Miracle-dz/UniFAR-FTUs huggingface dataset:
Knowledge-Augmented Language Models for Cause-Effect Relation Classification

Previous studies have shown the efficacy of knowledge augmentation methods in pretrained language models. However, these methods behave differently across domains and downstream tasks. In this work, we investigate the augmentation of pretrained language models with knowledge graph data in the cause-effect relation classification and commonsense causal reasoning tasks. After automatically verbalizing triples in ATOMIC2020, a wide coverage commonsense reasoning knowledge graph, we continually pretrain BERT and evaluate the resulting model on cause-effect pair classification and answering commonsense causal reasoning questions. Our results show that a continually pretrained language model augmented with commonsense reasoning knowledge outperforms our baselines on two commonsense causal reasoning benchmarks, COPA and BCOPA-CE, and a Temporal and Causal Reasoning (TCR) dataset, without additional improvement in model architecture or using quality-enhanced data for fine-tuning.
Proceedings of the Annual Meeting of the Cognitive Science Society Word order affects the frequency of adjective use across languages

Word order affects the frequency of adjective use across languages Abstract Recent research has proposed that adjective form (i.e., whether adjectives typically occur before or after the nouns they modify) interacts with considerations from efﬁcient communication to determine the rate at which we use adjectives to resolve reference to objects. According to this efﬁciency hypothesis, languages with pre-nominal adjectives use modifying adjectives at a higher rate in an effort to aid incremental reference resolu- tion. We test this broad typological prediction in a large-scale corpus analysis of 74 languages, ﬁnding that languages that favor pre-nominal adjectives indeed do exhibit higher rates of adjectival modiﬁcation than languages that favor post-nominal adjectives.
Robust Unsupervised Cross-Lingual Word Embedding using Domain Flow Interpolation

This paper investigates an unsupervised approach towards deriving a universal, cross-lingual word embedding space, where words with similar semantics from different languages are close to one another. Previous adversarial approaches have shown promising results in inducing cross-lingual word embedding without parallel data. However, the training stage shows instability for distant language pairs. Instead of mapping the source language space directly to the target language space, we propose to make use of a sequence of intermediate spaces for smooth bridging. Each intermediate space may be conceived as a pseudo-language space and is introduced via simple linear interpolation. This approach is modeled after domain flow in computer vision, but with a modified objective function. Experiments on intrinsic Bilingual Dictionary Induction tasks show that the proposed approach can improve the robustness of adversarial models with comparable and even better precision. Further experiments on the downstream task of Cross-Lingual Natural Language Inference show that the proposed model achieves significant performance improvement for distant language pairs in downstream tasks compared to state-of-the-art adversarial and non-adversarial models.
UC Merced Proceedings of the Annual Meeting of the Cognitive Science Society

This is a modern horror story about an innocently misbehaving projector, and why we beseech everyone to report minimal colorimetric data about stimulus displays. We present anecdotal experience of conﬁguring a projector to display video stimuli in a high-tesla MRI room, along with all the gotchas, (broken) technical assumptions, and theoretical rehashings that should be considered by every scientist who uses computers to display visual stimuli. The moral of our story is: (1) check that your monitor/projector is actually showing the colors and lu-minances that you think it is, (2) make explicit assumptions regarding the physical/perceptual space of your stimuli and how they relate to any model analysis you will perform. This is especially important when modeling non-human animals, since most equipment and data formats implicitly assume human perception. We show that innocent changes to display settings such as brightness reduction can cause dangerously unexpected results. Understanding and reporting colorimetric data in scientiﬁc publications is important for two reasons: (1) reproducibility, and (2) model ﬁdelity.
REVIEW PAPER ON STRUCTURAL BEHAVIOUR OF INDUSTRIAL PALLET RACK WITH BRACED AND UNBRACED FRAMES

According to the structural point of view Industrial Pallet rack structure can be considered typical steel framed structure. This work presents a general analysis of an industrial pallet rack structure, evaluating the influence of each of the components on the global stability. An analytical study for the sensitivity of pallet rack configuration in linear static equivalent lateral loads. The aim is to braced/unbraced frames were design and their analytical models are to be built in software. The finite element analysis is used to determine axial forces in beam and column, maximum storey displacement and buckling loads on braced/unbraced pallet rack structure. Bracing systems are mostly provided to enhance the stiffness factor of the structures with the seismic loads. Unbraced systems have mostly translational modes of failure and are very flexible due to excessive loads.
A Taxonomy of Academic Abstract Sentence Classification A Taxonomy of Academic Abstract Sentence Classification Modelling Modelling

