in its transmission cycle, including the putative mosquito vectors. Although evidence points to Aedes (Stegomyia) mosquitoes as the primary vectors in nature among humans, there remains the possibility that other common mosquito species could be implicated in explaining the rapid spread of the virus. Herein we examined field caught Culex quinquefasciatus from different neighborhoods in San Juan, Puerto Rico collected during June 2016 for the presence of natural infection of Zika virus (ZIKV). Aedes aegypti from the same locations were also analyzed. None of the Cx. quinquefasciatus tested showed natural infection for ZIKV, whereas Ae. aegypti tested positive at 7 sites. Our results suggest that Cx. quinquefasciatus was not involved in the transmission of Zika virus in San Juan, Puerto Rico in 2016.
Expression Modalities: How Speaking Versus Writing Shapes Word of Mouth

Consumers often communicate their attitudes and opinions with others, and such word of mouth has an important impact on what others think, buy, and do. But might the way consumers communicate their attitudes (i.e., through speaking or writing) shape the attitudes they express? And, as a result, the impact of what they share? While a great deal of research has begun to examine drivers of word of mouth, there has been less attention to how communication modality might shape sharing. Six studies, conducted in the laboratory and ﬁeld, demonstrate that compared to speaking, writing leads consumers to express less emotional attitudes. The effect is driven by deliberation. Writing offers more time to deliberate about what to say, which reduces emotionality. The studies also demonstrate a downstream consequence of this effect: by shaping the attitudes expressed, the modality consumers communicate through can inﬂuence the impact of their communication. This work sheds light on word of mouth, effects of communication modality, and the role of language in communication.
Original Research Article Nanoscale water flows in networks against a total fail

A failsafe network design recovering from the stressed condition against a massive supply disruption is generally useful for various applications. Water flow in plants under a tension is inherently vulnerable to an embolism, a water supply cut off, causing a death. However, the function of the network structures of leaf veins and xylem stems effectively reduces the embolism-induced failure. In this study, water transport in plants under the pressurized conditions compared to the normal physiological conditions is observed by X-ray imaing. By examining embolism-induced water supply limits in the architecturally diverse leaf and stem networks, a progressive hydraulic rule has been found: the limited flows in the selected parts of the network structures against a total fail. For a scientific explanation on nanoscale water flow dynamics occurring in plants, temporal meniscus development in the nanomembrane model system is investigated. The pressure-driven hydrodynamic transport phenomena can be explained to follow network dynamics of the modified imbibition typically occuring in nanostrutcures. This study contributes to a variety of design technologies of networked materials against the spread of flow damages under the stressed conditions.
Plant Extracellular Vesicles: Current Landscape and Future Directions

Plant cells secrete membrane-enclosed micrometer- and nanometer-sized vesicles that, similarly to the extracellular vesicles (EVs) released by mammalian or bacterial cells, carry a complex molecular cargo of proteins, nucleic acids, lipids, and primary and secondary metabolites. While it is technically complicated to isolate EVs from whole plants or their tissues, in vitro plant cell cultures provide excellent model systems for their study. Plant EVs have been isolated from the conditioned culture media of plant cell, pollen, hairy root, and protoplast cultures, and recent studies have gathered important structural and biological data that provide a framework to decipher their physiological roles and unveil previously unacknowledged links to their diverse biological functions. The primary function of plant EVs seems to be in the secretion that underlies cell growth and morphogenesis, cell wall composition, and cell–cell communication processes. Besides their physiological functions, plant EVs may participate in defence mechanisms against different plant pathogens, including fungi, viruses, and bacteria. Whereas edible and medicinal-plant-derived nanovesicles isolated from homogenised plant materials ex vivo are widely studied and exploited, today, plant EV research is still in its infancy. This review, for the first time, highlights the different in vitro sources that have been used to isolate plant EVs, together with the structural and biological studies that investigate the molecular cargo, and pinpoints the possible role of plant EVs as mediators in plant–pathogen interactions, which may contribute to opening up new scenarios for agricultural applications, biotechnology, and innovative strategies for plant disease management.
Proof of Compliance for Anonymous, Unlinkable Messages

