Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of morphology on spelling and reading accuracy: a study on Italian children

In opaque orthographies knowledge of morphological information helps in achieving reading and spelling accuracy. In transparent orthographies with regular print-to-sound correspondences, such as Italian, the mappings of orthography onto phonology and phonology onto orthography are in principle sufficient to read and spell most words. The present study aimed to investigate the role of morphology in the reading and spelling accuracy of Italian children as a function of school experience to determine whether morphological facilitation was present in children learning a transparent orthography. The reading and spelling performances of 15 third-grade and 15 fifth-grade typically developing children were analyzed. Children read aloud and spelled both low-frequency words and pseudowords. Low-frequency words were manipulated for the presence of morphological structure (morphemic words vs. non-derived words). Morphemic words could also vary for the frequency (high vs. low) of roots and suffixes. Pseudo-words were made up of either a real root and a real derivational suffix in a combination that does not exist in the Italian language or had no morphological constituents. Results showed that, in Italian, morphological information is a useful resource for both reading and spelling. Typically developing children benefitted from the presence of morphological structure when they read and spelled pseudowords; however, in processing low-frequency words, morphology facilitated reading but not spelling. These findings are discussed in terms of morpho-lexical access and successful cooperation between lexical and sublexical processes in reading and spelling.
Antihyperlipidemic Activity of Aloe succotrina in Rats: Possibly Mediated by Inhibition of HMG-CoA Reductase

The present study was designed to investigate antihyperlipidemic activity of dried pulp of Aloe succotrina leaves in Wistar albino rats. Hyperlipidemia was induced in rats by feeding them high fat diet (HFD) or D-fructose (25% w/v) for 4 successive weeks. From 15th to 28th day, dried pulp (100 and 200 mg/kg, p.o) and atorvastatin (10 mg/kg, p.o.) per se were administered 2 h prior to feeding rats with HFD or fructose. Aloe succotrina did not significantly decrease the body weight of rats. The dried pulp and atorvastatin per se significantly decreased relative liver weight but did not significantly affect relative heart weight. HFD or fructose significantly increased serum total cholesterol, triglycerides, LDL-c, and VLDL, and decreased HDL-c; significantly increased liver MDA and decreased GSH levels. The dried pulp (200 mg/kg p.o.) significantly reversed high fat diet-induced and fructose-induced hyperlipidemia and atherogenic index. Aloe succotrina significantly decreased HMG Co-A reductase activity. Antihyperlipidemic effect of the dried pulp was comparable to atorvastatin. Thus, Aloe succotrina produced significant antihyperlipidemic activity in both HFD and fructose-induced hyperlipidemic rats, possibly through normalization of serum lipid profile, HMG-CoA reductase inhibitory activity, and amelioration of oxidative stress in liver.
Performance comparison of different element shapes used in printed reflectarrays

A systematic study of the performance of reflectarrays with different element shapes is presented. The reflection properties of the printed elements versus their geometrical dimensions are calculated by using the method of moments (MoM)/boundary integral-resonant mode expansion (BI-RME) method, which permits the analysis of arbitrarily shaped elements. In order to compare the element performance, four parameters are defined as "figures of merit": the range of the reflection phase; the sensitivity to fabrication tolerances; the bandwidth; the cross-polarization level. Both classical (e.g., rectangles and rectangles with tuning stubs) and novel element shapes (e.g., ridge, dogbone) are considered in the case of single-layer structures; the novel proposed shapes exhibit a good tradeoff of all the figures of merit. Double-layer structures are also analyzed, which prove their superior performance at the cost of an increased fabrication complexity.
A Soluble Fucose-Specific Lectin from Aspergillus fumigatus Conidia - Structure, Specificity and Possible Role in Fungal Pathogenicity

Aspergillus fumigatus is an important allergen and opportunistic pathogen. Similarly to many other pathogens, it is able to produce lectins that may be involved in the host-pathogen interaction. We focused on the lectin AFL, which was prepared in recombinant form and characterized. Its binding properties were studied using hemagglutination and glycan array analysis. We determined the specificity of the lectin towards l-fucose and fucosylated oligosaccharides, including α1-6 linked core-fucose, which is an important marker for cancerogenesis. Other biologically relevant saccharides such as sialic acid, d-mannose or d-galactose were not bound. Blood group epitopes of the ABH and Lewis systems were recognized, LeY being the preferred ligand among others. To provide a correlation between the observed functional characteristics and structural basis, AFL was crystallized in a complex with methyl-α,l-selenofucoside and its structure was solved using the SAD method. Six binding sites, each with different compositions, were identified per monomer and significant differences from the homologous AAL lectin were found. Structure-derived peptides were utilized to prepare anti-AFL polyclonal antibodies, which suggested the presence of AFL on the Aspergillus’ conidia, confirming its expression in vivo. Stimulation of human bronchial cells by AFL led to IL-8 production in a dose-dependent manner. AFL thus probably contributes to the inflammatory response observed upon the exposure of a patient to A. fumigatus. The combination of affinity to human epithelial epitopes, production by conidia and pro-inflammatory activity is remarkable and shows that AFL might be an important virulence factor involved in an early stage of A. fumigatus infection.
Role of the Contralateral Inferior Frontal Gyrus in Recovery of Language Function in Poststroke Aphasia: A Combined Repetitive Transcranial Magnetic Stimulation and Positron Emission Tomography Study

