Miracle-dz/UniFAR-FTUs huggingface dataset:
Intraoperative diagnosis of left-sided appendicitis in a patient with partial situs inversus and levocardia: a rare case report

Acute appendicitis is common surgical conditions, requiring an emergency operation and accounting for 4% to 8% of all emergency department visits. The diagnosis depends on clinical manifestation, radiological findings, and surgeon experience. Appendicitis causing pain in the left lower quadrant is rare and can occur with congenital abnormalities that include a true left-sided appendix or as an atypical presentation of a right-sided, but long appendix, which projects into the left lower quadrant. Left-sided acute appendicitis develops in association with two types of congenital anomalies: situs in versus and mid-gut malrotation. Here we are reporting a case of right-side lower quadrant pain presentation of left appendicitis with partial situs inversus. A 28-year-old male presented to the emergency department with a one-day history of right lower quadrant (RLQ) abdominal pain associated with nausea and vomiting. Physical examination revealed RLQ abdominal tenderness with localized guarding. Laboratory tests revealed raised levels of C-reactive protein and neutrophilic leukocytosis. Abdominal ultrasound report came as non-visualized appendix. Patient was taken for laparoscopic appendicectomy where the appendix was not found on the right iliac fossa. Laparoscopic exploration was done and revealed a swollen inflamed left-sided appendix attached to a healthy mobile left sided caecum. Laparoscopic appendicectomy was carried out and the postoperative period was uneventful and the patient was discharged within 24 hours. Postoperative chest and abdominal contrast-enhanced computed tomography showed a situs inversus with levocardia. Left-sided appendicitis is a rare condition characterized by the anatomical variation of the appendix with atypical presentation and is therefore easy to misdiagnose. Preoperative clinical diagnosis of left sided acute appendicitis is difficult and imaging may help determine the correct diagnosis. Laparoscopic appendicectomy is far more superior to the open method in these cases as it saves the patient a formal open surgical exploration.
Acceleration of a multi-objective topology optimisation in 2D electro-magnetic field based on the level-set method and the boundary element method by the - H matrix method

In this study, we develop an efficient topology optimisation method with the H -matrix method and the boundary element method (BEM). In sensitivity analyses of topology optimisation, we need to solve a set of two algebraic equations whose coefficient matrices are common, particularly in many cases. For such cases, by using a direct solver such as LU decomposition to factorise the coefficient matrix, we can reduce the computational time for the sensitivity analysis. A coefficient matrix derived by the BEM is, however, fully populated, which causes high numerical costs for the LU decomposition. In this research, the LU decomposition is accelerated by using the H -matrix method for the sensitivity analyses of topology optimisation problems. We demonstrate the efficiency of the proposed method by a numerical example of a multi-objective optimisation problem for 2D electromagnetic field.
Underdispersion models: Models that are “under the radar”

ABSTRACT The Poisson distribution is a benchmark for modeling count data. Its equidispersion constraint, however, does not accurately represent real data. Most real datasets express overdispersion; hence attention in the statistics community focuses on associated issues. More examples are surfacing, however, that display underdispersion, warranting the need to highlight this phenomenon and bring more attention to those models that can better describe such data structures. This work addresses various sources of data underdispersion and surveys several distributions that can model underdispersed data, comparing their performance on applied datasets.
Integrated Quantum Optics: Experiments towards integrated quantum-light sources and quantum-enhanced sensing

The work presented in this thesis is focused on experimental application and generation of continuous variable quantum correlated states of light in integrated dielectric structures. Squeezed states are among the most exploited continuous variable optical states for free-space quantum-enhanced sensing and communication protocols, but for these developments to be applicable for future technologies they must be transformed to an integrated architecture compatible with current electro-optical technology. So far only little work has been done in this direction, but two such contributions are made in this thesis: Firstly, we present proof-ofprinciple demonstration of interfacing squeezed light with an on-chip optomechanical resonator, demonstrating a quantum-enhanced sensitivity to the vibrations of the micromechanical object. Secondly, work on developing an integrated source of squeezed light is presented and an optimized device design is proposed. The devices have been fabricated and tested optically and preliminary interrogations of the output quantum noise have been performed. Integreret kvanteoptik – eksperimentelle studier med henblik på generering og anvendelse af kvanteoptiske tilstande i integrerede strukturer. Dansk resumé Denne afhandling har fokus på eksperimentelle anvendelser og generering af kvantekorrelerede lystilstande i integrerede dielektriske strukturer. Kvantestøjsreducerede tilstande er blandt de hyppigst anvendte til kvanteforstærkede måleteknikker og kommunikationsprotokoller, men en praktisk implementering af sådanne teknikker i kommende teknologi fordrer, at de realiseres i en integreret platform kompatibel med den gængse elektro-optiske fabrikationslinje. Antallet af arbejder med dette fokus er sparsomt, men to sådanne bidrag er indeholdt i nærværende afhandling: Vi har for første gang koblet kvantestøjsreducerede optiske tilstande til en integreret optomekanisk ræsonator, resulterende i en kvanteforstærket måling af et mikromekanisk objekts termisk eksiterede vibrationer. I et særskilt forskningsprojekt har vi arbejdet mod at udvikle en integreret kilde til kvantestøjsreduceret lys, og vi har på baggrund af et omfattende numerisk og teoretisk arbejde fremsat et optimeret design. Optiske mikroræsonatorer er blevet fabrikeret i henhold til designet, og indledende undersøgeler af strukturernes faktiske anvendelighed som kilder til kvantestøjsreducerede optiske tilstande er blevet udført. Dette arbejde er endnu ikke afsluttet.
Dimensionality Reduction for Deep Learning Based Intrusion Detection Systems for IoT

