Miracle-dz/UniFAR-FTUs huggingface dataset:
Blind Image Quality Index With Cross-Domain Interaction and Cross-Scale Integration

With the assistance of Convolutional Neural Networks (CNNs), Image Quality Assessment (IQA) models have made great progress in evaluating both simulated distortion and authentic distortion. However, most of the existing IQA models only learn the features of distorted images, and thus do not make full use of the available feature representation of other domains. Furthermore, the common multi-scale fusion strategies are relatively simple, such as downsampling and concatenating, which further limits the prediction performance. To this end, we propose a novel blind image quality index with cross-domain interaction and cross-scale integration, which is designed based on the combination of CNN and Transformer. First, the hierarchical spatial-domain and gradient-domain representations are obtained through a typical CNN architecture. Then, based on the proposed gradient-query cross-attention, these two types of features are fully interacted in the Cross-Domain Interaction (CDI) module. To represent the distortion information more comprehensively, the Cross-Scale Integration (CSI) module is proposed to combine the information between different scales progressively. Finally, the quality score is obtained through a simple regression module. The experimental results on five public IQA databases of both simulated and authentic scenes show that the proposed model outperforms the compared state-of-the-art metrics. In addition, cross-database experiments show that the proposed model has strong generalization performance.
A Guided Tour in Constraint Qualifications for Nonlinear Programming under Differentiability Assumptions

It is well-known that the celebrated Kuhn-Tucker or Karush-Kuhn-Tucker necessary optimality conditions hold at a local solution point of a nonlinear programming problem if some regularity conditions, usually called "constraint qualifcations", are satisfied. In the present paper we give an up-to-date overview of several constraint quali? cations proposed in the literature for a nonlinear programming problem, under differentiability assumptions. In particular, we point out the various implications existing among the constraint qualifications considered. For the reader's convenience we shall consider separately the case of inequality constraints only and the case of mixed equality and inequality constraints. Some remarks on second-order constraint qualifications are made and some historical notes on this subject are given.
Prone vs supine position in intubated COVID-19 patients with ARDS: a systematic review and meta-analysis

Background & Objective: The recent COVID-19 pandemic has tested the healthcare sector to the maximum, but it also has taught us some valuable lessons, especially in the context of intensive care, and particularly in the respiratory support. This review determined the effect of prone positioning in changes of partial pressure of arterial oxygen/fraction of inspired oxygen (PaO2/FiO2) ratio, partial pressure of carbon dioxide (PaCO2), mortality rate, ICU length of stay and duration of mechanical ventilation in intubated COVID-19 patients with ARDS. Methodology: A computer-aided comprehensive electronic bibliographic search from MEDLINE, EMBASE, and Science Direct were conducted. The search comprised the articles written in English and intubated adult (≥ 18 y old) patients with COVID-19. The primary outcome was comparing PaO2/FiO2 ratio between prone and supine position groups. Secondary outcomes were comparisons of PaCO2, ICU discharge, and mortality rate. Review Manager version 5.4 (The Cochrane Collaboration) was used for statistical analyses of the included studies. Results: A total of 7 articles were determined to be eligible, consisting of 1403 intubated COVID-19 patients with ARDS that showed prone position was associated with a higher PaO2/FiO2 ratio compared to the supine position (MD 60.17, 95% CI 46.86−73.47; P < 0.00001). Four studies reported the PaCO2 measurements and showed no significant difference between prone and supine positions (MD 2.07, 95% CI -2.79−6.92; P < 0.40). Only two studies reported mortalities, one study had 262 deaths out of 648 patients (40.4%) and the other study lost 11 out of 20 patients (55%). One study reported median ICU stay and mechanical ventilation duration (16 days) were significantly longer in prone position group. Conclusion: This meta-analysis showed that prone position improved PaO2/FiO2 ratio in intubated COVID-19 patients with ARDS. It also prolonged ICU stay and mechanical ventilation duration, but had no effect on mortality rate. Abbreviations: APACHE-II- Acute Physiology and Chronic Health Evaluation-II; ARDS - acute respiratory distress syndrome; ICU – Intensive Care Unit; MD – Mean Difference; NOS - Newcastle-Ottawa scale; SOFA - Sequential Organ Failure Assessment Key words: Prone Position; Supine Position; COVID-19; ARDS, Intubation; Meta-Analysis Citation: Aditianingsih D, Sugiarto A, Manggala SK, Angkasa H, Natanegara AP. Prone versus supine position in intubated COVID-19 patients with ARDS: a systematic review and meta-analysis. Anaesth. pain intensive care 2023;27(4):535−544; DOI: 10.35975/apic.v27i4. 2136 Received: January 20, 2023; Reviewed: May 04, 2023; Accepted: June 23, 2023
UvA-DARE (Digital Academic Repository) Cross-disciplinary, authentic student research projects Cross-Disciplinary, Authentic Student Research Projects

