Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of rhinomanometry in evaluating the effectiveness of laser surgical treatment in children with chronic hypertrophic rhinitis

Background . Rhinomanometry is an objective way of assessing nasal patency. Due to advances in technology and the use of microcomputers connected to measuring instruments, the use of this approach has increased. Rhinomanometry evaluates nasal resistance by measuring airflow and transnasal pressure gradient. With the help of this examination, the presence of a nasal respiratory obstruction is detected, and it is evaluated which nosological structure continuously causes it, in this case the hypertrophy of the inferior nasal turbinates. The purpose of the research is to evaluate the effectiveness of the functional examination such as the anterior rhinomanometry in monitoring the results of laser surgical treatment in children with chronic hypertrophic rhinitis. Materials and methods . The given study was carried out in the pediatric otorhinolaryngology clinic of the Emilian Co ţ aga Republican Children’s Clinical Hospital. The research involved a group of 120 children with hypertrophic chronic rhinitis, aged between 8–17 years, divided into three groups of 40 children each, treated surgically by 3 techniques: group 1 — cauterization of the inferior nasal turbinates with bipolar forceps, group 2 — shaver mucotomy and group 3 — diode laser surgery. In all patients, rhinomanometry was performed as an objective preoperative and postoperative examination on the 7 th day, after one month, one year and in 12 months. Results . The analysis of the functional examination results demonstrates that the surgical interventions had a beneficial effect in terms of the recovery of the space parameters of the nasal cavities. A more pronounced improvement of the endonasal architectural indices is determined in group 3 where the diode laser surgical technique was used compared to group 2 — only shaver mucotomy and group 1 where the standard surgical technique of cauterization with bipolar forceps was practiced. Conclusions . The functional rhinomanometric results were statistically different after the surgical treatment in all study groups that indicates an important diagnostic value of this examination in the monitoring of postoperative dynamics.
Web server load prediction and anomaly detection from hypertext transfer protocol logs

As network traffic increases and new intrusions occur, anomaly detection solutions based on machine learning are necessary to detect previously unknown intrusion patterns. Most of the developed models require a labelled dataset, which can be challenging owing to a shortage of publicly available datasets. These datasets are often too small to effectively train machine learning models, which further motivates the use of real unlabeled traffic. By using real traffic, it is possible to more accurately simulate the types of anomalies that might occur in a real-world network and improve the performance of the detection model. We present a method able to predict and categorize anomalies without the aid of a labelled dataset, demonstrating the model’s usability while also gathering a dataset from real noisy network traffic. The proposed long short-term memory (LTSM) based intrusion detection system was tested in a real-world setting of an antivirus company and was successful in detecting various intrusions using 5-minute windowing over both the predicted and real update curves thereby demonstrating its usefulness. Our contribution was the development of a robust model generally applicable to any hypertext transfer protocol (HTTP) traffic with almost real-time anomaly detection, while also outperforming earlier studies in terms of prediction accuracy.
Magnetic Resonance Radiofrequency Pulse Design by Optimal Control

∗ Institute for Mathematics and Scientific Computing, University of Graz, Heinrichstr. 36, 8010 Graz, Austria and BioTechMed-Graz, 8010 Graz, Austria (e-mail: armin.rund@ uni-graz.at). ∗∗ Institute of Medical Engineering, Graz University of Technology, Stremayrgasse 16/III, 8010 Graz, Austria. ∗∗∗ Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, Altenbergstraße 69, 4040 Linz, Austria. ∗∗∗∗ BioTechMed-Graz, 8010 Graz, Austria.
Functional quantization-based stratified sampling

Functional quantization-based stratified sampling is a method for variance reduction proposed by Corlay and Pagès (2015). This method requires the ability to both create functional quantizers and to sample Brownian paths from the strata defined by the quantizers. We show that product quantizers are a suitable approximation of an optimal quantizer for the formation of functional quantizers. The notion of functional stratification is then extended to options written on multiple stocks and American options priced using the Longstaff-Schwartz method. To illustrate the gains in performance we focus on geometric brownian motion (GBM), constant elasticity of variance (CEV) and constant elasticity of variance with stochastic volatility (CEV-SV) models. The pricing algorithm is used to price knock-in, knockout, autocall, call on the max and path dependent call on the max options.
Comparing Asset Pricing Models: Distance-Based Metrics and Bayesian Interpretations