Background and Purpose— Functional neuroimaging studies have demonstrated right inferior frontal gyrus (IFG) activation in poststroke aphasia. It remains unclear whether this activation is essential for language performance. We tested this hypothesis in a positron emission tomography (PET) activation study during a semantic task with repetitive transcranial magnetic stimulation (rTMS) on right-handed patients experiencing poststroke aphasia and examined whether rTMS stimulation over the right and left IFG would interfere with language performance. Methods— Eleven patients with left-sided middle cerebral arterial infarction, 50 to 75 years of age, were tested with the Aachen Aphasia Test Battery and underwent 15O-H2O PET activation during a semantic task within 2 weeks after stroke. PET activation images were coregistered to T1-weighted MRIs. Stimulation sites were determined on renderings of head and brain over the maximum activation within left and right IFG. rTMS was performed with 20% maximum output (2.1 T), 10-s train duration, at 4Hz frequency. A positive rTMS effect was defined as an increased reaction time latency or error rate in the semantic task. Results— PET activations of the IFG were observed on the left (3 patients) and bilaterally (8 patients). Right IFG stimulation was positive in 5 patients with right IFG activation, indicating essential language function. In a verbal fluency task, these patients had a lower performance than patients without right-sided TMS effect. Conclusions— In some poststroke aphasics, right IFG activation is essential for residual language function. However, its compensatory potential seems to be less effective than in patients who recover left IFG function. These results suggest a hierarchy in recovery from poststroke aphasia and a (limited) compensatory potential of the nondominant hemisphere.
GTA-Net: A Robust Method for Deepfake Face Image Detection

The rapid advancement of artificial intelligence technology has resulted in the emergence of deepfake, which has had a significant impact on various fields due to its realistic effects. Addressing the challenges posed by deepfake has become a crucial area of research. In this study, we propose a two-stream network framework, GTA-Net, for the detection of deepfake face images. The framework comprises a Global Residual Attention module (GRA), a Texture Feature Saliency module (TFS), and an Attention Feature Fusion module (AFF). We incorporate Local Binary Patterns (LBP) features into the network input to guide the decision-making process of the model towards prominent texture features, thereby enhancing detection accuracy. Additionally, we employ a residual attention mechanism to focus on specific deepfake-generated features and improve robustness by avoiding interference from content-preserving manipulations. Experimen-tal results show that the proposed method has high detection accuracy and strong robustness against degraded datasets, and generalization for cross-dataset detection.
The Cauchy–Schwarz Divergence for Poisson Point Processes

In this paper, we extend the notion of Cauchy-Schwarz divergence to point processes and establish that the Cauchy-Schwarz divergence between the probability densities of two Poisson point processes is half the squared L2-distance between their intensity functions. Extension of this result to mixtures of Poisson point processes and, in the case where the intensity functions are Gaussian mixtures, closed form expressions for the Cauchy-Schwarz divergence are presented. Our result also implies that the Bhattacharyya distance between the probability distributions of two Poisson point processes is equal to the square of the Hellinger distance between their intensity measures. We illustrate the result via a sensor management application where the system states are modeled as point processes.
Qualitative Change from Quantitative Change: Mathematical Catastrophe Theory in Relation to Psychoanalysis

The relation of qualitative change to quantitative change is important to psychoanalytic theory. Until recently no tools were available for dealing with the problem, but the development of catastrophe theory has provided methods for studying it. Psychoanalytic investigators might benefit from the methods of catastrophe theory, and dilemmas arising from the supposed impossibility of relating quantity to quality are seen to allow of solution.
Predicting lexical proficiency in language learner texts using computational indices