Anonymous systems are susceptible to malicious activity. For instance, in anonymous payment systems, users may engage in illicit practices like money laundering. Similarly, anonymous federated learning systems decouple user updates to a central machine learning model from the user’s identity; malicious users can manipulate their updates to poison the model. Today, compliance with system-generated rules in such systems can be guaranteed at the level of a single message by utilizing Zero-Knowledge Proofs (ZKP). However, it remains unclear how to prove compliance for rules that are deﬁned over a collection of a user’s messages, without compromising the unlinkability of the messages. To address this challenge, we propose an eﬃcient protocol called Shuﬄe - ZKP , which enables users within an unlinkable messaging system to collectively prove their compliance. Our protocol leverages a distributed and private set equality check protocol along with generic Non-Interactive Zero-Knowledge (NIZK) proof systems. We also provide an additional attributing protocol to identify misbehaving users. We theoretically analyze the protocol’s correctness and privacy properties; we then implement and test it across multiple use cases. Our empirical results show that in use cases involving thousands of users, each user is able to generate a compliance proof within 0.2-10.6 seconds, depending on the use case, while the additional communication overhead remains under 3KB. Furthermore, the protocol is computationally eﬃcient on the server side; the veriﬁcation algorithm requires a few seconds to handle thousands of users in all of our use cases.
Two lncRNA signatures with cuproptosis as a novel prognostic model and clinicopathological value for endometrioid endometrial adenocarcinoma

Objective: Cuproptosis may contribute to tumorigenesis. However, the predictive value and therapeutic significance of cuproptosis-related lncRNAs (CRLs) in endometrioid endometrial adenocarcinoma (EEA) remains unknown. Methods: We obtained RNA-seq data from TCGA database and searched the Literature to identify cuproptosis-related genes. Using machine learning models, we identified prognostic lncRNAs for cuproptosis. Immune properties and drug sensitivity were investigated based on these signatures. Further, a ceRNA network was constructed by bioinformatics and in vitro experiments were performed. Results: We determined two cuproptosis-related signatures to build the prognostic model in EEA. Afterward, the risk scores of two cuproptosis-related signatures were associated with clinicopathological molecular typing and as independent prognostic factors for EEA. In addition, we observed significant differences in immune function, checkpoints, and CD8+ T lymphocyte infiltration between the two risk groups. Furthermore, chemotherapy drugs such as AKT inhibitors exhibited lower IC50 values in the high-risk group. We speculate that ACOXL-AS1 can be served as an endogenous ‘sponge’ to regulate the expression of MTF1 by miR-421. Through in vitro experiments, we preliminarily validated the ceRNA network relationship in the cellular model. Conclusion: In EEAs, this study proposed a broad molecular signature of CRLs are promising biomarkers for predicting clinical outcomes and therapeutic responses.
Optimization of Pulsed Electric Fields-Assisted Extraction of Phenolic Compounds From White Grape Pomace Using Response Surface Methodology

