Miracle-dz/UniFAR-FTUs huggingface dataset:
mBAT-combo: a more powerful test to detect gene-trait associations from GWAS data

Gene-based association tests aggregate multiple SNP-trait associations into sets defined by gene boundaries. Since genes have a direct biological link to downstream function, gene-based test results are widely used in post-GWAS analysis. A common approach for gene-based tests is to combine SNPs associations by computing the sum of χ2 statistics. However, this strategy ignores the directions of SNP effects, which could result in a loss of power for SNPs with masking effects (e.g., when the product of the effects of two SNPs and their linkage disequilibrium (LD) correlation is negative). Here, we introduce “mBAT-combo”, a new set-based test that is better powered than other methods to detect multi-SNP associations in the context of masking effects. We validate the method through simulations and applications to real data. We find that of 35 blood and urine biomarker traits in the UK Biobank, 34 traits show evidence for masking effects in a total of 4,175 gene-trait pairs, indicating that masking effects in complex traits is common. We further validate the improved power of our method in height, body mass index and schizophrenia with different GWAS sample sizes and show that on average 95.7% of the genes detected only by mBAT-combo with smaller sample sizes can be identified by the single-SNP approach with larger sample sizes (average sample size increased by 1.7-fold). For instance, LRRC4B is significant only in our method for schizophrenia, which has been shown to play a role in presynaptic pathology using genetic fine-mapping and evidence-based synaptic annotations. As a more powerful gene-based method, mBAT-combo is expected to improve the downstream pathway analysis or tissue and cell-type enrichment analysis that takes genes identified from GWAS data as input to understand the biological mechanisms of the trait or disease. Despite our focus on genes in this study, the framework of mBAT-combo is general and can be applied to any set of SNPs to refine trait-association signals hidden in genomic regions with complex LD structures.
Transcriptome landscape of kleptoplastic sea slug Elysia viridis

Certain sacoglossan sea slugs can sequester and maintain photosynthetically active chloroplasts through algae feeding, a phenomenon called kleptoplasty. The period while these plastids remain active inside the slug’s body is species- and environment-dependent and can span from a few days to more than three weeks. Here we report for the first time the transcriptome of sea slug Elysia viridis (Montagu, 1804), which can maintain kleptoplasts for more than two weeks and is distributed along all the Atlantic European coastline. The obtained transcriptome of E. viridis comprised 12,884 protein-coding sequences (CDS). The shortest one was 261bp, and the longest 8,766bp; the whole transcriptome has a total length of 9.3Mb (Table S4 and Fig. S2). Analysing these CDS, we identified 9,422 different proteins, with best hits mainly from two genera: Elysia (87.2%), and Plakobranchus (11.0%) (Fig. S2); the other 2.3% corresponded to multiple genera of sea slugs and snails (Tectipleura) (Kano et al., 2016). We got the functional annotation (Gene Ontologies, GO) corresponding to 9,333 CDS: 4,755 CDS associated with 2,583 Biological Process (BP); 5,466 CDS linked to 683 Cellular Components (CC); and 6,693 related to 1,606 Molecular Functions (MF). We identified 201 CDS related to response to stress (GO:0006950) and 10 CDS associated with the regulation of response to stress (GO:0080134). Focussing on the ROS-quenching toolkit, we found 24 CDS related to oxidoreductase complex (GO:1990204) and 560 annotated with oxidoreductase activity (GO:0016491) acting in a large number of donors, e.g., CH-OH, CH=O, C=O, CH and CH2. In addition, we found 39 CDS with antioxidant activity (GO:00162099) and other CDS with ROS-quenching function: superoxide dismutase (GO:0004784), peroxidase (GO:0004601), glutathione oxidoreductase (GO:0097573) and peroxidase (GO:0004602); and thioredoxin peroxidase (GO:0008379) activity. Furthermore, we found 8 CDS related to the symbiont response (GO:0140546) and nine related to the pattern recognition receptor signalling pathway (GO:0002221).
Optimal reliability, robustness and control of nucleus centering in fission yeast is contingent on nonequilibrium force patterning

