Miracle-dz/UniFAR-FTUs huggingface dataset:
Advertising: A Case for Intersemiotic Translation

In the world of the printed page, pictures and graphic layout are generally taken to be mere complements or exemplifications of the verbal part of the text. This is not only against the principles of semiotics, it is against the very rules of communication, as the text is not perceived by the reader as a sum of different dimensions (i.e., verbal, visual, tactile, etc.) but as a whole where all components are connected and interdependent. Thus, splitting a text into its several dimensions is a completely artificial procedure that should be carried out for analytical purposes only, since all components of a text, as well as their interplay and the interplay of the text with its context and co-text, contribute to the construction of meaning. This cannot be ignored by translators and should be made clear to any client who may think that the act of translation is by definition limited to the verbal dimension, and may go as far as submitting texts for translation without providing briefs about the visual elements they will be “complemented” with, or the graphic conventions that will be adopted in the final version. The translation – or localization – of advertisements is a case in point. The visual component plays a prominent role in most forms of advertising, particularly so in magazine ads; developing the pictorial and graphic aspects of a campaign, however these might appear “casual,” is a time-consuming and expensive process. If the translator (or localizer) is responsible for the text resulting from his/her work, then, he/she cannot ignore its visual dimension, and should be prepared to suggest modifications not only to the verbal part of the text, but also to its many other dimensions, in a holistic, intersemiotic perspective. Real-life examples, not only from advertising but also from editorial translation, will be provided to support this argument.
The Compound Poisson Risk Model with Interest and a Threshold Strategy

We consider the compound Poisson risk model with a constant force of interest and a threshold strategy. Under such a strategy, no dividends are paid if the insurer's surplus is below a certain threshold level. When the surplus is above the threshold level, part of the premium income and all of the interest income are paid out as dividends. The integro-differential equations for the Gerber–Shiu discounted penalty function and the expected discounted dividends are derived and solved. Closed-form expressions are given when the claim size is exponentially distributed. Numerical presentations are also provided for the case of exponential individual claim to illustrate the influence of force of interest and the safety loading on the expected discounted dividends.
Quality of Life and Family Impact in Down Syndrome, Autism Spectrum Disorder, and Co-occurring Down Syndrome and Autism Spectrum Disorder

This article has supplementary material on the web site: www.jdbp. org. Abstract: Objective: Families of children with neurodevelopmental disorders have developmental, behavioral, and social-emotional needs that affect quality of life (QoL). This study assesses the validity and utility of a caregiver QoL measure; characterizes QoL in families with children with Down syndrome (DS), autism spectrum disorder (ASD), and a dual diagnosis of DS and ASD (DS + ASD); and compares and explores differences in QoL based on diagnosis. Methods: Caregivers of children and adolescents with ASD (n = 610) and DS (n = 177) completed the Pediatric Quality of Life Inventory Family Impact Module 2.0, yielding overall, parent functioning, family functioning, and subscale scores, and a Parent Global Impression (PGI) rating. An ASD cohort (n = 177) was sex matched to the DS cohort (n = 177) to mitigate potential sex bias. Additional analyses compared these groups with children and adolescents with DS + ASD (n = 37). Results: Analyses showed that the Pediatric Quality of Life Inventory was valid and reliable in DS, ASD, and DS + ASD populations. No differences were reported in PGI ratings among groups. Caregivers in the DS group demonstrated higher QoL and family functioning compared with the ASD and DS + ASD groups. The DS group reported significantly better Emotional Functioning and Communication and less Worry than the ASD group. Compared with the ASD group, caregivers of the DS + ASD group indicated more concerns with Physical Functioning. Notably, the DS + ASD group had significantly lower levels of QoL than the DS group in nearly all caregiver functioning domains. Conclusion: This study highlights differences in QoL within and between neurodevelopmental disorder groups, which may help identify families requiring additional support, advocacy, and community engagement.
Edge-elements for scattering problems

It is shown that edge elements, as vectorial finite-element approximations fields like e and h, can be used to solve scattering problems. This can be done in essentially two ways, according to which of the two fields d or b one most wishes to get in divergence-free form. Apparent drawback of edge elements (due to the increased number of degrees of freedom in comparison with nodal elements) are more than compensated by economies due to greater sparsity. Moreover, they could help get rid of unwanted spurious modes when resonance frequencies of waveguides of complicated shape are computed. >
Asymptotic modal analysis and statistical energy analysis of dynamical systems

