Miracle-dz/UniFAR-FTUs huggingface dataset:
SemIE: Semantically-aware Image Extrapolation

We propose a semantically-aware novel paradigm to perform image extrapolation that enables the addition of new object instances. All previous methods are limited in their capability of extrapolation to merely extending the already existing objects in the image. However, our proposed approach focuses not only on (i) extending the already present objects but also on (ii) adding new objects in the extended region based on the context. To this end, for a given image, we first obtain an object segmentation map using a state-of-the-art semantic segmentation method. The, thus, obtained segmentation map is fed into a network to compute the extrapolated semantic segmentation and the corresponding panoptic segmentation maps. The input image and the obtained segmentation maps are further utilized to generate the final extrapolated image. We conduct experiments on Cityscapes and ADE20K-bedroom datasets and show that our method outperforms all baselines in terms of FID, and similarity in object co-occurrence statistics. Project url: https://semie-iccv.github. io/
A Misdiagnosed Case of Schizoaffective Disorder With Bipolar Manifestations

Bipolar and schizoaffective disorders are both psychiatric illnesses that share common traits, but also significant differences. Due to the close overlap in symptoms, obtaining the correct diagnosis can be difficult. The management of these patients often poses a challenge to clinicians. Five years ago, our patient was misdiagnosed with bipolar disorder with psychotic features. It was later discovered that she was suffering from schizoaffective disorder, bipolar type. The schizoaffective disorder involves symptoms of both schizophrenia and mood disorder.
Is nutritional status associated with depression? evidence from a cross-sectional study among workers in tertiary educational institutions in Southwestern Nigeria

Introduction different studies have shown a relationship between depression and nutrition, but there seems to be no consistent consensus on this. This study therefore investigated the relationship of nutrition status and depression among workers in tertiary educational institutions in Southwestern Nigeria. Methods this was a cross-sectional study conducted among 399 members of staff of three tertiary educational institutions in Osun State, Southwestern Nigeria. Depression was assessed using the Patient Health Questionnaire-9 (PHQ-9), while nutritional status was assessed using the body mass index (BMI), waist circumference and waist hip ratio (WHR). The respondents were selected using multi-stage sampling technique, and data were collected using pre-tested structured questionnaires. Analysis was done using IBM SPSS. Results the mean age of the respondents was 45.8 ± 10.4 years. The prevalence of depression was 23.8%. Concerning the nutritional status of respondents, 2.3% were underweight and 69.7% were overweight/obese. There were statistically significant associations between depression and the nutritional status of the respondents using BMI (p = 0.001), WHR (p = 0.015) and waist circumference (p = 0.036). After controlling for other factors, only the BMI was still significantly associated with depression, such that those underweight were more likely to be depressed (Odds ratio: 7.9; p-value: 0.009). Conclusion the prevalence of depression among the respondents was relatively high, and this was significantly associated with the BMI, even after controlling for co-founders.
The Effect of Spectacle-Induced Low Myopia in the Non-Dominant Eye on the Binocular Defocus Curve with a Non-Diffractive Extended Vision Intraocular Lens

Purpose To quantify the changes in the binocular defocus curve associated with the Vivity™ non-diffractive extended vision intraocular lens when the dominant eye was targeted for emmetropia and the non-dominant eye was artificially targeted for slight myopia using spectacles. Patients and Methods This was a non-interventional research study of the corrected binocular defocus curve associated with binocular emmetropia (Setting A) and with emmetropia in the dominant eye and two different levels of myopia simulated in the non-dominant eye (−0.50 D, Setting B and −1.00 D, Setting C). Subjects were patients implanted with the AcrySof® IQ Vivity® intraocular lens in both eyes 3 to 12 months previously. Using the defocus data, the percentage of subjects with a continuous 2.5 D range of vision (distance to 40 cm) was calculated for various levels of minimum visual acuity (VA). Results Forty subjects were enrolled. The mean spherical equivalent refraction was −0.06 D ± 0.36 D, with 0.37 D ± 0.29 D of refractive cylinder. There was no statistically significant difference in the mean VA at −0.25 D or at −0.50 D vergences between the test Settings, but there was a statistically significant difference at all other vergences. Differences were particularly noticeable at −2.00 D, −2.50 D and −3.00 D, where higher myopia in the non-dominant eye yielded better binocular VA. A 2.5 D range of functional vision (20/25) was achieved by 38% of subjects at Setting A, 68% of subjects at Setting B and 85% of subjects at Setting C. At setting C, all but one subject (39/40, 97.5%) had a 2.5 D range of vision with a VA of 20/32 or better. Conclusion Significant gains in binocular near vision, with only a nominal effect on distance vision, can be achieved with the Vivity IOL by leaving the non-dominant eye of patients with 0.50 D or 1.00 D of myopia.
Al‐Doped ZnO Nanowires by Electrochemical Deposition for Selective VOC Nanosensor and Nanophotodetector