Cells, such as fission yeast, center their division apparatus to ensure symmetric cell division, a challenging task when the governing dynamics is stochastic. Here we show that the spindle pole body (SPB) positioning, which defines the division septum, is controlled by the patterning of nonequilibrium polymerization forces of microtubule (MT) bundles. We define two cellular objectives, reliability, the mean SPB position relative to the geometric center, and robustness, the variance of the SPB position, which are sensitive to genetic perturbations that change cell length, MT-bundle number/orientation and MT dynamics. We show that the optimal control of reliability and robustness required to minimize septum positioning error is achieved by the wild-type (WT). A stochastic model for the MT-based nucleus centering, with parameters measured directly or estimated using Bayesian inference, recapitulates WT optimality. We use this to perform a sensitivity analysis of the parameters that control nuclear centering.
Enhancing the Classification Performance of Machine Learning Techniques by Using Hjorth's and Other Statistical Parameters for Precise Tracking of Naturally Evolving Faults in Ball Bearings

The research on identification of artificially induced faults in bearing is available in abundance in the past literature, however, the diagnosis becomes more challenging when the fault evolves naturally inside the bearing, and especially when its stages need to be precisely tracked. The conventional statistical features used commonly in the past literature do not uniquely characterize the fault status, and yield satisfactory results only in limited cases, like those for artificial faults. In this work, a new combination of fault descriptors, including three Hjorth's parameters, three statistical features and an entropy measure, is proposed and its effectiveness has been analyzed on classification performances of k-Nearest Neighbor (k-NN) and Support Vector Machine (SVM). Two datasets comprising the signals of run-to-failure tests were taken from Intelligent Maintenance Systems (IMS) and the Paderborn university repository. The data were categorized into large number of classes to closely indicate the actual fault type and size. Compared to conventional statistical features, the new combination was able to enhance the classification accuracy of k-NN and SVM, respectively, from 91.3% to 99.9%, and from 94.8% to 99.7% in the case of IMS dataset, and from 94.1% to 98.5%, and from 94.7% to 98.4% in the case of Paderborn dataset. In addition to accuracy, the performance metrics, including precision, recall, and F1-score were also improved using the proposed combinatory features.
A 100Gbps User Plane Function Prototype Based on Programmable Switch for 5G Network

User Plane Function (UPF) plays a crucial role in the 5G core network, which is vital to improve UPF performance. In this prototype, we provide novel UPF architecture with a programmable switch. The implemented UPF prototype can provide up to 100Gbps matching throughput within 1 microsecond(us) latency. Moreover, the prototype is feasible in the real network.
To Be or Not To Be Informed, That Is the Question of Oo ntology

The relations between ontology and information are many and fundamental, and they help us to understand the present gulf between (formal) o ntology and (philosophical) O ntology: We can speak of respectively ontology-driven information and information-driven ontology as the focus on being informed vs. informed being. The question of whether these two (can) coincide is relevant to both ﬁelds, and in this article I elaborate on what needs to be addressed ﬁrst of all to provide us with an answer: The form . This core ontological concept rooting in Aristotelian metaphysics was central to philosophical ontology, in particular in Latin Scholasticism, when it was clearly put into relation with information as that which deﬁnes an entity. In this context, Dietrich of Freiberg synthesized this long debate in a way that matters not only to the philosophical eﬀort of producing information-driven ontologies but also to the engineering constructs of ontology-driven information systems.
Entwicklung eines Korrekturmodells für BioNER