The well known text by Lyon on Statistical Energy Analysis (SEA) [R. H. Lyon, Statistical Energy Analysis of Dynamical Systems: Theory and Applications (MIT Press, Cambridge, MA, 1975)] is the standard reference on the subject. As originally conceived SEA was based upon several plausible hypotheses. Various authors have considered the underlying basis for SEA and thereby advanced our understanding of it. In the present paper, the relationship between classical modal analysis (CMA) and SEA is studied. It is shown how the results of SEA may be obtained as an asymptotic limit of CMA. The present work only considers the response of a single general linear structure under a random or sinusoidal load. However future plans will consider (a) the structural acoustic response of an enclosure bounded by a flexible wall and excited by external forces and (b) two (or more) coupled structural systems. Here the emphasis is on (1) a new derivation of the SEA results from CMA for a single structure under a random load, (2) the generalization of the usual SEA result to show that, asymptotically, all points on the structure have the same response. In the literature this is sometimes invoked as an assumption. Here the result is derived as part of the asymptotic limit of CMA. (3) A numeriCal example which displays the manner in which the asymptotic limit is approached for random loading and (4) an extension of the usual SEA result for sinusoidal loading. In view of the above, the present results might be called more appropriately Asymptotic Modal Analysis (AMA) rather than SEA.
Evaluation and Bias Correction of Regional Climate Model Results Using Model Evaluation Measures

AbstractFor the assessment of regional climate change the reliability of the regional climate models needs to be known. The main goal of this paper is to evaluate the quality of climate model data that are used for impact research. Temperature, precipitation, total cloud cover, relative humidity, and wind speed simulated by the regional climate models Climate Local Model (CLM) and Regional Model (REMO) are evaluated for the metropolitan region of Hamburg in northern Germany for the period 1961–2000. The same evaluation is performed for the global climate model ECHAM5 that is used to force the regional climate models. The evaluation is based on comparison of the simulated and observed climatological annual cycles and probability density functions of daily averages. Several model evaluation measures are calculated to assure an objective model evaluation. As a very selective model evaluation measure, the hit rate of the percentiles is introduced for the evaluation of daily averages. The influence of interann.
Osmoregulatory Performance among Prickly Sculpin (Cottus asper) Living in Contrasting Osmotic Habitats

During the colonization of freshwater by marine fish, adaptation to hypoosmotic conditions may impact their ability to osmoregulate in seawater. The prickly sculpin (Cottus asper) is a euryhaline fish with marine ancestors that postglacially colonized many freshwater habitats. Previous work on C. asper suggested that isolation in freshwater habitats has resulted in putative adaptations that improve ion regulation in freshwater populations compared with populations with current access to estuaries. To determine whether long-term colonization of freshwater is associated with a reduced ability to ion regulate in seawater, we acclimated C. asper populations from three habitat types that vary in the extent to which they are isolated from marine habitats and compared their seawater osmoregulation. Seawater acclimation revealed that lake populations exhibited a reduced capacity to osmoregulate in seawater compared with coastal river populations with ongoing access to estuaries. In particular, when acclimated to seawater for several weeks, lake populations had lower gill Na+/K+-ATPase activity and lower intestinal H+-ATPase activity than coastal river populations. Lake populations also had a reduced ability to maintain plasma ion concentrations, and they produced lower quantities of intestinal carbonate precipitates in seawater than coastal river populations. Furthermore, there was a positive relationship between the anterior intestinal Na+/K+-ATPase activity and the amount of precipitate produced by the intestine, which suggests that the anterior intestine plays a role in seawater osmoregulation. Our results suggest that the extent of isolation from the sea could, in part, explain the reduced osmoregulation in seawater in postglacial freshwater populations of C. asper.
Hausdorff dimension of hairs and ends for entire maps of finite order

Abstract We study transcendental entire maps f of finite order, such that all the singularities of f−1 are contained in a compact subset of the immediate basin B of an attracting fixed point of f. Then the Julia set of f consists of disjoint curves tending to infinity (hairs), attached to the unique point accessible from B (endpoint of the hair). We prove that the Hausdorff dimension of the set of endpoints of the hairs is equal to 2, while the union of the hairs without endpoints has Hausdorff dimension 1, which generalizes the result for exponential maps. Moreover, we show that for every transcendental entire map of finite order from class (i.e. with bounded set of singularities) the Hausdorff dimension of the Julia set is equal to 2.
Exemplar-Based Sparse Representations for Detection of Parkinson's Disease From Speech