This study was focused on the optimization of the pulsed electric fields (PEF)-assisted extraction process using central composite design for response surface methodology from response surface methodology (RSM) with the aim to sustainably intensify the extractability of phenolic compounds from white grape pomace. The cell disintegration index (Zp) was used as response variable to identify the optimal PEF pre-treatment conditions of grape pomace in terms of field strength (E = 0.5–5 kV/cm) and energy input (WT = 1–20 kJ/kg), to be applied prior to the subsequent solid-liquid extraction (SLE) process. for both untreated and PEF-treated samples SLE process was optimized to determine the most effective combination of extraction temperature (20–50°C), extraction time (30–300 min), and solvent concentration (0–100% ethanol in water). Total phenolic content (TPC), flavonoid content (FC), and antioxidant activity (FRAP) of the obtained extracts were determined. The extracted compounds from untreated and PEF-treated samples at the optimal conditions were analyzed via HPLC-PDA analysis. Results revealed that, at a fixed extraction temperature (50°C), the application of PEF at optimal processing conditions (E = 3.8 kV/cm, WT = 10 kJ/kg) prior to SLE has the potential to reduce the solvent consumption (3–12%) and shorten the extraction time (23–103 min) to obtain the same recovery yield of phenolic compounds. Under optimized conditions, the extracts derived from PEF-treated samples showed significantly higher TPC (8%), FC (31%), and FRAP (36%) values, as compared to the control extraction. HPLC analyses revealed that epicatechin, p-coumaric acid, and quercetin were among the main phenolic compounds extracted, and no degradation phenomena occurred due to PEF application.
Mathematica Bohemica

Two-scale convergence is a powerful mathematical tool in periodic homogenization developed for modelling media with periodic structure. The contribution deals with the classical definition, its problems, the “dual” definition based on the so-called periodic unfolding. Since in the case of domains with boundary the unfolding operator introduced by D.Cioranescu, A.Damlamian, G.Griso does not satisfy the crucial integral preserving property, the contribution proposes a modified unfolding operator which satisfies the property and thus simplifies the theory. The properties of two-scale convergence are surveyed.
Novel Sensing Techniques for Lithium-ion Battery Modeling and States Estimation

Executive Summary The increasing dependence on batteries calls for the accurate monitoring of battery functional status to increase their quality, reliability, and life. This has led to a variety of ingenious approaches developed over the years, among which the utilization of novel sensors is attracting increasing attention. Rather than summarizing all relevant previous work in novel sensing-based battery states monitoring, this paper selects noteworthy work that may suggest crucial future trends of applying novel sensing techniques to enhance the physics-guided functionalities in the battery management system. With ultrasonic sensors as an example, their working principles and general application in non-destructive detection are introduced. The ultrasonic evaluation for a commercial lithium-ion pouch cell is performed. The experiment results show that features from ultrasonic measurements could be potential parameters to determine the battery state-of-charge. The discussion presented herein is expected to induce a more fluent exchange of ideas and more intense interest in this emerging field. Future studies will present more on novel sensors and their benefits, drawbacks, possibilities and applications in battery domain.
UvA-DARE (Digital Academic Repository) Engaging with TV events on Twitter

Purpose – The purpose of this paper is to explore the interrelationship between television (TV) consumption (viewing ratings), engagement behaviors of different actors on Twitter (TV programs, media, celebrities and viewers) and the content of engagement behaviors (affective, program-related and social content). Design/methodology/approach – TV ratings and Twitter data were obtained. The content of tweets was analyzed by means of a sentiment analysis. A vector auto regression model was used to understand the interrelationship between tweets of different actors and TV consumption. Findings – First, the results showed a negative interrelationship between TV viewing and viewers ’ tweeting behavior. Second, tweets by celebrities and media exhibited similar patterns and were both affected mostly by the number of tweets by viewers. Finally, the content of tweets matters. Affective tweets positively relate to TV viewing, and program-related and social content positively relates to the number of tweets by viewers. Research limitations/implications – The findings help us understand the online engagement ecosystem and provide insights into drivers of TV consumption and online engagement of different actors. Practical implications – The results indicate that content producers may want to focus on stimulating affective conversations on Twitter to trigger more online and offline engagement. The results also call for rethinking the meaning of TV metrics. Originality/value – While some studies have explored viewer interactions on Twitter, only a few studies have looked at the effects of such interactions on variables outside of social media, such as TV consumption. Moreover, the authors study the interrelations between Twitter interactions with TV consumption, which allows us to examine the effect of online engagement on offline behaviors and vice versa. Finally, the authors take different actors into account when studying real-life online engagement.