In light of the power problems of statistical tests and undisciplined use of alpha-based statistics to compare models, this paper proposes a unified set of distance-based performance metrics, derived as the square root of the sum of squared alphas and squared standard errors. The Bayesian investor views model performance as the shortest distance between his dogmatic belief (model-implied distribution) and complete skepticism (data-based distribution) in the model, and favors models that produce low dispersion of alphas with high explanatory power. In this view, the momentum factor is a crucial addition to the five-factor model of Fama and French (2015), alleviating his prior concern of model mispricing by -8% to 8% per annum. The distance metrics complement the frequentist p-values with a diagnostic tool to guard against bad models.
Child-Pugh versus APACHE II Scoring Systems for Prognosis Prediction of Acute Variceal Upper Gasterointestinal Bleeding

: Background Accurate risk stratification for patients with acute variceal upper gastrointestinal bleeding would be useful for identifying low-risk patients, who might not require hospitalization and high-risk patients, who require aggressive care in a closely monitored setting. Objectives: To evaluate the application of Child-Pugh and APACHE II scoring systems in the prediction of outcome of patients with acute variceal upper gastrointestinal bleeding. Patients and Methods: 100 patients were included prospectively. Clinical and laboratory data necessary to both Child-Pugh and APACHE II scores were calculated through 24 hours following admission. During hospitalization patients' outcome was reported. Discrimination was tested using the receiver operating characteristic curves and by comparing areas under the curve. Results: 26 patients developed one or more complications, 13 patients developed rebleeding without statistical significant Child-Pugh and APACHE II scores, 3 patients developed renal failure, 21patients had hepatic encephalopathy. All Child A patients survived, only one out of Child B patients died (2.2%) and 9 patients in Child C died (23.7%). Child-Pugh score cut off value for mortality was more than 10, with sensitivity 90%, specificity 77.5%, positive predictive value 31%, negative predictive value 98.6% and accuracy 80.4%. While applying APACHE II score, it was found that the cut off value was more than 15, with sensitivity 70%, specificity 77.8%, positive predictive value 25.9%, negative predictive value 95.9% and accuracy 70.6%. Conclusions: APACHE II and Child-Pugh scoring systems are useful for risk stratification of patients with acute variceal bleeding regarding mortality but not for rebleeding. It is preferred to use Child-Pugh score as a more sensitive score as well as more easy to apply to predict mortality.
Acid stress evaluation using multimetric indices in the Carolina stream (San Luis –Argentina)

: Acid stress evaluation using multimetric indices in the Carolina stream (San Luis – Argentina). The effect of water acidity on benthic macroinvertebrates using multimetric indices was evaluated. Biological integrity indices were adjusted for a stream reach affected by acid drainage from an abandoned mine. This permitted to demonstrate changes in the community of benthic macroinvertebrates subject to acid stress. Five sampling sites were established, in Grande river and in Carolina stream; four of them represented the reference condition. The latter were contrasted with the affected site to establish its degree of impairment. The sampling program was carried out between May 1997 and December 1998. The metric indices that discriminated between the reference situation and the problem site were selected while those that provided redundant information were eliminated. The range of metric values was divided into four categories and then translated in water quality judgments. After the selection, 13 metrics were considered reliable for the analysis and were used for the aggregation in the index and later evaluation of the biological quality of the water. The final evaluation of the multimetric index for the problem site was the sum of the scores of the selected metric indices. The biological condition of problem site was determined as moderately deteriorated environment. Biological monitoring by means of multimetric methods is sensitive to biological degradation in mining areas and effective when it is developed from the database of a regional reference condition.
Assembly of the Cereus fernambucensis Genome , Gene Annotation, and Tertiary Structure of Secondary Metabolism Enzymes in Carnegiea gigantea, Lophocereus schottii, Pachycereus pringlei, Pereskia humboldtii, Selenicereus undatus, and Stenocereus thurberi