Nanomaterials for new nanosensor systems with selective detection of hazardous volatile organic compounds (VOCs) vapors are of great demand nowadays. In this paper, the use in nanosensors of electrochemically deposited (ECD) Al‐doped ZnO (ZnO:Al) nanowires (NWs) is reported. The NWs are characterized by micro‐Raman and optical measurements. Individual ZnO and ZnO:Al NWs are integrated into nanosensor devices for room temperature UV and gas sensing. It is shown that, compared to undoped ZnO NW with irreversible response, the doped ZnO:Al NWs have faster response (≈5 s) and recovery (≈55 s), as well as enhanced UV response (≈4.8, about 2 times higher). The room temperature gas sensing investigations demonstrate that an individual ZnO:Al NW can detect volatile organic compounds (VOCs) vapors such as 2‐propanol, n‐butanol and ethanol at room temperature with a relatively fast response time of ≈10 s and a reversible signal (the recovery time being 30–40 s). This shows the possibility to use it with further development as indoor air quality monitor.
Social Media in the Eye of Parents

The purpose of this study is to identify the views of parents about social media. In accordance with phenomenological research design, one of qualitative research methods, the data was collected with semi-structured interview questions developed by the researcher under the control of experts. In the determination of the work group of the study the criterion sampling was used. The data was collected by recording the interviews and analysed by using the content analysis. In the findings of the study, the opinions of the parents about the effects of social median on students’ behaviours were grouped as positive and negative behaviours. While parents stated that “gathering information about the lessons” and “positive shares” are important positive behaviours, students’ “wasting time” and “causing violence” were stated as negative behaviours. An important ratio of the parents stated that social media may improve students academically, however, more than half of the parents stated that social media could not improve students school success as students waste their time on social media and do not use it for educational purposes. According to parents, social media supports education by providing easiness to reach information and including so many sources. Causing waste of time and being exposed to undesirable content are accepted as obstacles to education. In order to have a more educative social media, parents suggest that we should raise awareness of using social media healthily. People should share more educational sources on social media and a mechanism to supervise social median must be developed.
Obesity and Race May Explain Differential Burden of White Matter Hyperintensity Load

Objective Compared to European Americans, research indicates that African Americans have higher white matter hyperintensity (WMH) load; however, the clinical and biological bases underlying this higher burden are poorly understood. We hypothesize that obesity may explain differences in WMH between African and European Americans. Methods Participants enrolled in longitudinal brain aging studies (n=292; 61% Female; 92% European American; mean age=69.6±7.7) completed evaluations including medical exams, neuroimaging, and sociodemographic surveys. Overweight/obese status defined as body mass index ≥30 kg/m2, and WMH load, captured by FLAIR images, as sum of deep and periventricular volumes, scored using the Fazekas scale (0–6), WMH≥4 considered high. Results Logistic regression analyses, adjusted for age, sex, hypertension, and smoking history, indicated that age and interaction between race and obesity were significant predictors of WMH, demonstrating that obesity significantly moderated the relationship between race and WMH. Age independently increased the odds of high WMH by 16% (OR=1.16, 95% CI=1.09–1.23, p<0.001). Stratified analysis indicates that older European Americans had increased WMH (OR=1.17, 95% CI=1.09–1.23, p<0.001), while obese African Americans had increased WMH (OR=27.65, 95% CI=1.47–519.13, p<0.05). In a case controlled subgroup matched by age, sex, and education (n=48), African Americans had significantly higher WMH load (27% vs 4%, Χ2=5.3, p=0.02). Conclusion Results denote that age predicted WMH among European Americans, while obesity predicted WMH among African Americans. Matched sample analyses indicate that obesity increases the odds of WMH, though more pronounced in African Americans. These findings suggest that obesity may explain the differential burden of white matter hyperintensity load, signifying public health and clinical importance.
Quantitation of Colonic Cells as Severity Markers in Patients with Irritable Bowel Syndrome