Biomedical Named Entity Recognition (BioNER) wird benutzt, um Entitäten aus biomedizinischen Texten zu extrahieren [1,2]. Bei den Entitäten kann es sich z.B. um Gene, Proteine oder Krankheiten handeln. Es existieren verschiedene Methoden, um BioNER zu realisieren [3]. Die meisten BioNER-Modelle benutzen Supervised Learning. Bei diesem Ansatz werden Modelle auf Daten mit bekannten Labels trainiert. Um eine hohe NER-Performance zu erreichen, werden qualitative annotierte Trainingsdaten benötigt. Häufig werden Domänenexperten wie z.B. Ärztinnen und Ärzte verschiedener Fachrichtungen bei dem Annotationsprozess eingesetzt, um einen qualitativen Goldstandard-Korpus zu erstellen. Diese Annotationsprozesse sind zeitund kostenintensiv. Deswegen existieren oft nur kleine Goldstandard-Korpora, die für das Trainieren und Evaluieren von BioNER-Modellen benutzt werden können. Die geringen Datenmengen erschweren zudem die Generalisierbarkeit der BioNER-Modelle und damit die Anwendung auf ungesehene Texte [1,4]. Grundsätzlich wird versucht, den Erstellungsprozess von Trainingsdaten weitgehend zu automatisieren, um damit den manuellen Aufwand zu reduzieren. Ein semi-automatischer Ansatz ist beispielsweise zuerst mit einem BioNER-Modell einen Zielkorpus zu annotieren, der anschließend von Expertinnen und Experten korrigiert wird. Die Annotationsgenauigkeit von BioNER-Modellen ist häufig zu ungenau, sodass der Korrekturaufwand durch die Experten immer noch hoch ist [1]. Fehlende Generalisierbarkeit, Domänenwechsel oder andere Annotationsrichtlinien können die Vorhersagegenauigkeit der BioNER-Modelle verringern [1,5]. In dieser Masterarbeit wird untersucht, ob mit einem Korrekturmodell der manuelle Aufwand bei der Annotation von Korpora gesenkt werden kann. Für die Vorannotation eines Korpus kann ein BioNER-Modell benutzt werden. Dann wird ein Korrekturmodell eingesetzt, um die Annotationsgenauigkeit des vorannotierten Korpus zu verbessern. Mit Goldstandard-Korpora aus unterschiedlichen Domänen wird der Korrekturprozess simuliert. Es werden verschiedene Varianten des Korrekturmodells erprobt und evaluiert. Zudem wird analysiert, welchen Einfluss die Menge der Trainingsdaten auf die Güte des Modells hat.
BalanceProofs: Maintainable Vector Commitments with Fast Aggregation

We present BalanceProofs , the first vector commitment that is maintainable (i.e., supporting sublinear updates) while also enjoying fast proof aggregation and verification. The basic version of BalanceProofs has O ( √ n log n ) update time and O ( √ n ) query time and its constant-size aggregated proofs can be produced and verified in milliseconds. In particular, BalanceProofs improves the aggregation time and aggregation verification time of the only known maintainable and aggregatable vector commitment scheme, Hyperproofs (USENIX SECURITY 2022), by up to 1000 × and up to 100 × respectively. Fast verification of aggregated proofs is particularly useful for applications such as stateless cryptocurrencies (and was a major bottleneck for Hyperproofs), where an aggregated proof of balances is produced once but must be verified multiple times and by a large number of nodes. As a limitation, the updating time in BalanceProofs compared to Hyperproofs is roughly 6 × slower, but always stays in the range from 10 to 18 milliseconds. We finally study useful tradeoffs in BalanceProofs between (aggregate) proof size, update time and (aggregate) proof computation and verification, by introduc-ing a bucketing technique, and present an extensive evaluation as well as a comparison to Hyperproofs.
M. Sc. thesis expos´e: Interpretable Rationale Extraction within Named Entity Recognition