Parkinson's disease (PD) is a progressive neurological disorder which affects the motor system. The automatic detection of PD improves the diagnosis of the disease, and it can be done in a non-invasive manner from speech. In this paper, we investigate the use of an exemplar-based sparse representation (SR) classification approach for detecting PD from speech. Exemplars are speech feature vectors extracted from the training data. The idea is to formulate the detection task as a problem of finding sparse representations of test speech feature vectors with respect to training speech exemplars. The main advantage of using the SR approach instead of conventional machine learning (ML)-based approaches is that the training step–which is time-consuming and sometimes requires unorganized hyper-parameter tuning–is not needed. Furthermore, SRs are more robust to redundancy and noise in the data. In this work, we study SR classification approaches based on two sparse coding models, namely, l1-regularized least squares (<inline-formula><tex-math notation="LaTeX">$l_{1}$</tex-math></inline-formula>LS) and non-negative least squares (NNLS). We propose a strategy based on class-specific dictionaries for improving performance of the <inline-formula><tex-math notation="LaTeX">$l_{1}$</tex-math></inline-formula>LS- and NNLS-based SR classification. To investigate the detection performance, the <inline-formula><tex-math notation="LaTeX">$l_{1}$</tex-math></inline-formula>LS- and NNLS-based approaches are applied and compared with the traditional PD detection approach based on ML classification algorithms using the PC-GITA PD dataset and an openly available dataset consisting of mobile device voice recordings from healthy and PD patients. The results indicate that the proposed NNLS-based SR classification approach performs better than the traditional ML-based methods in discriminating PD patients from healthy subjects.
Technical and Economic Irrigation Potentials Within Land and Water Boundaries

To satisfy the increasing global demand for agricultural products, the expansion of irrigation is an important intensification measure. At the same time, unsustainable water abstractions and cropland expansion pose a threat to biodiversity and ecosystem functioning. Irrigation potentials are influenced by local biophysical irrigation water availability and competition of different water users. Using a novel hydro‐economic data processing routine that considers economic criteria of water allocation via a productivity ranking of grid cells and both land and water sustainability criteria, we estimate global irrigation potentials at a 0.5° spatial resolution. We show that there is considerable technical potential to expand irrigation within local water and land boundaries. In terms of potentially irrigated areas on all global land suitable for crop production, 2,144 Mha could be irrigated within land and water environmental boundaries when only considering biophysical criteria. However, not all of these areas would actually be irrigated under consideration of irrigation costs. Of these, only 698 Mha (330 Mha) have a yield gain of more than 300 (600) USD ha−1 under the current crop mix valued at their current commodity price (economic irrigation potential).
Pregnancy in Chronic Kidney Disease

While pregnancy among end-stage kidney disease patients is rare, the number of females becoming pregnant has been increasing worldwide during the last decade. The frequency of conception in this patient group has been reported to be between 0.3% and 7% per year. The aim of this review is to summarize the latest guidelines and practice points for ensuring the best outcome for both the fetus and the mother.
Controllability and observability of a class of linear time-invariant system with interval plants

The authors is con cerned with problem of sufficient conditions for the controllability and the observability of multi input/multi output linear time invariant systems with parameter uncertaingy:=Ax+Bu y=Cx(A,B,C) are confined with a bounded closed set.The main choracteristics of this tert is to adopt a method of matrix iequacitg so as to deal coith this question.The purpose of this tert is to establish a sufficient conditon for such.
The Neural Signatures of Shame, Embarrassment, and Guilt: A Voxel-Based Meta-Analysis on Functional Neuroimaging Studies

Self-conscious emotions, such as shame and guilt, play a fundamental role in regulating moral behaviour and in promoting the welfare of society. Despite their relevance, the neural bases of these emotions are uncertain. In the present meta-analysis, we performed a systematic literature review in order to single out functional neuroimaging studies on healthy individuals specifically investigating the neural substrates of shame, embarrassment, and guilt. Seventeen studies investigating the neural correlates of shame/embarrassment and seventeen studies investigating guilt brain representation met our inclusion criteria. The analyses revealed that both guilt and shame/embarrassment were associated with the activation of the left anterior insula, involved in emotional awareness processing and arousal. Guilt-specific areas were located within the left temporo-parietal junction, which is thought to be involved in social cognitive processes. Moreover, specific activations for shame/embarrassment involved areas related to social pain (dorsal anterior cingulate and thalamus) and behavioural inhibition (premotor cortex) networks. This pattern of results might reflect the distinct action tendencies associated with the two emotions.
Soy Isoflavones Induce Cell Death by Copper-Mediated Mechanism: Understanding Its Anticancer Properties