Background: Irritable bowel syndrome (IBS) is the most common gastrointestinal syndrome. Routine histopathology and immunohistochemistry (IHC) evaluations have shown an increase in the number of different inflammatory cells in the colon of IBS patients. In this study, we have compared the number of intraepithelial lymphocytes (IELs), eosinophils, mast cells and CD3+ T cells, in IBS patients and normal subjects. Materials and Methods: In 2016, seventynine patients with IBS and seventy-nine healthy subjects who underwent colonoscopy for other non-specific causes and with no pathologic findings, were enrolled in this cross-sectional study. Biopsy specimens obtained from the colon were stained, using IHC methods to determine the number of IELs, eosinophils, mast cells and CD3+ T cells. Quantitative and qualitative variables were compared between the two groups, using a Chi-square test and Student’s t-test. Results: Seventy-nine patients with IBS, 79.7% females with a mean age of 42.5±14.6 years, were recruited, as the case group, and seventy-nine individuals, 51.9% females with a mean age of 39.7±18.9 years, were enrolled as controls. The average number of IELs per high power fields (hpf) was found to be higher in the IBS group, and this difference was statistically significant (32.8±11.8 vs. 28.6±12.9; P=0.034). Also, the mean count/hpf of CD3+ T lymphocytes (23.1±7.9 vs. 20.2±8.1; P=0.024) and mast cells (7.6±3.1 vs. 6.6±3.0; P=0.041) were significantly higher in the IBS group, compared to the control group. The number of eosinophils was higher in the IBS group, but the differences were not statistically significant (P=0.066). Conclusion: According to the results, we suggest that analysis of immune cells and IELs in intestinal biopsies might be an appropriate method for diagnosis of IBS.
Sheaves of modules on atomic sites and discrete representations of topological groups

The main goal of this paper is to establish close relations among sheaves of modules on atomic sites, representations of categories, and discrete representations of topological groups. We characterize sheaves of modules on atomic sites as saturated representations, and show that the category of sheaves is equivalent to the Serre quotient of the category of presheaves by the category of torsion presheaves. Consequently, the sheaﬁﬁcation functor and sheaf cohomology functors are interpreted by localization functors, section functors, and derived functors of torsion functor in representation theory. These results as well as a classical theorem of Artin provides us a new approach to study discrete representations of topological groups. In particular, by importing established facts in representation stability theory, we explicitly classify simple or indecomposable injective discrete representations of some discrete topological groups such as the inﬁnite symmetric group, the inﬁnite general or special linear group over a ﬁnite ﬁeld, and the automorphism group of the linearly ordered set Q . We also show that discrete representations of these topological groups satisfy a certain stability property.
The effect of intermittent fasting during Ramadan on energy expenditure and substrate oxidation in healthy men