In the Dutch secondary education system, students must carry out at the end of their school career a rather large research or design project to demonstrate their ability to apply acquired knowledge and skills while pursuing a research question or design goal in some depth. They are encouraged to choose the topic themselves and they are to some extent free in setting up their work. Ideally, the students do not only see it as a compulsory subject but also enjoy the stimulating aspects of doing their own research or design. Challenging and authentic projects, which are representative for actual research and design work done by professionals, seem effective in this respect. The focus of this paper is on how the use of ICT for data acquisition, video-analysis, modelling, and data analysis can contribute to the realisation of such projects in mathematics and science education and on how it can give students opportunities to take the nature and level of their work close to the characteristics of work of experts in the field. We present two examples of students’ inquiry work, in the context of bungee jumping and human gait, and we discuss the ICT usage, the authenticity and resemblance with an expert’s approach.
A Study on Locus of Hope and Suicide Ideation among Undergraduate Students in the Philippines

Last Academic Year 2021-2022, an alarming total of 2,147 students attempted suicide when most schools were still closed due to the pandemic as reported by the Philippine Daily Inquirer [1]. This study gained insight into suicide ideation among undergraduate students across the country anchoring Bernardo’s extended hope theory [7] of Snyder [8] with the premise that blockage towards the goal pathway may lead to suicide ideation among individuals with perceived low hope. The data were collected online (N=128) through Google Forms. Descriptive and multiple regression analyses of data were used. Results have shown a negative relationship between undergraduate students’ external locus of hope and suicide ideation. The likelihood of suicide ideation decreases by (-0.44 as predicted by EXT-PA; -0.62 as predicted by EXT-PE, and -0.79 as predicted by EXT-SP). Internal locus of hope (INT) on the other hand, does not predict suicide ideation. A high level of hope and a low level of suicide ideation were reported at the time of data collection. Proposed interventions to universities or colleges are recommended to further increase or maintain the hope level of undergraduate students as well as lessen or keep their suicide ideation at bay.
Probabilistic Categorical Adversarial Attack and Adversarial Training

The studies on adversarial attacks and defenses have greatly improved the robustness of Deep Neural Networks (DNNs). Most advanced approaches have been overwhelmingly designed for continuous data such as images. However, these achievements are still hard to be generalized to categorical data. To bridge this gap, we propose a novel framework, Probabilistic Categorical Ad-versarial Attack (or PCAA) . It transfers the discrete optimization problem of finding categorical adversarial examples to a continuous problem that can be solved via gradient-based methods. We analyze the optimality (attack success rate) and time complexity of PCAA to demonstrate its significant advantage over current search-based attacks. More importantly, through extensive empirical studies, we demonstrate that the well-established defenses for continuous data, such as adversarial training and TRADES, can be easily accommo-dated to defend DNNs for categorical data.
Parrots of the Sydney region: population changes over 100 years

With European settlement, the landscape of Australia changed dramatically due to clearing for agriculture, forestry and urban development. These changes have impacted on the diversity and abundance of many Australian native fauna. The avifauna provides a conspicuous example. Despite their generally striking colours, strident call and large body size, the status of parrot populations in urban regions have been largely ignored. We reviewed three bird data bases to determine trends. The two species, recorded within 10 km of Sydney’s General Post Office pre-1900, are no longer present, although 15 species are now known from this area. Populations of the five most common of these species have continued to increase in the last 20 years, one appears to have remained unchanged and others are present in insufficient numbers to comment. No species appears to have declined in numbers. Escapees or deliberate releases from aviaries are major sources of birds that establish viable populations, although even in these populations, numbers may also have been supplemented by vagrants. We suggest that supplementary feeding, and changes in the vegetation in the city landscape, are major contributing factors to the current diversity and abundance of parrots within Sydney.
Magnetic resonance diffusion tensor imaging for characterizing diffuse and focal white matter abnormalities in multiple sclerosis