The authors present a model of lexical proficiency based on lexical indices related to vocabulary size, depth of lexical knowledge, and accessibility to core lexical items. The lexical indices used in this study come from the computational tool Coh-Metrix and include word length scores, lexical diversity values, word frequency counts, hypernymy values, polysemy values, semantic co-referentiality, word meaningfulness, word concreteness, word imagability, and word familiarity. Human raters evaluated a corpus of 240 written texts using a standardized rubric of lexical proficiency. To ensure a variety of text levels, the corpus comprised 60 texts each from beginning, intermediate, and advanced second language (L2) adult English learners. The L2 texts were collected longitudinally from 10 English learners. In addition, 60 texts from native English speakers were collected. The holistic scores from the trained human raters were then correlated to a variety of lexical indices. The researchers found that lexical diversity, word hypernymy values and content word frequency explain 44% of the variance of the human evaluations of lexical proficiency in the examined writing samples. The findings represent an important step in the development of a model of lexical proficiency that incorporates both vocabulary size and depth of lexical knowledge features.
Systematic Errors in South Asian Monsoon Simulation: Importance of Equatorial Indian Ocean Processes

AbstractForecasting monsoon rainfall using dynamical climate models has met with little success, partly due to models’ inability to represent the monsoon climatological state accurately. In this article the nature and dynamical causes of their biases are investigated. The approach is to analyze errors in multimodel-mean climatological fields determined from CMIP5, and to carry out sensitivity experiments using a coupled model [the Coupled Model for the Earth Simulator (CFES)] that does represent the monsoon realistically. Precipitation errors in the CMIP5 models persist throughout the annual cycle, with positive (negative) errors occurring over the near-equatorial western Indian Ocean (South Asia). Model errors indicate that an easterly wind stress bias Δτ along the equator begins during April–May and peaks during November; the severity of the Δτ is that the Wyrtki jets, eastward-flowing equatorial currents during the intermonsoon seasons (April–May and October–November), are almost eliminated. An erroneo.
On Boundary Recognition without Location Information in Wireless Sensor Networks

Boundary recognition is an important and challenging issue in wireless sensor networks when no coordinates or distances are available. The distinction between inner and boundary nodes of the network can provide valuable knowledge to a broad spectrum of algorithms. This paper tackles the challenge of providing a scalable and range-free solution for boundary recognition that does not require a high node density. Our solution approximates the boundary of the sensor network by determining the inner nodes using geometric constructions that guarantee that, for a given d, a node lies inside of the construction for a d-quasi unit disk graph model of the wireless sensor network. Moreover, such geometric constructions make it possible to compute a guaranteed distance from a node to the boundary. We provide a thorough evaluation of our approach and show that it is applicable to dense as well as sparse deployments.
URBAN DEVELOPMENT IN OMAN: AN OVERVIEW

During the past two decades, the Gulf countries have experienced the most rapid urban growth in the world. The traditional societies in this region have been guilelessly opened on the market economy and western lifestyle. In spite the progress realized at many levels, these societies became victims of its consumerist style. This article aims to present an overview of the urban development in Oman since it started its ‘modernization’. This study is not only interested in how the country has been developing since its “renaissance” in the 1970s, but also how does this development appear, compared to its traits in the neighboring Gulf countries. Based on the assumption that urban research is a tool of analysis that can enlighten future decisions and actions in the domain of urban development, this study is also a critical review of the published research about the urbanization in Oman since the 1970s. This research showed that, although it shares several aspects with what the other Gulf cities have witnessed, urbanization in Oman was slower, less drastic and relatively more controlled. The scrutiny of the published research on this topic also revealed that the urban studies about Oman, and the GCC countries in general, were insignificant before the rise of leading cities such as Dubai, then Doha, to the international scene. It concluded that even if these urban studies have progressively broadened in their topics, disciplines and case studies, their effect on the new orientations chosen for the future developments in these countries remains negligible.
Ecological Determinants of Highly Pathogenic Avian Influenza (H5N1) Outbreaks in Bangladesh

Background The agro-ecology and poultry husbandry of the south Asian and south-east Asian countries share common features, however, with noticeable differences. Hence, the ecological determinants associated with risk of highly pathogenic avian influenza (HPAI-H5N1) outbreaks are expected to differ between Bangladesh and e.g., Thailand and Vietnam. The primary aim of the current study was to establish ecological determinants associated with the risk of HPAI-H5N1 outbreaks at subdistrict level in Bangladesh. The secondary aim was to explore the performance of two different statistical modeling approaches for unmeasured spatially correlated variation. Methodology/Principal Findings An ecological study at subdistrict level in Bangladesh was performed with 138 subdistricts with HPAI-H5N1 outbreaks during 2007–2008, and 326 subdistricts with no outbreaks. The association between ecological determinants and HPAI-H5N1 outbreaks was examined using a generalized linear mixed model. Spatial clustering of the ecological data was modeled using 1) an intrinsic conditional autoregressive (ICAR) model at subdistrict level considering their first order neighbors, and 2) a multilevel (ML) model with subdistricts nested within districts. Ecological determinants significantly associated with risk of HPAI-H5N1 outbreaks at subdistrict level were migratory birds' staging areas, river network, household density, literacy rate, poultry density, live bird markets, and highway network. Predictive risk maps were derived based on the resulting models. The resulting models indicate that the ML model absorbed some of the covariate effect of the ICAR model because of the neighbor structure implied in the two different models. Conclusions/Significance The study identified a new set of ecological determinants related to river networks, migratory birds' staging areas and literacy rate in addition to already known risk factors, and clarified that the generalized concept of free grazing duck and duck-rice cultivation interacted ecology are not significant determinants for Bangladesh. These findings will refine current understanding of the HPAI-H5N1 epidemiology in Bangladesh.
An Improved YOLOv5 for High-Resolution Ore Image Detection