While neural networks have produced recent breakthroughs in a vast array of Machine Learning tasks, the inner workings of models produced in this way are unfortunately quite opaque which makes it hard for humans to understand the decision making process. As a result, researchers and companies are faced with certain problems. These range from an interest in identifying the shortcomings of a given model (in order to debug and improve it) to compliance with legal requirements such as pushes from EU lawmakers for a ’right to explanation’ of machine-made decisions. [1] This includes the identification of discriminatory biases inherent in systems trained on real-world data. [2] These problems have sparked an interest in both creating interpretable systems and making existing systems explainable. Explanations that can serve this purpose are called rationales and the task of acquiring them is called Rationale Extraction. [3] In the context of Natural Language Processing, a rationale is usually either a list of the k most important tokens wrt their importance in the decision making process or a continuous span of tokens with the length k. The latest research in the field of NLP has already produced a few insights into how NLP models could potentially make explainable decisions. [4] But the focus of this research has so far been mostly on Text Classification tasks whereas other standard NLP tasks such as Named Entity Recognition (NER) have seen little to no publications with regards to interpretability yet. The goal of this Master’s thesis shall be to choose and adapt one of the suggested approaches to create interpretable NER models that can be evaluated in comparison with the performance of their non-interpretable variants and in terms of quality of the resulting explanations. The datasets used will be focussing on the domain of biomedical information extraction.
Application of Metal/Metal Oxide Doped Electrospun Nanofiber Membranes in Sustainable Catalysis

The unsustainability of the production of catalysts due to limited resources and higher energy demands makes it critical to explore and reengineer new catalytic materials for future applications. Woefully, the unrelenting demand for the metals/metal oxides increases both the financial and environmental cost, particularly in mining and synthesis, rendering consumption unsustainable in its current form. In this context, electrospinning offers a new template for designing sustainable ways of minimizing the higher loading of catalysts and recyclability. In this context, metals/metal oxide doped electrospun membranes have grasped a great scientific interest as sustainable catalysts due to their enhanced catalytic activity and synergistic structure-property relationship of the doped material and the matrix. More specifically, the selectivity arising from the electronic properties and quantum mechanical interactions at the nanoscale of metal/metal oxide nanoparticles coupled with interactions at the electrospun membrane interfaces lead to such enhanced properties. This review article summarizes the applications of metals/metal doped electrospun membranes in different aspects of catalysis, such as thermocatalysis, photocatalysis, organocatalysis and electrocatalysis, with a particular focus on their sustainability.
A blockchain-based digital wallet application with HoneyBadger-BFT consensus algorithm

HoneyBadger-BFT [4] is a consensus algorithm for blockchain that can tolerate Byzantine fault in an asynchronous network. However, there has never been a public blockchain that utilizes HoneyBadger. At the same time, public blockchain such as Bitcoin [5] uses Proof-of-Work to solve consensus, which is not power-efficient. In this project, we explore the possibility of HoneyBadger-BFT by building a simple digital wallet applications built on top of a blockchain that utilizes HoneyBadger-BFT. Our system provides a simple user interface for clients to register accounts and submit transactions, all records of which is recorded on the blockchain, which is totally ordered among all replicas in the system.
BEST PRACTICES THAT ENABLE EQUITABLE GENDER RELATIONS CAN HELP OVERCOME GENDER-BASED CONSTRAINTS AMONG LIVESTOCK KEEPERS IN ETHIOPIA A LOOK AT FOUR-VALUE CHAIN SITES IN ETHIOPIA

The negative effect of social norms, as structural barriers to progress achieving gender equality, is established beyond doubt (Aguilar et al., 2014; Didana, 2019; Legovini, 2006). With the premise that gender equality and women’s empowerment improve agricultural outcomes (Najjar et al., 2019), development efforts have so far increased women’s perceived empowerment and freedom but this has not always resulted in altering norms (Boudet et al., 2013). Few studies have looked into the reasons behind this.
Semantic Segmentation Through Graph Neural Network Blocks

Semantic segmentation task aims to create a dense classification by labeling pixel-wise each object present in images. Convolutional Neural Network (CNN) approaches have been proved useful by exhibiting the best results in this task. However, some challenges remain, such as the lowresolution of feature maps and the loss of spatial precision, both produced in the CNNs by limited local neighborhoods, i.e., filters with small size. In this work, we propose an encoder-decoder architecture with skip connections based on Graph Neural Network (GNN) (hereafter called GNNblock). This GNN-block proved to have a greater receptive field by having a global vision of objects and their relationships, thus providing additional global information to the model. Finally, we present preliminary results on Cityscape database, achieving close performance with state-of the-art.
Three-body model of 6Li using hyperspherical harmonics