High‐resolution diffusion tensor imaging (DTI) was performed in 14 patients with clinically definite multiple sclerosis (MS) and the trace of the diffusion tensor (〈D〉) and the fractional anisotropy (FA) were determined in normal appearing white matter (NAWM) and in different types of focal MS lesions. A small but significant increase of the 〈D〉 in NAWM compared to control white matter ((840 ± 85) × 10–6 mm2/sec vs. (812 ± 59) × 10–6 mm2/sec; P < 0.01) was found. In addition, there was a significant decrease in the FA of normal‐appearing regions containing well‐defined white matter tracts, such as the genu of the internal capsule. In non‐acute lesions, the 〈D〉 of T1‐hypointense areas was significantly higher than that of T1‐isointense lesions ((1198 ± 248) × 10–6 mm2/sec vs. (1006 ± 142) × 10–6 mm2/sec; P < 0.001), and there was a corresponding inverse relation of FA. Diffusion characteristics of active lesions with different enhancement patterns were also significantly different. DTI with a phase navigated interleaved echo planar imaging technique may be used to detect abnormalities of isotropic and anisotropic diffusion in the NAWM and selected fiber tracts of patients with MS throughout the entire brain, and it demonstrates substantial differences between various types of focal lesions. Magn Reson Med 44:583–591, 2000. © 2000 Wiley‐Liss, Inc.
[Expression of fibroblast growth factor receptor like 1 protein in oral squamous cell carcinoma and its influence on tumor cell proliferation and migration].

OBJECTIVE This study aims to investigate the expression of fibroblast growth factor receptor like 1 (FGFRL1) in oral squamous cell carcinoma (OSCC) and reveals its association with tumor cell proliferation and migration. METHODS Western blot was performed to detect the expression of FGFRL1 protein in OSCC tissues, adjacent normal tissues, OSCC cell lines and normal epithelial cells. After knocking down of FGFRL1 in HN4 cells, CCK-8 and Ki67 assays were performed to detect cell proliferation, wounding healing assay and transwell were performed to detect cell-migration. Western blot was used to detect the expression of protein related to epithelial-mesenchymal transition (EMT). RESULTS The expression of FGFRL1 in OSCC tissues was higher than that in adjacent nontumor tissues, respectively (t=2.820, P=0.047 8). Moreover, the expression of FGFRL1 in OSCC cells was higher than that in HOK cells. Quantitative real-time polymerase chain reaction (qRT-PCR) showed that FGFRL1 expression of FGFRL1 RNA in HOK cells was lower than that in OSCC cells. HN4 cells transfected with FGFRL1 siRNA were included in the experimental group, whereas HN4 cells treated with NC siRNA were included in the control group. CCK-8 experiment showed no significant difference between the experimental and control groups with regard to proliferation ability at 48 h (P=0.478 1) and 72 h (P=0.334 2). Migration experiment showed that the wound healing areas in the experimental group after 12 h (P=0.022 8), 24 h (P=0.005 1), and 36 h (P=0.009 5）were smaller than that in the control group. Transwell invasion assay showed that the number of invaded cells in the experimental group after 16 h (P=0.008 7) and 24 h (P=0.008 6) were lower than that in the control group. Knocking-down FGFRL1 up-regulated the expression of E-cadherin and down-regulated the expression of N-cadherin and Vimentin in HN4 cells. CONCLUSIONS FGFRL1 expression in the OSCC tissues was significantly higher than that in the adjacent nontumor tissues. FGFRL1 expression in the OSCC cells was significantly higher than that in the HOK cells, and FGFRL1 had no effect on cell proliferation but promoted tumor cell migration and EMT.
Increased epidermal growth factor receptor gene copy number is associated with poor prognosis in head and neck squamous cell carcinomas.