Recently, there is growing interest in obtaining bioactive compounds from species in the family Cactaceae , which has been little analyzed at the genomic and transcriptomic level. We here report the assembly of the genome of Cereus fernambucensis and we analyzed six cactus genomes ( Carnegiea gigantea , Lophocereus schottii , Pachycereus pringlei , Pereskia humboldtii , Selenicereus undatus and Stenocereus thurberi ), the annotation of putative genes, and the modeling of the three-dimensional structures of their predicted proteins involved in flavonoid metabolism. We identified genes encoding proteins related to plant pathogenesis (PR-10), coding secuences (CDS) of aldehyde reductase and flavonoid reductase, CDS of enzymes involved in the biosynthesis of phenolic compounds, and ABC transporters. The grouping of the enzymes aspartic proteinase-like protein, flavanone 3-hydroxylase (F3H), hydroxycinnamoyl-CoA shikimate/quinate hydroxycinnamoyl transferase (HCT), and protein serine/threonine- phosphatase was shown to be highly conserved in the genomes of the analyzed cacti. We found divergence of the plant PDR ABC-type transporter family protein (PEN3) in Cereus fernambucensis and the absence in this species of sterol methyltransferase (SMT1). Our three-dimensional modeling of the tertiary structure of F3H from a consensus sequence of cactus species had 88 % identity with that reported in Arabidopsis thaliana . We observed the conservation in several plant species of the 2-oxoglutarate and iron-dependent domain of F3H. This is the first report of an exploration of putative genes encoding enzymes involved in secondary metabolism in cacti species providing information that could be used to improve the production of bioactive compounds in them.
Application and Performance of Space Time Coding in MIMO System—Analysis of Alamouti Space Time Coding Scheme

: This research first intuitively shows the implementation diagram of a MIMO system, and then introduces transmission diversity and space-time coding technology, with space-time coding technology belonging to the category of spatial diversity technology. The earliest and most classical Alamouti space-time coding scheme is then applied to MIMO wireless communication systems. The principle of the Alamouti space-time coding scheme is demonstrated, and a theoretical demonstration is carried out in a MIMO diversity system with two transmitters and one receiver. Finally, the Alamouti space-time coding scheme is simulated using MATLAB, and it is verified that the diversity gain and coding gain are obtained by using the Alamouti space-time coding scheme in the MIMO system.
An effective feature selection using improved marine predators algorithm for Alzheimer’s disease classification

Alzheimer’s disease (AD) is an irremediable neurodegenerative illness developed by the fast deterioration of brain cells. AD is mostly common in elder people and it extremely disturbs the physical and mental health of patients, therefore early detection is essential to prevent AD development. However, the precise detection of AD and mild cognitive impairment (MCI) is difficult during classification. In this paper, the Residual network i.e., ResNet-18 is used for extracting the features, and the proposed improved marine predators algorithm (IMPA) is developed for choosing the optimum features to perform an effective classification of AD. The multi-verse optimizer (MVO) used in the IMPA helps to balance exploration and exploitation, which leads to the selection of optimal relevant features. Further, the classification of AD is accomplished using the multiclass support vector machine (MSVM). Open access series of imaging studies-1 (OASIS-1) and Alzheimer disease neuroimaging initiative (ADNI) datasets are used to evaluate the IMPA-MSVM method. The performance of the IMPA-MSVM method is analyzed using accuracy, sensitivity, specificity, positive predictive value (PPV) and matthews correlation coefficient (MCC). The existing methods such as the deep learning-based segmenting method using SegNet (DLSS), mish activation function (MAF) with spatial transformer network (STN) and BrainNet2D are used to evaluate the IMPA-MSVM method. The accuracy of IMPA-MSVM for the ADNI dataset is 98.43% which is more when compared to the DLSS and MAF-STN.
Accelerated kernel discriminant analysis