- Recent attacks on Internet of Things (IoT) devices have made it very important to provide a strong protection mechanism for IoT devices. A method of such protection mechanism is using Deep Learning models for Intrusion Detection Systems. Intrusion Detection Systems (IDS) can determine whether an invasion is currently ongoing or an intrusion has already occurred. In this study, the performance of the Deep Neural Network and Autoencoders were evaluated using the BoT-IoT dataset towards the development of binary classification model. The dataset was split into two; one for building the model and the other for validating it. The dataset was split into Normal-DoS, Normal-DDOS and Normal-Reconnaissance. This study has revealed that dimensionality reduction provided better classification of the dataset The model was developed for intrusion detection using DNN algorithms based on features extracted with and without Autoencoder for dimensionality reduction. The dimensionality reduction was performed to determine if it’s possible to identify features that would improve the information required to effectively classify network intrusions. It was revealed that AeNN increased the accuracy of the classification of the Normal-DoS dataset for the classification of network intrusion detection by +3.4%, +11.5%, +13.1% for three simulations and a decline of -2.1% in the fourth simulation.
Can Neural Networks Enhance Physics Simulations?

The primary objective of this research manuscript is to design, develop, and evaluate an artificial neural network architecture that is capable of emulating and predicting the dynamic interaction patterns manifested during the encounter between two distinct entities. This endeavor is primarily centered around computational learning and understanding of the associated physical impulses that emerge when these objects engage in contact, elucidating the complex physical interplays therein. This process incorporates the strategic use of an extant physics engine to generate the requisite training datasets, thereby providing a robust and comprehensive foundation for neural network training and subsequent performance evaluation. In order to scrutinize and substantiate the effectiveness of the proposed artificial neural network model, this investigation also embarks on a rigorous comparative analysis. The principal focus of this comparison is to juxtapose the results rendered by the trained neural network vis-a-vis those produced by the original physics engine. The goal here is to gauge the precision, reliability, and practicality of the trained model in accurately predicting the physical impulses, thereby demonstrating its potential to stand as a feasible alternative to the traditional physics engine. Despite the initial success of this endeavor, it is worth noting that the proposed neural network system managed to achieve a range of prediction rates, oscillating between 60% and 91%, contingent upon the specific test scenario. While these preliminary results are promising, they elucidate the necessity for further optimization and refinement to bolster the model's performance and prediction accuracy.
Transcending the Acceleration-Bandwidth Trade-off: Lightweight Precision Stages with Active Control of Flexible Dynamics

Micro/Nano-positioning stages are of great importance in a wide range of manufacturing machines and instruments. In recent years, the drastically growing demand for higher throughput and reduced power consumption in various IC manufacturing equipment calls for the development of next-generation precision positioning systems with unprecedented acceleration capability while maintaining exceptional positioning accuracy and high control bandwidth. Reducing the stage's weight is an effective approach to achieving this goal. However, the reduction of stages' weight tends to decrease its structural resonance frequency, which limits the closed-loop control bandwidth and can even cause stability issues. Aiming to overcome the aforementioned challenge and thus create new lightweight precision stages with substantially improved acceleration capability without sacrificing stage control performance, this research presents a novel sequential structure and control design framework for lightweight stages with low-frequency flexible modes of the stage being actively controlled. Additional actuators and sensors are placed to actively control the flexible structural dynamics of the lightweight stage to attain high control bandwidth. A case study is simulated to evaluate the effectiveness of the proposed approach, where a stage weight reduction of 24% is demonstrated compared to a baseline case, which demonstrates the potential of the proposed design framework. Experimental evaluation of the designed stage's motion performance will be performed on a magnetically levitated linear motor platform for performance demonstration.
Investigation of O -Alkyl/ O -Alkenyl Glycerolipid Ratios in Erythrocyte Lysates of Patients with Obstructive Sleep Apnea