PURPOSE High epidermal growth factor receptor (EGFR) gene copy number is associated with poor prognosis in lung cancer, but such findings have not been reported for HNSCC. A better understanding of the EGFR pathway may improve the use of EGFR inhibitors in HNSCC. PATIENTS AND METHODS EGFR status was analyzed in 86 tumor samples from 82 HNSCC patients by fluorescent in situ hybridization (FISH) to determine EGFR gene copy number, by polymerase chain reaction and direct sequencing for activating mutations, and by DNA microarray and immunohistochemistry for RNA and protein expression. The results were associated with patient characteristics and clinical end points. RESULTS Forty-three (58%) of 75 samples with FISH results demonstrated EGFR high polysomy and/or gene amplification (FISH positive). The FISH-positive group did not differ from the FISH-negative group with respect to age, sex, race, tumor grade, subsites and stage, or EGFR expression by analyses of RNA or protein. No activating EGFR mutations were found. However, the FISH-positive group was associated with worse progression-free and overall survival (P < .05 and P < .01, respectively; log-rank test). When microarray data were interrogated using the FISH results as a supervising parameter, ECop (which is known to coamplify with EGFR and regulate nuclear factor-kappa B transcriptional activity) had higher expression in FISH-positive tumors. CONCLUSION High EGFR gene copy number by FISH is frequent in HNSCC and is a poor prognostic indicator. Additional investigation is indicated to determine the biologic significance and implications for EGFR inhibitor therapies in HNSCC.
Algorithmic Game Theory: Incentives and Information Security

Many interesting and important new applications of game theory have been discovered over the past 5 years in the context of research into the economics of information security. Many systems fail not ultimately for technical reasons but because incentives are wrong. For example, the people who guard a system often are not the people who suffer the full costs of failure, and as a result they make less effort than would be socially optimal. Some aspects of information security are public goods, like clean air or water; externalities often decide which security products succeed in the marketplace; and some information risks are not insurable because they are correlated in ways that cause insurance markets to fail. Deeper applications of game-theoretic ideas can be found in the games of incomplete information that occur when critical information, such as about software quality or defender efforts, is hidden from some principals. An interesting application lies in the analysis of distributed system architectures; it took several years of experimentation for designers of peer-to-peer systems to understand incentive issues that we can now analyze reasonably well. Evolutionary game theory has recently allowed us to tie together a number of ideas from network analysis and elsewhere to explain why basing peer-to-peer systems on rings is a bad idea, and why revolutionaries use cells instead. The economics of distributed systems looks like being a very fruitful field of research.
Health and Environment: Methodological Strategies to Assess the Impact of Environmental Damage on Health

This paper aims to present different methodologies used to assess the impact of environmental pollution on the health of the population, and some results that have been addressed by the most important studies on the subject. These impacts, known as externalities in economics, become important because when investment decisions are taken, such as the type of technology used in a production process or the location of an electrically plant, it is
THE GREAT WHITE SHARK Carcharodon carcharias (LINNÉ, 1758) IN THE PLIOCENE OF PORTUGAL AND ITS EARLY DISTRIBUTION IN EASTERN ATLANTIC

Fossil great white shark Carcharodon carcharias has been recognized for the first time in Portugal near Marinha Grande in Pliocene sediments. This occurrence further broadens its already huge distribution. It is indeed the first Pliocene shark so far identified in Portugal. The great white shark is represented but by a single upper right lateral tooth lost after use from a ca. 4 m TL, adult individual. The presence is very much in agreement with all known data about Iberian Peninsula, where it really has never been found in Miocene units but becomes common in lower Pliocene levels in Spain. Although the evidence is typical, it is too scarce to allow much speculation on the species numerical importance. If however we take into account that no other shark teeth are known in the concerned sediments it can provisorily be accepted that its occurrence would be rather common. This new record for the Pliocene in Portugal underlines the closeness of the first known occurrences for the eastern Atlantic, both in its northern (as this is the case) and southern parts as shown by the referred Pliocene fauna of Farol das Lagostas, Angola.
ANALISIS KINERJA METODE ARTIFICIAL NEURAL NETWORK DAN SUPPORT VECTOR REGRESSION UNTUK PREDIKSI SIGNIFICANT WAVE HEIGHT