In this paper, using a novel matrix factorization and simultaneous reduction to diagonal form approach (or in short simultaneous reduction approach), Accelerated Kernel Discriminant Analysis (AKDA) and Accelerated Kernel Subclass Discriminant Analysis (AKSDA) are proposed. Specifically, instead of performing the simultaneous reduction of the between- and within-class or subclass scatter matrices, the nonzero eigenpairs (NZEP) of the so-called core matrix, which is of relatively small dimensionality, and the Cholesky factorization of the kernel matrix are computed, achieving more than one order of magnitude speed up over kernel discriminant analysis (KDA). Moreover, consisting of a few elementary matrix operations and very stable numerical algorithms, AKDA and AKSDA offer improved classification accuracy. The experimental evaluation on various datasets confirms that the proposed approaches provide state-of-the-art performance in terms of both training time and classification accuracy.
CONSTITUTIONAL COURT AS MEDIATOR: A MODELS AND SOLUTIONS TO ARMED CONFLICT AND THE RULE OF LAW IN PAPUA, INDONESIA

: Conflicts and tensions in Papua that have occurred for a long time, continue to escalate in 2021 until until April 2023 with quite complex problems. This study analyses the concept of the Constitutional Court as a mediator which is used as a model and solution for armed conflict and the rule of law in Papua, Indonesia. Using a normative legal research approach by collecting primary, secondary and tertiary legal materials. In order to get answers to research problems, the four models of problem solving approaches are used statute approach, conceptual approach, comparative approach, historical approach. This research uses descriptive-prescriptive and content analysis. The result of this research is the granting of new authority to the Constitutional Court through amendments to the 1945 Constitution, because it sees the opportunity for the Constitutional Court to become a mediator in resolving armed conflicts carried out by the government and KKB/KSB/OPM in Papua, thereby creating security, order & peace.
Reproducibility of inhibitory control, working memory, and cognitive flexibility measures in older women

Introduction: Executive Function is expressed in day-to-day activities through inhibitory control, working memory, and cognitive flexibility. Despite the importance of evaluating these measures, there are disagre-ements about the reproducibility of the tests. Objective: To test the reproducibility of the Stroop Color-Word Test, Corsi Block-Tapping Test, and Trail Making Test in older women. Methods: Thirty-five older women performed the Stroop Color-Word Test (Inhibitory Control), Corsi Block-Tapping Test (Working Memory), and Trail Making Test (Cognitive Flexibility) within one week between the test and retest. The reproducibility of the tests was determined by the intraclass correlation coefficient, coefficient of variation, standard error of measurement, and visual inspection of the Bland-Altman graphs. Results: The Stroop Color-Word Test showed satisfactory reproducibility values only for congruent and incongruent measures, with excellent intraclass correlation coefficient values. Corsi Block-Tapping Test showed reproducible values with a moderate and good intraclass correlation coefficient for the sequence and composite score, respectively. The Trail Making Test showed reproducible values for parts A, B, and the ratio (B/A), with intraclass correlation coefficients between moderate and good. Visual inspection of the Bland-Altman plots showed low bias in all variables. Conclusion: The results of the Stroop Color-Word Test, for congruent and incongruent trials, the sequence and the composite score of the Corsi Block-Tapping Test, as well as the part A, B, and the ratio (B/A) of the Trail Making Test, are reproducible measurements for older women.
No Longer Lost in Translation: Evidence that Google Translate Works for Comparative Bag-of-Words Text Applications

Automated text analysis allows researchers to analyze large quantities of text. Yet, comparative researchers are presented with a big challenge: across countries people speak different languages. To address this issue, some analysts have suggested using Google Translate to convert all texts into English before starting the analysis (Lucas et al. 2015). But in doing so, do we get lost in translation? This paper evaluates the usefulness of machine translation for bag-of-words models—such as topic models. We use the europarl dataset and compare term-document matrices (TDMs) as well as topic model results from gold standard translated text and machine-translated text. We evaluate results at both the document and the corpus level. We first find TDMs for both text corpora to be highly similar, with minor differences across languages. What is more, we find considerable overlap in the set of features generated from human-translated and machine-translated texts. With regard to LDA topic models, we find topical prevalence and topical content to be highly similar with again only small differences across languages. We conclude that Google Translate is a useful tool for comparative researchers when using bag-of-words text models.
ADIWIYATA GREEN SCHOOL PROGRAM IMPLEMENTATION ANALYSIS: A PORTRAIT FROM THE ELEMENTARY SCHOOLS IN SURABAYA, INDONESIA