During ore dressing production, the size of the ore significantly affects the grinding and classification efficiency and is a crucial control parameter. In the past, most ore image detection algorithms focused on the detection tasks of high-resolution ore image. At the same time, due to the sparse data set for industrial production applications, the generalization ability and robustness of the model are low, and it has poor performance on tiny ore target detection tasks. To remedy these shortcomings, this paper proposes the ODA-YOLOv5 network model for ore image detection. In this paper, we adopt a multi-scale training strategy to address the difficulty of detecting tiny ores in high-resolution images. A self-built dataset is constructed by fusing multi-scale ore images. The input image size is dynamically adjusted during training to enhance the robustness of the detection model for ore of different scales. In order to improve the performance of the detection algorithm, we introduce the C3-ECA attention module, which fully takes into account the local cross-letter road interactions and considerably reduces the model complexity. Our algorithm achieves approximately 97.9% mAP and approximately 62.11 FPS on the self-built dataset. Our algorithm sufficiently demonstrates the superiority of our detection model algorithm for industrial ore detection.
The hierarchical structure of common Turkish person‐descriptive adjectives

Findings from analyses of self‐descriptions by 631 native speakers of Turkish, using 498 familiar Turkish person‐descriptive adjectives, are compared to those of Saucier (1997), who analyzed 500 familiar English adjectives. In the total item pools in both studies, variants of the English/German ‘Big‐Five’ factors were recovered, along with a broad Attractiveness factor and another factor composed of items of extremely low endorsement rates. Moreover, in both studies when the item pools were restricted to terms that are less pejorative and more clearly related to personality traits, again variants of the Big‐Five factors were recovered. These latter findings replicate those from Somer and Goldberg (1999), who analyzed Turkish synonym clusters rather than single person‐descriptive adjectives. We discuss some of the pitfalls of comparative studies of personality lexicons, and suggest some procedures for reconciling diverse findings. Copyright © 2000 John Wiley & Sons, Ltd.
Violence against wives, sexual risk and sexually transmitted infection among Bangladeshi men

Objective: To assess the relationship between men’s reported violence against wives and their sexual risk behaviours and sexual health. Design, setting and participants: Cross-sectional analyses of a survey of a nationally representative household-based sample of married men in Bangladesh (n = 3096). Main outcome measure(s): Physical and sexual violence against wives during the previous 12 months was assessed and examined for relations to men’s extramarital sexual behaviours and sexually transmitted infection (STI) symptoms or diagnosis during this same period, as well as to men’s disclosure of such infection to wives and condom use while infected. Results: More than 1 in 3 (36.84%) married Bangladeshi men reported physically and/or sexually abusing their wives in the past year. Men perpetrating such violence were more likely to report both premarital and extramarital sex partners (ORadjs 1.80–3.45; 95% CI 1.20 to 8.23); those reporting physical violence were more likely to report STI symptoms or diagnosis in the past year (ORadjs 1.68–2.52; 95% CI 1.24 to 3.73). Men perpetrating physical violence and contracting an STI were somewhat more likely to fail to disclose infection status to wives (ORadj 1.58; 95% CI 0.93 to 2.70) than infected men not reporting such abuse. Conclusions: Violence against wives is common among Bangladeshi men. Men who perpetrate such abuse represent increased risk regarding their wives’ sexual health because they are more likely to both participate in extramarital sexual behaviour and contract an STI compared with non-abusive husbands. Given the growing epidemic of HIV infection among monogamous South Asian women based on intercourse with infected non-monogamous husbands, research and intervention regarding men’s violence in marriage and implications of such behaviour for women’s sexual health should be prioritised.
Profit-Seeking Punishment Corrupts Norm Obedience

Punishment typically involves depriving violators of resources they own such as money or labor. These resources can become revenue for authorities and thus motivate profit-seeking punishment. In this paper, we design a novel experiment to provide direct evidence on the role punishment plays in communicating norms. Importantly, this allows us to provide experimental evidence indicating that if people know that enforcers can benefit monetarily by punishing, they no longer view punishment as signaling a norm violation. The result is a substantial degradation of punishmentʼs ability to influence behavior. Our findings draw attention to the detrimental effect of profit-seeking enforcement on the efficacy of punishment.