Background: Vulnerabilities of plasmalogens in erythrocyte membrane to hypoxic conditions and alteration induced by sleep restriction make them potential biomarkers for the evaluation of sleep apnea related sleep disorders. Objective: We aimed to investigate and to compare ratios of alkyl/alkenyl glycerolipids of erythrocyte membranes (representing plasmanyl/plasmenyl plasmalogens) between controls and patients with sleep apnea and to evaluate possible differences, if any, which could be considered as a diagnostic tool. Material and methods: The patients underwent polysomnography and categorized according to the severity of sleep apnea using Apnea-Hypopnea Index (AHI). Phospholipids in erythrocyte lysates were hydrolyzed by phospholipase C and the acylgroups were saponified. Then the O -alkyl/ O -alkenyl glycerolipids were separated by thin-layer chromatography (TLC). Densitometric image analyses were performed on the lipid spots of TLC plates and the ratios were determined. Results: No significant correlation was observed between the alkyl/alkenyl glycerolipid ratios of the eryhtrocyte lysates of sleep apnea patients and that of controls. Conclusion: Results of this study warrants reinvestigation of alkyl/alkenyl glycerolipid ratios in erythrocytes of patients with sleep apnea, with each subjects sampled before and after the treatment of sleep apnea to better understand the potential of this ratio as a diagnostic tool.
Diversiﬁcation in Multi-Product Choices: Bias or Rational Utility Maximization?

This paper tests a theory of rational multi-product choice ( RMPC ) using empirical evidence from a large-scale choice experiment, two smaller longitudinal choice experiments, and multi-market panel data. Multi-product choice involves the selection of a set of substitutable products, where “set” incorporates both the product alternatives included and the number of units of each. Derived from a basic random utility framework, RMPC theory predicts that multi-product choices will reﬂect a tradeoﬀ between the intrinsic utility of products in a set and the consumption ﬂexibility aﬀorded by the structure of that set. Data from the large-scale choice experiment show that modeling this tradeoﬀ oﬀers superior predictions compared to other models for 3-, 4, and 5-product choice sets in two diﬀerent categories. Interestingly, we also ﬁnd that the modal variety is exactly three product alternatives for all choice set sizes and categories studied. Data from the longitudinal choice experiments provide support for RMPC theory’s prediction that consumption choice probabilities will be proportional to the inventories of available product alternatives. While consumption choices are found to be consistent with RMPC theory, they are not consistent with variety seeking. Finally, RMPC theory predicts that the variety in a consumer’s multi-product choice set will be higher for lower consumption rates, and lower for higher consumption rates. Evidence from panel data of yogurt purchases supports this proposition. Taken in its entirety, the empirical evidence presented in this paper conﬁrms that multi-product choices, in particular the product diversiﬁcation previously attributed to bias, are actually consistent with rational utility maximization
Dynamic Probabilistic Entailment. Improving on Adams' Dynamic Entailment Relation

The inferences of contraposition (A ⇒ C ∴ ¬C ⇒ ¬A), the hypothetical syllogism (A ⇒ B, B ⇒ C ∴ A ⇒ C), and others are widely seen as unacceptable for counterfactual conditionals. Adams convincingly argued, however, that these inferences are unacceptable for indicative conditionals as well. He argued that an indicative conditional of form A ⇒ C has assertability conditions instead of truth conditions, and that their assertability ‘goes with’ the conditional probability p(C|A). To account for inferences, Adams developed the notion of probabilistic entailment as an extension of classical entailment. This combined approach (correctly) predicts that contraposition and the hypothetical syllogism are invalid inferences. Perhaps less well-known, however, is that the approach also predicts that the unconditional counterparts of these inferences, e.g., modus tollens (A ⇒ C, ¬C ∴ ¬A), and iterated modus ponens (A ⇒ B, B ⇒ C, A ∴ C) are predicted to be valid. We will argue both by example and by calling to the results from a behavioral experiment (N = 159) that these latter predictions are incorrect if the unconditional premises in these inferences are seen as new information. Then we will discuss Adams’ (1998) dynamic probabilistic entailment relation, and argue that it is problematic. Finally, it will be shown how his dynamic entailment relation can be improved such that the incongruence predicted by Adams’ original system concerning conditionals and their unconditional counterparts are overcome. Finally, it will be argued that the idea behind this new notion of entailment is of more general relevance.
Digit Recognition Using Local Projection Dependent Clustering