The direction of sustainable development (SDGs) in Indonesia is one of the pillars of environmental action. Green environmental development emphasizes environmental insight and minimizes damage and negative impacts on the environment. Attention to the environment is a shared responsibility for the next generation, so it is vital to shape the character of caring for the environment from an early age. One way is through the adiwiyata school program, a program from the Ministry of Environment and Forestry in collaboration with local governments. Building pro-environment character and behavior is certainly not an easy thing. It needs support and innovative studies to support its implementation and sustainability, so this study's main objective is to examine the implementation model of the adiwiyata program more deeply. We collected data through literature studies, semi-structured interviews, and surveys involving schools and several informants from the government offices related to the adiwiyata program. The obtained data were reduced and analyzed using triangulation techniques. From the data obtained, the analysis of the performance of the adiwiyata program is based on the content of
Anthocyanin Content and Antioxidant Activity of Red Chrysanthemum ( Chrysanthemum morifolium Ramat.) at Different Flower Ages

Chrysanthemum sp. is a floricultural plant of the Asteraceae family with high economic value. The anthocyanin pigment in red chrysanthemum acts as an antioxidant, the content of which can be influenced by genetic factors such as the physiological age of the flower. This study aimed to determine the effect of flower age on anthocyanin content and antioxidant activity in red chrysanthemum plants. The age of red chrysanthemum used was 115 Days After Planting (DAP) (early bloom stage), 120 DAP (half-bloom stage), 125 DAP (blooming stage), and 134 DAP (wilted flower). The anthocyanin content was analysed using spectrophotometric methods. Antioxidant activity was determined by the DPPH method and then the absorbance was measured using a UV-Vis spectrophotometer. The results showed that the highest anthocyanin content was obtained at the age of 134 DAP at 3.56 mg/g, followed by the age of 115 DAP at 2.40 mg/g, then at 125 DAP at 1.95 mg/g and the lowest at 120 DAP at 1.69 mg/g. The highest antioxidant activity was shown in chrysanthemum flowers aged 115 DAP which had an IC 50 value of 288.85 g/ml. The research shows that wilted chrysanthemum flowers still contain anthocyanins so it can be used in various industrial fields such as chrysanthemum tea and additives for soap.
Ion-Pair Complex of Trimethoprim with Alizarin Yellow and its Determination and Extraction by LLE and DLLME

F or the analysis of trimethoprim medication in its pure form and pharmaceutical formulations, precise and accurate microextraction techniques with UV-Vis measurement have been developed and confirmed. In this study, LLE and DLLME procedures were utilized for the separation, preconcentration, and evaluation of trimethoprim in pure form and pharmaceutical preparations by UV-Vis spectroscopy at 390 nm. The method was validated and applied to the evaluation of trimethoprim in pharmaceutical formulations. Several experimental factors containing the type
How far away and how old are these stars?

Abstract RAVE is the spectroscopic survey with the largest overlap with TGAS (around 200000 stars). Since RAVE's fourth data release, it has contained distance estimates based on a Bayesian estimation scheme. Here we compare these estimates to TGAS's parallaxes, to determine the strengths and weaknesses of each. We also combine the two datasets together to find more precise distance estimates for all these stars.
Tracking freely moving mice using computer vision, statistical inference and statistical learning techniques

—Tracking movements of animals is essential for understanding behaviours in natural environments, as well as for investigating their neural correlates. Here we describe and evaluate the computer vision, statistical inference and statistical learning methods that we used to estimate positions, velocities and accelerations from videos of mice freely moving in a large arena. We provide code and sample data to reproduce all ﬁgures in the poster.