Background: Abstract sentence classification modelling has the potential to advance literature discovery capability for the array of academic literature information systems, however, no artefact exists that categorises known models and identifies their key characteristics. Aims: To systematically categorise known abstract sentence classification models and make this knowledge readily available to future researchers and professionals concerned with abstract sentence classification model development and deployment. Method: An information systems taxonomy development methodology was adopted after a literature review to categorise 23 abstract sentence classification models identified from the literature. Corresponding dimensions and characteristics were derived from this process with the resulting taxonomy presented. Results: Abstract sentence classification modelling has evolved significantly with state-of-the-art models now leveraging neural networks to achieve high performance sentence classification. The resulting taxonomy provides a novel means to observe the development of this research field and enables to consider how such models can further improved or deployed in real-world applications.
A Design of Anisotropic Wet Etching System to Reduce Hillocks on Etched Surface of Silicon Substrate

— This research aims to design and build a wet etching system, which is suitable for anisotropic wet etching, in order to reduce etching time, to reduce hillocks on the etched surface (to reduce roughness), and to create a 45-degree wall angle (micro-mirror). This study would start by designing a wet etching system. There are four main components in this system: an ultrasonic cleaning, a condenser, a motor and a substrate holder. After that, an ultrasonic machine was modified by applying a condenser to maintain the consistency of the solution concentration during the etching process and installing a motor for improving the roughness. This effect on the etch rate and the roughness showed that the etch rate increased and the roughness was reduced.
Holistic Modeling In Medical Image Segmentation Using Spatial Recurrence

In clinical practice, regions of interest in medical imaging (MI) often need to be identified through a process of precise image segmentation. For MI segmentation to generalize, we need two components: to identify local descriptions, but at the same time to develop a holistic representation of the image that captures long-range spatial dependencies. Unfortunately, we demonstrate that the start of the art does not achieve the latter. In particular, it does not provide a modeling that yields a global, contextual model. To improve accuracy, and enable holistic modeling, we introduce a novel deep neural network architecture endowed with spatial recurrence. The implementation relies on gated recurrent units that di-rectionally traverse the feature map, greatly increasing each layers receptive field and explicitly modeling non-adjacent relationships between pixels. Our method is evaluated in four different segmentation tasks: nuclei segmentation in microscopy images, colorectal polyp segmentation in colonoscopy videos, liver segmentation in abdominal CT scans, and aorta artery segmentation in thoracic CT scans. Our experiments demonstrate an average improvement in performance of 4.72 Dice points and 0.68 Hausdorff distance units comparing to U-Net and U-Net++, and a performance better or on par when compared to transformer-based architectures. Code available at https://github.com/JoaoCarv/holistic-seg
Modeling and Simulation of a flexible Damper during Ice in Propeller Impacts

In the beginning the problematic of ice impacts on a ships drive train and the similarity of this work to last year's thesis from Bjørn Eliassen Vik is mentioned. After that the Bond-Graph-Methodology on which this thesis is based in shortly explained. Then the modeling of the coupling is explained. Here the coupling is divided into parts and modeled separately. A particular interest is on the dynamic behavior of the springs. These parts are then joined together. In the next chapter the coupling model is compared to the values given by the manufacturer. It shows that the model is too sti . Therefore the thickness of the springs and the bulk-modulus of the oil is adjusted until it matches the template. The model is than tested by varying the excitation frequency, the resistance of the load and the inertia of the coupling. It shows that the frequency has a great in uence on the sti ness of the system, the resistance a limited in uence and the inertia an in uence on the nominal frequency of the system. In the end the coupling is inserted into a drive train model. First it is simulated in open water, than an additional ice load is placed upon the propeller. The results are compared to simulations of the drive train with a simpler coupling and without a coupling. The results show that both couplings have damping capabilities. However, the ice load is too little to determine the e ect of sudden peak loads properly.
[R E ] G RAPH N EURAL F AKE N EWS D ETECTION WITH E XTERNAL K NOWLEDGE

The presented work aims to reproduce the results from the ACL-IJCNLP paper by Hu et al. [2021], titled "Compare to The Knowledge: Graph Neural Fake News Detection with External Knowledge". This work is done within the scope of the ML Reproducibility Challenge 2021. I focus on two aspects of the paper: the method itself and the validity of the stated results. I show that, despite some differences in the obtained results, the proposed method performs the expected way
Searching for the Strong AI for Cybersecurity