Water companies utilize water meters to measure and calculate water usage bills. However, the current process employed by PDAM requires redundant resources, as it involves taking photos of each customer's house and having other officers read the numbers from the water meter images, resulting in inefficiency. The problem is further compounded by the neglect and improper maintenance of water meters, with some being buried in garbage or soil. Additionally, officers contribute to the challenges by capturing blurry and tilted photos, hindering the accurate reading of the water meter numbers. This study applies a water meter reading system by processing water meter photos and converting them into text using image processing methods to process images and Neural Networks to perform digit recognition. The image processing process includes steps such as (1) grayscale conversion, (2) gamma correction, (3) x-Histogram Projection, (4) White Temporal Ascent Accumulation, and (5) Peak Identification. Furthermore, image segmentation techniques are applied to enhance image quality and eliminate noise using clustering methods. The segmented images are then processed by a neural network to recognize the meter digits. The system achieves a digit recognition accuracy of 75.2%, despite encountering various technical and non-technical challenges during the water meter photo capture process.
First light at EBL2

TNO is building EBL2 as a publicly accessible test facility for EUV lithography related development of photomasks, pellicles, optics, and other components requiring EUV exposure. EBL2 consists of a EUV Beam Line, a XPS system, and sample handling infrastructure. Recently we finished installation of the source, exposure chamber, handlers and XPS system. This paper describes the integration process and first light of the EUV source.EBL2 accepts a wide range of sample sizes, including EUV masks with or without pellicles. All types of samples will be loaded using a standard dual pod interface. EUV masks returned from EBL2 will retain their NXE compatibility to facilitate wafer printing on scanners after exposure in EBL2. The Beam Line provides high intensity EUV irradiation from a Sn-fueled EUV source from Ushio. EUV intensity, spectrum, and repetition rate are all adjustable. The XPS system is now operational and accepts samples up to reticle size.
Transcendence : Measuring Intelligence

Among the many common criticisms of the Turing test, a valid criticism concerns its scope. Intelligence is a complex and multi-dimensional phenomenon that will require testing using as many different formats as possible. The Turing test continues to be valuable as a source of evidence to support the inductive inference that a machine possesses a certain kind of intelligence and when interpreted as providing a behavioural test for a certain kind of intelligence. This paper raises the novel criticism that the Turing test represents an example of Goodhart's Law operating in the field of artificial intelligence. As one measure towards the goal of creating genuinely intelligent machines, the Turing test must not be confused with the goal itself. Moreover, the Turing test ought to be augmented such that through its use additional evidence could be secured to support the strong inference that a machine, were it to pass the Turing Test, could think like a human.
Using Generated Object Reconstructions to Study Object-based Attention

Object-based attention operates by selecting complete object representations as a fundamental unit, but existing theories tend to focus on bottom-up cues, such as Gestalt principles, and have given relatively little attention to the influence of top-down signals on this process, as well as how bottom-up and top-down factors may interact. Here we propose that Object Reconstruction-guided Attention (ORA) may provide a useful framework to study the interplay between bottom-up and top-down factors in object-based attention. The ORA model encodes object-based representations to reconstruct object location and appearance, and utilizes this reconstructed information to further bias the bottom-up signal in the feedforward pass. The objective of the model is to best explain the input by selecting and reconstructing target objects with the lowest reconstruction error, creating an object-selection bias. Our results demonstrate that this simple reconstruction-based selection principle can support various visual tasks, providing new insights into the brain mechanisms underlying robust object-based attention and visual perception. Future work will extend this work to more naturalistic images and examine the model’s correspondence with human behavior.
Impact of Visual Distortion on Medical Images

—The distortion is a common occurrence in the imaging area, especially medical imaging. The most common kinds of distortion in medical imaging are blurry, contrast-and noise-distorted images. The purpose of this study is to provide a four-step technique for determining if current Objective Image Quality Assessment (IQA) mathematical models function as well as human eyes. Throughout the investigation, the appropriate quality and source of X-ray CT scans were chosen. The results indicate that the Perception-Based Image Quality Evaluator (PIQE) is a moderately effective mathematical model of No-Reference IQA (NR-IQA). However, in comparison to PIQE, both the Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) and the Naturalness Image Quality Evaluator (NIQE) performed poorly when used with X-ray CT scans.
Do Misstatement Correction Disclosures Reflect Impaired Auditor Independence?

Management has strong incentives to avoid correcting accounting misstatements through restatements, but auditor incentives are less clear. Using misstatement corrections disclosed in annual financial statements from 2006 to 2017, I investigate whether disclosures of misstatement corrections potentially reflect impaired auditor independence. I find that economically important clients and clients of non-specialist auditors are more likely to disclose misstatements as revisions or adjustments rather than as restatements. I also find that the magnitudes of disclosed revisions and adjustments are more likely to exceed traditional materiality thresholds for economically important clients and clients of non-specialist auditors. These relationships are strongest when audit offices experience negative client growth, when audit markets have high competition, when the auditor in the year of correction was also the auditor in the year of misstatement, and when the corrections have negative effects on financial statements. Overall, my study suggests that misstatement correction disclosures may reflect impaired auditor independence. As such, investors and regulators should exercise substantial skepticism as they identify and evaluate disclosures of misstatement corrections.