The study aimed to examine the effect of Ramadan fasting (RF) on substrate partitioning, energy production, blood lipids and glucose as well as body composition. Nine healthy Muslim men (FAST group) and eight healthy men (CNT group) were assessed pre- and post-RF. FAST were additionally assessed at 10ᵀᴴ , 20ᵀᴴ and 30ᵀᴴ day of RF in the morning (a.m.) and evening (p.m.). Results showed a significant reduction in body mass and fat mass in FAST with no statistical differences pre- vs. post-RF for all other variables in both groups. A significant daytime fasting effect [a.m. vs. p.m. ] on substrates oxidation (fat and carbohydrate) and blood parameters (glucose, insulin, total cholesterol, and triglycerides) was observed. In conclusion, although RF brings about an acute metabolic response that shifts substrate partitioning towards lipids, no chronic metabolic response was observed despite the extended daily fasting period (18.0±0.3 hrs) and changes in body composition.
Photon control and coherent interactions via lattice dark states in atomic arrays

Ordered atomic arrays with subwavelength spacing have emerged as an efficient and versatile light-matter interface, where emitters respond collectively and form subradiant lattice modes with supressed decay rate. Here, we demonstrate that such lattice dark states can be individually addressed and manipulated by applying a spatial modulation of the atomic detuning. More specifically, we show that lattice dark states can be used to store and retrieve single photons with near-unit efficiency, as well as to control the temporal, frequency and spatial degrees of freedom of the emitted electromagnetic field. Additionally, we discuss how to engineer arbitrary coherent interactions between multiple dark states. These results pave the way towards building a quantum platform that can equally act as a quantum memory and a photon shaper capable of producing states of light relevant in quantum information protocols.
Health reference intervals and values for common bottlenose dolphins (Tursiops truncatus), Indo-Pacific bottlenose dolphins (Tursiops aduncus), Pacific white-sided dolphins (Lagenorhynchus obliquidens), and beluga whales (Delphinapterus leucas)

This study reports comprehensive clinical pathology data for hematology, serum, and plasma biochemistry reference intervals for 174 apparently healthy common bottlenose dolphins (Tursiops truncatus) and reference values for 27 Indo-Pacific bottlenose dolphins (Tursiops aduncus), 13 beluga whales (Delphinapterus leucas), and 6 Pacific white-sided dolphins (Lagenorhynchus obliquidens) in zoos and aquariums accredited by the Alliance for Marine Mammal Parks and Aquariums and the Association of Zoos & Aquariums. Blood samples were collected as part of a larger study titled “Towards understanding the welfare of cetaceans in zoos and aquariums” (colloquially called the Cetacean Welfare Study). Two blood samples were collected following a standardized protocol, and two veterinarian examinations were conducted approximately six months apart between July to November 2018 and January to April 2019. Least square means, standard deviations, and 95% confidence intervals were calculated for hematology, serum, and plasma biochemical variables. Comparisons by age, gender, and month revealed statistically significant differences (p < 0.01) for several variables. Reference intervals and values were generated for samples tested at two laboratories for up to 56 hematologic, serum, and plasma biochemical variables. To apply these data, ZooPhysioTrak, an iOS mobile software application, was developed to provide a new resource for cetacean management. ZooPhysioTrak provides species-specific reference intervals and values based on user inputs of individual demographic and sample information. These data provide a baseline from which to compare hematological, serum, and plasma biochemical values in cetaceans in zoos and aquariums.
The two halves of disjunctive correctness

Ali Enayat had asked whether two halves of Disjunctive Correctness (DC) for the compositional truth predicate are conservative over Peano Arithmetic. In this article, we show that the principle"every true disjunction has a true disjunct"is equivalent to bounded induction for the compositional truth predicate and thus it is not conservative. On the other hand, the converse implication"any disjunction with a true disjunct is true"can be conservatively added to PA. The methods introduced here allow us to give a direct nonconservativeness proof for DC.
Sample Efficient Detection and Classification of Adversarial Attacks via Self-Supervised Embeddings