Currently, the creation of strong artificial intelligence (eng. Strong Artificial Intelligence (AI)) to ensure the required cybersecurity of digital platforms Industry 4.0 is one of the most interesting scientific and technical problems of our time. In the 1940s, when Norbert Wiener's book Cybernetics, or Control and Communication in the Animal and in the Machine, and other scientific papers on this topic were published, when the first computers of the von Neumann architecture appeared and began to be distributed. The mentioned problem was transferred from the field of science fiction to the field of real theoretical research and engineering developments. Since then, experts in the field of cyber security have been eagerly awaiting the emergence of fundamentally new technical information protection systems, the level of intelligence of which will be comparable to that of humans. That is, such engineering solutions, the distinctive ability of which will be the independent association and synthesis of new knowledge. Let's take a brief look at the history of the issue and dwell in more detail on the possible formulation of tasks for creating strong cybersecurity artificial intelligence.
Over-Mutated Mitochondrial, Lysosomal and TFEB-Regulated Genes in Parkinson’s Disease

The association between Parkinson’s disease (PD) and mutations in genes involved in lysosomal and mitochondrial function has been previously reported. However, little is known about the involvement of other genes or cellular mechanisms. We aim to identify novel genetic associations to better understand the pathogenesis of PD. We performed WES in a cohort of 32 PD patients and 30 age-matched controls. We searched for rare variants in 1667 genes: PD-associated, related to lysosomal function and mitochondrial function and TFEB-regulated. When comparing the PD patient cohort with that of age matched controls, a statistically significant burden of rare variants in the previous group of genes were identified. In addition, the Z-score calculation, using the European population database (GnomAD), showed an over-representation of particular variants in 36 genes. Interestingly, 11 of these genes are implicated in mitochondrial function and 18 are TFEB-regulated genes. Our results suggest, for the first time, an involvement of TFEB-regulated genes in the genetic susceptibility to PD. This is remarkable as TFEB factor has been reported to be sequestered inside Lewy bodies, pointing to a role of TFEB in the pathogenesis of PD. Our data also reinforce the involvement of lysosomal and mitochondrial mechanisms in PD.
Implementation of object-oriented programming in study of electrical race car

The paper covers issue of conducting advanced research of electrical race car participating in international competition called Sileverline Corporate Challenge. Process of designing race cars in Silesian Greenpower team is aided by a professional engine test stand built particularly in purpose of this research. Phase of testing and simulation is an important part of the implementation of new technologies. Properly developed solutions and test procedures are able to significantly shorten development time and reduce design costs. Testing process must be controlled by a modular and flexible application, easy to modify and ensuring safety. This paper describes the concept of object-oriented programming in LabVIEW and exemplary architecture of object-oriented control application designed to control engine test stand of the electrical race car. Eventually, the task of application will be to steer the electromagnetic brake and the engine load torque to perform according to data from the actual race track. During the designing process of the car, minimizing energy losses and maximizing powertrain efficiency are the main aspects taken into consideration. One of the crucial issues to accomplish these goals is to maintain optimal performance of the motor by applying effective cooling. The paper covers the research verifying the effectiveness of the cooling system.
The Analysis of E-plane Metal Lens in Beam Forming

In communication system, for the different application, it's need antenna provide different pattern, such as cosecant squared pattern, The antenna with cosecant square pattern can rapidly find object, and cover the larger effective region, so the antenna which have cosecant squared pattern is widely used in the radar system. This article will analyze how to use E-plane metal lens to realize beam forming, and designed a kind of E-plane metal lens which can realized cosecant squared beam forming in 9.5GHz. v is less than 0 v which is the phase velocity in the free space. So the phase distribution of the electromagnetic wave can be changed by using the characteristic that the metal-plate lens can change the phase velocity. In antenna applications, this feature can be used to obtain the desired phase distribution. Reference (3) using metal-plate lens realized beam forming for the horn antenna's elevation plane, Reference (4) using metal-plate lens realized beam forming for the horn antenna's horizontal plane. This article will put aside all the specific applications, analysis and explain why the E-plane metal lens can realize beam forming, and designed a kind of E-plane metal lens which can realized cosecant squared beam forming in 9.5GHz.
Development of Drought Tolerant Transgenic Cotton through Agrobacterium Mediated Transformation

: The growth and productivity of cotton (Gossypiumhirsutum L.) are adversely affected by abiotic stresses such as dehydration. Plants adaptation to these stresses is controlled by cascades of molecular networks, including the dehydration responsive element binding (DREB) transcription factors, which specifically interact with C-repeat/DRE (A/GCCGAC), play an important role in plant environmental stress tolerance by controlling the expression of many stress related genes. In this work, an optimized cotton regeneration system from shoot apices was developed. The hypocotyl explants were transformed with Agrobacterium tumefaciens strain LBA4404 harboring the recombinant binary vector containing the DREB gene and Neomycin phosphotransferase (nptII) gene as a selectable marker under the control of CaMV 35S promoter. New putative plantlets were subsequently regenerated and confirmed by Polymerase chain reaction and southern blot analysis.
The Art of Wireless Sensor Networks: Volume 1 Fundamentals