Abstrak. Faktor tekanan angin pada laut dapat menghasilkan gelombang. Tinggi gelombang atau wave height (WH) adalah salah satu bagian dari bentuk gelombang. Significant wave height (SWH) salah satu jenis WH yang merupakan rata-rata nilai sepertiga WH tertinggi pada gelombang spektrum. Data SWH dapat diperoleh dari dua sumber yaitu dari situs resmi penyedia data historikal yang jumlahnya sangat besar dan dari hasil observasi satellite. Namun data dari hasil observasi satelite umumnya data kurang akurat. Prediksi SWH sangat penting dilakukan untuk mengukur kekuatan beban yang diterima oleh kapal dan bangunan diatas atau dalam laut. Metode prediksi yang digunakan oleh peneliti bidang kelautan umumnya adalah metode numerik dan statistik. Metode numerik memiliki kendala dalam memprediksi data skala besar dan hasil prediksi tidak akurat. Metode statistik terkendala pada penentuan parameter untuk menghasilkan prediksi yang akurat. Metode machine learning (ML) merupakan metode yang sering digunakan untuk memprediksi data berdasarkan data histori sehingga dapat digunakan sebagai metode untuk memprediksi nilai SWH. Kelebihan metode ML yaitu dapat memprediksi SWH skala besar, ML dapat memodelkan prediksi dengan mempelajari data. Metode ML yang biasanya digunakan untuk memprediksi data adalah artificial neural network (ANN) dan support vector regression (SVR). Paper ini melakukan analisis kinerja kedua metode tersebut untuk memprediksi nilai SWH. Dataset yang digunakan adalah data historikal SWH dari Brisbane, Australia.Dataset dirubah dengan Sliding Window (SW) untuk menyesuaikan dengan struktur ANN dan SVR. Hasil prediksi kedua metode dievaluasi menggunakan metode evaluasi yaitu mean absolute percentage error (MAPE). Dataset SWH berasal dari situs bmkg pemerintahan Australia. Berdasarkan hasil prediksi SWH menggunakan ANN dan SVR. Hasil evaluasi prediksi pada SW ukuran 3 yaitu ANN mendapatkan MAPE 6.88 % sedangkan hasil evaluasi prediksi SVR mendapatkan MAPE 8.51 % . Kata Kunci: Wave Height, Significant Wave Height, Numerik, Statistik, Machine Learning, Artificial Neural Networks, Support Vector Regression, Prediksi, Data Historikal, Evaluasi, Mean Absolute Percentage Error, Sliding Window. DOI : https://doi.org/10.33005/scan.v13i1. 1054
Comparative Effects of LY3020371, a Potent and Selective Metabotropic Glutamate (mGlu) 2/3 Receptor Antagonist, and Ketamine, a Noncompetitive N-Methyl-d-Aspartate Receptor Antagonist in Rodents: Evidence Supporting the Use of mGlu2/3 Antagonists, for the Treatment of Depression.

The ability of the N-methyl-d-aspartate receptor antagonist ketamine to alleviate symptoms in patients suffering from treatment-resistant depression (TRD) is well documented. In this paper, we directly compare in vivo biologic responses in rodents elicited by a recently discovered metabotropic glutamate (mGlu) 2/3 receptor antagonist 2-amino-3-[(3,4-difluorophenyl)sulfanylmethyl]-4-hydroxy-bicyclo[3.1. 0]hexane-2,6-dicarboxylic acid (LY3020371) with those produced by ketamine. Both LY3020371 and ketamine increased the number of spontaneously active dopamine cells in the ventral tegmental area of anesthetized rats, increased O2 in the anterior cingulate cortex, promoted wakefulness, enhanced the efflux of biogenic amines in the prefrontal cortex, and produced antidepressant-related behavioral effects in rodent models. The ability of LY3020371 to produce antidepressant-like effects in the forced-swim assay in rats was associated with cerebrospinal fluid (CSF) drug levels that matched concentrations required for functional antagonist activity in native rat brain tissue preparations. Metabolomic pathway analyses from analytes recovered from rat CSF and hippocampus demonstrated that both LY3020371 and ketamine activated common pathways involving GRIA2 and ADORA1. A diester analog of LY3020371 [bis(((isopropoxycarbonyl)oxy)-methyl) (1S,2R,3S,4S,5R,6R)-2-amino-3-(((3,4-difluorophenyl)thio)methyl)-4-hydroxy-bicyclo[3.1. 0]hexane-2,6-dicarboxylate (LY3027788)] was an effective oral prodrug; when given orally, it recapitulated effects of intravenous doses of LY3020371 in the forced-swim and wake-promotion assays, and augmented the antidepressant-like effects of fluoxetine or citalopram without altering plasma or brain levels of these compounds. The broad overlap of biologic responses produced by LY3020371 and ketamine supports the hypothesis that mGlu2/3 receptor blockade might be a novel therapeutic approach for the treatment of TRD patients. LY3020371 and LY3027788 represent molecules that are ready for clinical tests of this hypothesis.