The method of hyperspherical harmonics (also called $K$ harmonics) is applied to the $\ensuremath{\alpha}\ensuremath{-}\ensuremath{\eta}\ensuremath{-}p$ model of $^{6}\mathrm{Li}$. The ground state (${J}^{\ensuremath{\pi}}={1}^{+}$) and the ${J}^{\ensuremath{\pi}}={0}^{+}$ excited state at 3.56 MeV are examined. Gaussian type $\ensuremath{\alpha}$-nucleon potentials and nucleon-nucleon potentials are used. By expanding the wave functions and the total potential of the system in terms of hyperspherical harmonics, coupled differential equations for the hyperradial part of the wave functions are derived from the Schr\"odinger equation. Binding energies of the two states, the charge form factor of the ground state, and the magnetic form factor are calculated. Only the grand orbital zero term is used. Comparison with the experimental data is given.
The Currents Coordinative Control Strategy for Integrated Motor-Drive and Battery-Charging System Based on the Split-Field-Winding DSEM in Driving Mode

This article proposes a currents coordinative control strategy for the integrated motor-drive and battery-charging system based on the split-field-winding doubly salient electromagnetic machine (DSEM) in driving mode, where the field windings are reused as the filter inductance of the front-end dc–dc converter. The combined strategy of maximum field current and the minimum copper loss control methods with respect to the error between the reference and feedback speed of DSEM is given. Compared to the traditional constant field control of DSEM, the copper loss in steady-state operation could be reduced significantly for higher efficiency, especially in light load conditions, and the maximum output power could also be obtained to improve the dynamic performance of the proposed system. The effectiveness and reliability of the proposed control strategy are verified by simulation and experiment results.
The Role of Technological Innovation in Improving the Egyptian Hotel Brand Image.

Loyalty ABSTRACT Despite the formidable significance of technological innovation and brand image in the hotel industry. Literature has revealed limited research into this aspect, especially in the Egyptian hotel industry. Less research examined the antecedents of customer satisfaction and loyalty to technological innovation. This study aims to investigate the role of technological innovation in improving the hotel brand image, as manifested by the customer evaluation of hotel technological collaboration and expertise of the hotel and hotel brand image through their satisfaction and loyalty in the Egyptian hotel sector. A survey of 254 five-star customers has confirmed a newly proposed model to improve the Egyptian hotel brand image. Structural equation modelling has been used for hypothesis testing. The research results indicate that technology innovations have significantly positive effects on customer satisfaction and loyalty. Moreover, the tandem mediation of customer satisfaction antecedents (i.e., security, product and service merchandise, ease of use, perceived service quality and information quality) reinforces their loyalty toward the hotel brand. Finally, the mediation of customer loyalty dimensions (i.e., relationships, trust, emotional benefits, and perceived value) significantly improves the hotel brand image
Practices of Care in a Multipavilion Prison: An Exploratory Study on the Role of the Built Environment

People’s health and well-being is known to be affected by the built environment. Since prisons are confronted with an overrepresentation of people with mental and physical health issues, we examine how the built prison environment affects the provision of care for prisoners with specific needs. Based on observations and (focus group) interviews with prisoners, prison officers, and care-staff, we report on the experiences of specific groups in highly particular prison environments: various pavilions of a former penal colony. By analyzing spatialities in relation to practices and temporalities of care, we provide a nuanced understanding of what caring entails in a prison environment. We show that in this context caring for safety, normality, and physical health ideally go hand in hand. To conclude, we illustrate that the need for control within a prison environment can be reduced by spatial variety, offering different types of settings matching different care and living needs, and allowing movement between settings depending on these needs.