During the last one and a half decades, wireless sensor networks have witnessed significant growth and tremendous development in both academia and industry.The Art of Wireless Sensor Networks: Volume 1: Fundamentals focuses on the fundamentals concepts in the design, analysis, and implementation of wireless sensor networks. It covers the various layers of the lifecycle of this type of network from the physical layer up to the application layer. Its rationale is that the first volume covers contemporary design issues, tools, and protocols for radio-based two-dimensional terrestrial sensor networks.All the book chapters in this volume include up-to-date research work spanning various classic facets of the physical properties and functional behavior of wireless sensor networks, including physical layer, medium access control, data routing, topology management, mobility management, localization, task management, data management, data gathering, security, middleware, sensor technology, standards, and operating systems. This book will be an excellent source of information for both senior undergraduate and graduate students majoring in computer science, computer engineering, electrical engineering, or any related discipline. In addition, computer scientists, researchers, and practitioners in both academia and industry will find this book useful and interesting.
Intubation and Inhospital mortality in trauma patients with Glasgow Coma Scale Score eight or less. A multicenter cohort study.

Abstract : Background :Most trauma societies recommend intubation of trauma patients with Glasgow coma scale (GCS) [≤] 8, without robust evidence supporting it. Methods We examined the association between intubation and inhopital 30 day mortality in trauma patients arriving with GCS [≤] 8. The data were obtained using the Towards Improved Trauma Care Outcomes (TITCO) registry in India cohort. We compared the outcomes of patients with GCS [≤] 8 who were intubated within one hour after arrival with those who were intubated later or not at all, using multiple analytical approaches to evaluate the consistency of the findings. We also examined the association in multiple subgroups to identify any variability of the effect. Results: Of 3476 patients who arrived with a GCS [≤] 8, 1671 (48.1%) were intubated within an hour and 1805 (51.9%) were intubated later or not intubated at all. Overall, 1957 (56.3%) patients died in whole cohort. A total of 947 (56.7%) patients died in intubation group and 1010 (56%) died in non intubation group. In the main analysis, there was no significant association between intubation within an hour and mortality(OR=1.18,[CI,0.76-1.84], p value = 0.467). This result was consistent across multiple sensitivity analysis. Conclusion: In this observational study of trauma patients with GCS [≤] 8, who present to tertiary care hospitals, intubation within one hour after arrival was not associated with increased or decreased risk of inhospital mortality compared to intubation after one hour or no intubation. Further studies are needed to precisely evaluate the benefit of intubation and thus supporting the recommendations.
Informal sector employment and the health outcomes of older workers in India

A large proportion of the older population in India constitutes an undeniable share of workforce after the retirement age. This stresses the need to understand the implications of working at older ages on health outcomes. The main objective of this study is to examine the variations in health outcomes by formal/informal sector of employment of older workers using the Longitudinal Ageing Study in India. Using binary logistic regression models with interaction terms, the results of this study affirm that type of work does play a significant role in determining health outcomes even after controlling socio-economic, demographic, life-style behaviour, and work characteristics. The risk of Poor Cognitive Functioning (PCF) is high among informal workers, while formal workers suffer greatly from Chronic Health Conditions (CHC) and Functional Limitations (FL). The presence of CHC among informal workers is more damaging because it elevates their FL, whereas for formal workers presence of FL is unfavourable because it deteriorates their cognitive functioning. Therefore, present study underscores the relevance of policies focusing on providing health and healthcare benefits by respective economic activity and socio-economic position of older workers.
An Assessment of a Complex Training System’s Resilience to Change Associated with the Introduction of the Live-Virtual-Constructive Training Paradigm

Introducing the Live-Virtual-Constructive (LVC) training paradigm into live air combat training means introducing significant changes into a complex and established training system. To facilitate the transition, research was performed to identify possible new hazards that might emerge as a result of the changes and to assess the ability of the live training system to withstand them. Aircrew interviews were conducted and submitted to qualitative analysis, the results of which were further assessed by air combat experts, to identify both potential hazards and mechanisms the training system uses to withstand, or be resilient to, hazards. This paper focuses on those system resilience mechanisms and their adequacy for protecting system effectiveness and aircrew safety in the face of changes associated with the adoption of LVC training.