Adversarial robustness of deep models is pivotal in ensuring safe deployment in real world settings, but most modern defenses have narrow scope and expensive costs. In this paper, we propose a self-supervised method to detect adversarial attacks and classify them to their respective threat models, based on a linear model operating on the embed-dings from a pretrained self-supervised encoder. We use a SimCLR encoder in our experiments, since we show the SimCLR embedding distance is a good proxy for human perceptibility, enabling it to encapsulate many threat models at once. We call our method SimCat since it uses SimCLR encoder to catch and categorize various types of adversarial attacks, including ℓp and non-ℓp evasion attacks, as well as data poisonings. The simple nature of a linear classifier makes our method efficient in both time and sample complexity. For example, on SVHN, using only five pairs of clean and adversarial examples computed with a PGD-ℓ∞ attack, SimCat’s detection accuracy is over 85%. More-over, on ImageNet, using only 25 examples from each threat model, SimCat can classify eight different attack types such as PGD-ℓ2, PGD-ℓ∞, CW-ℓ2, PPGD, LPA, StAdv, ReColor, and JPEG-ℓ∞, with over 40% accuracy. On STL10 data, we apply SimCat as a defense against poisoning attacks, such as BP, CP, FC, CLBD, HTBD, halving the success rate while using only twenty total poisons for training. We find that the detectors generalize well to unseen threat models. Lastly, we investigate the performance of our detection method under adaptive attacks and further boost its robustness against such attacks via adversarial training.
Financially Constrained Index Futures Arbitrage

We develop two models for index futures arbitrage that take the financing constraints faced by real-world arbitrageurs into account. Our models predict that the price of an index futures contract and the value of its underlying index should deviate further from their theoretical cost-of-carry relationship when (a) the contract has a longtime to go before expiry, and (b) volatility is high. The fact that these predictions enjoy considerable empirical support highlights the importance of financing constraints for explaining index futures mispricing.
Characteristics of Corneal Subbasal Nerves in Different Age Groups: An in vivo Confocal Microscopic Analysis

Purpose To determine the normative characteristics of corneal subbasal nerves in different age groups using laser scanning in vivo confocal microscopy (IVCM). Patients and Methods This descriptive observational study recruited healthy subjects (aged 20–60 years) from Siriraj Health-Screening Center. Excluded were individuals who had abnormal ocular symptoms, previous ocular surgery, a history of any diseases related to systemic and/or corneal neuropathy, or abnormal corneal sensitivity. Corneal IVCM (HRT3/Rostock Corneal Module) was performed at the central cornea to analyze the subbasal nerve plexus. The corneal nerve characteristics, comprising the number and density of nerves (main nerve trunks, branches, and total nerves) were analyzed using the NeuronJ program, and the corneal nerve tortuosity was graded. The correlations between the subbasal nerve density, tortuosity and age were then analyzed. Results Eighty subjects were enrolled, with twenty in each of four age groups (20–30, >30–40, >40–50, and >50–60 years). Overall, the mean number and density of main nerve trunks were 27.93±0.81/mm2 and 11.22±0.30 mm/mm2, respectively. As of the nerve branches, the average number and density were 103.56±2.37/mm2 and 9.15±0.30 mm/mm2, respectively. The total nerve density was 20.37±0.39 mm/mm2. There were no significant differences between subbasal nerve parameters of the four age groups. It is noteworthy that 65% of the subjects aged over 40 years revealed high-grade nerve tortuosity. Conclusion The corneal subbasal nerve numbers and densities were not significantly different among a healthy population aged 20–60 years. However, there was a trend towards high tortuosity of the corneal nerve in people aged over 40 years.
Lost in a black‐box? Interpretable machine learning for assessing Italian SMEs default

Academic research and the financial industry have recently shown great interest in Machine Learning algorithms capable of solving complex learning tasks, although in the field of firms' default prediction the lack of interpretability has prevented an extensive adoption of the black‐box type of models. In order to overcome this drawback and maintain the high performances of black‐boxes, this paper has chosen a model‐agnostic approach. Accumulated Local Effects and Shapley values are used to shape the predictors' impact on the likelihood of default and rank them according to their contribution to the model outcome. Prediction is achieved by two Machine Learning algorithms (eXtreme Gradient Boosting and FeedForward Neural Networks) compared with three standard discriminant models. Results show that our analysis of the Italian Small and Medium Enterprises manufacturing industry benefits from the overall highest classification power by the eXtreme Gradient Boosting algorithm still maintaining a rich interpretation framework to support decisions.