Cancer incidence varies around the globe, implying a relationship between food and cancer risk. Plant polyphenols are a class of secondary metabolites that have recently attracted attention as possible anticancer agents. The subclass of polyphenols, known as isoflavones, includes genistein and daidzein, which are present in soybeans and are regarded as potent chemopreventive agents. According to epidemiological studies, those who eat soy have a lower risk of developing certain cancers. Several mechanisms for the anticancer effects of isoflavones have been proposed, but none are conclusive. We show that isoflavones suppress prostate cancer cell growth by mobilizing endogenous copper. The copper-specific chelator neocuproine decreases the apoptotic potential of isoflavones, whereas the iron and zinc chelators desferroxamine mesylate and histidine do not, confirming the role of copper. Reactive oxygen species (ROS) scavengers reduce isoflavone-induced apoptosis in these cells, implying that ROS are cell death effectors. Our research also clearly shows that isoflavones interfere with the expression of the two copper transporter genes, CTR1 and ATP7A, in cancerous cells. Copper levels are widely known to be significantly raised in all malignancies, and we confirm that isoflavones can target endogenous copper, causing prooxidant signaling and, eventually, cell death. These results highlight the importance of copper dynamics within cancer cells and provide new insight into the potential of isoflavones as cancer-fighting nutraceuticals.
Iron Limitation Restores Autophagy and Increases Lifespan in the Yeast Model of Niemann–Pick Type C1

Niemann–Pick type C1 (NPC1) is an endolysosomal transmembrane protein involved in the export of cholesterol and sphingolipids to other cellular compartments such as the endoplasmic reticulum and plasma membrane. NPC1 loss of function is the major cause of NPC disease, a rare lysosomal storage disorder characterized by an abnormal accumulation of lipids in the late endosomal/lysosomal network, mitochondrial dysfunction, and impaired autophagy. NPC phenotypes are conserved in yeast lacking Ncr1, an orthologue of human NPC1, leading to premature aging. Herein, we performed a phosphoproteomic analysis to investigate the effect of Ncr1 loss on cellular functions mediated by the yeast lysosome-like vacuoles. Our results revealed changes in vacuolar membrane proteins that are associated mostly with vesicle biology (fusion, transport, organization), autophagy, and ion homeostasis, including iron, manganese, and calcium. Consistently, the cytoplasm to vacuole targeting (Cvt) pathway was increased in ncr1∆ cells and autophagy was compromised despite TORC1 inhibition. Moreover, ncr1∆ cells exhibited iron overload mediated by the low-iron sensing transcription factor Aft1. Iron deprivation restored the autophagic flux of ncr1∆ cells and increased its chronological lifespan and oxidative stress resistance. These results implicate iron overload on autophagy impairment, oxidative stress sensitivity, and cell death in the yeast model of NPC1.
User-Context Collaboration and Tensor Factorization for GNN-Based Social Recommendation

One goal of social recommendation is to utilize social information to alleviate data sparsity and improve recommendation accuracy. User social relationships are inherently graph-structured, graph neural network (GNN) has recently attracted extensive attention in social recommendation because of its capability to integrate structural information and topology. However, current graph neural network (GNN)-based social recommendation models fail to consider context information during user interactions, which hinders more accurate modeling of user interest features. To address this problem, we propose a new social recommendation model based on context-aware graph neural network named CENTRIC (User-ContExt CollaboratioN and TensoR Factorization for GNN-based SocIal ReCommendation). Specifically, first a multi-channel GNN model with user-context collaboration module is designed, so that context can directly affect user features and participate in the calculation of user interaction probability with items. Then tensor factorization is adopted in output layer to effectively fuse the features extracted from different channels. Experiments on three public datasets show that CENTRIC significantly outperforms other state-of-the-art social recommendation models, further experiments also demonstrate that context information and tensor factorization help improve the accuracy of GNN-based social recommendation.
The Allocative Efficiency Analysis of Special Allocation Fund for Road Sector in 2015-2019

Indonesia, as an archipelago, requires connectivity infrastructures to ease mobility and equitable development. However, the current condition has not reflected a decent quality of road infrastructure. The road sector's special allocation funds are the main instrument for financing local road infrastructure development following national priorities. Departs from this, the study analyzes the extent to which the allocation for the Road Sector in 2015- 2019 complied with the Allocative Efficiency principles as part of the public expenditure management (PEM) framework. The research uses a postpositivism approach with primary data analysis (in-depth interviews) and secondary data in literature reviews, regulatory reviews, and descriptive statistics. The study concluded that the 2015-2019 allocation was not optimally in line with priority-based allocations, a weak medium-term budgeting perspective, poor consolidation within the local autonomy, and several contradictions among regulations. Even though there are several weaknesses in the practice of implementing allocative efficiency principles, the Government's strong commitment is reflected in the Cabinet Review annually and the planned issuance of the Presidential Instruction of Regional Roads. This study brought practical recommendations highlighting the need to sharpen priority targets and recipients, adopt the medium-term expenditure framework (MTEF), and regulatory harmonization. In addition, it is essential to revamp the structure of regional capital spending and the need to accommodate roads in the Minimum Standards Services.