Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalization of spatio-temporal deep learning for vision-based force estimation

: Robot-assisted minimally-invasive surgery is increasingly used in clinical practice. Force feedback offers potential to develop haptic feedback for surgery systems. Forces can be estimated in a vision-based way by capturing deformation observed in 2D-image sequences with deep learning models. Variations in tissue appearance and mechanical properties likely influence force estimation methods ’ generalization. In this work, we study the generalization capabilities of different spatial and spatio-temporal deep learning methods across different tissue samples. We acquire several data-sets using a clinical laparoscope and use both purely spatial and also spatio-temporal deep learning models. The results of this work show that generalization across different tissues is challenging. Nevertheless, we demonstrate that using spatio-temporal data instead of individual frames is valuable for force estimation. In particular, processing spatial and temporal data separately by a combination of a ResNet and GRU architecture shows promising results with a mean absolute error of 15.450 compared to 19.744 mN of a purely spatial CNN.
Non-syndromic hearing loss: clinical and diagnostic challenges

Abstract Hereditary hearing loss is clinically and genetically heterogeneous. There are presently over 120 genes that have been associated with non-syndromic hearing loss and many more that are associated with syndromic forms. Despite an increasing number of genes that have been implemented into routine molecular genetic diagnostic testing, the diagnostic yield from European patient cohorts with hereditary hearing loss remains around the 50 % mark. This attests to the many gaps of knowledge the field is currently working toward resolving. It can be expected that many more genes await identification. However, it can also be expected, for example, that the mutational signatures of the known genes are still unclear, especially variants in non-coding or regulatory regions influencing gene expression. This review summarizes several challenges in the clinical and diagnostic setting for hereditary hearing loss with emphasis on syndromes that mimic non-syndromic forms of hearing loss in young children and other factors that heavily influence diagnostic rates. A molecular genetic diagnosis for patients with hearing loss opens several additional avenues, such as patient tailored selection of the best currently available treatment modalities, an understanding of the prognosis, and supporting family planning decisions. In the near future, a genetic diagnosis may enable patients to engage in preclinical trials for the development of therapeutics.
Characterization of cellular and viral microRNAs in Kaposi's sarcoma -associated herpesvirus malignancies

MicroRNAs are regulated by gene alteration, transcription, and processing. Thus far, few studies have simultaneously assessed all 3 levels of regulation. Using real-time quantitative polymerase chain reaction (QPCR)–based arrays, we determined changes in gene copy number, pre-miRNA, and mature miRNA levels for the largest set of primary effusion lymphomas (PELs) to date. We detected PELspecific miRNA gene amplifications, and concordant changes in pre-miRNA and mature miRNA. We identified 68 PEL-specific miRNAs. This defines the miRNA signature of PEL and shows that transcriptional regulation of pre-miRNA as well as mature miRNA levels contribute nonredundant information that can be used for the
Evaluation of Basic Trainings for Rescue Forces

Abstract Since members of rescue forces such as firefighters have to deal with sometimes extreme and dangerous situations, high-quality basic trainings are indispensable for their professional success. There is therefore an obvious need for standardized tools assessing the training quality. This paper aims to develop and validate such an evaluation instrument. In Study 1, a qualitative analysis (N = 21) was used to identify core characteristics of good firefighter basic trainings and served as theoretical basis for the generation of corresponding items. In Study 2 (N = 257), the item set was piloted and reduced, its structure was assessed in exploratory factor analyses, and first validations were conducted. Study 3 (N = 451) tested the proposed factor structure via confirmatory analyses and validated the questionnaire comprehensively. Factor analyses showed a six-factor structure. The scales of the newly created Feedback Instrument for Rescue forces Education – Basic education (FIRE-B) are to be judged as reliable. Moreover, there are several clear indications of validity. Thus, the present research contributes to the understanding of critical factors and processes of basic trainings. Furthermore, the FIRE-B has a high practical relevance, both in the assessment of training quality and in the identification of opportunities for improvement.
Optical Potts machine through networks of three-photon down-conversion oscillators

Abstract In recent years, there has been a growing interest in optical simulation of lattice spin models for applications in unconventional computing. Here, we propose optical implementation of a three-state Potts spin model by using networks of coupled parametric oscillators with phase tristability. We first show that the cubic nonlinear process of spontaneous three-photon down-conversion is accompanied by a tristability in the phase of the subharmonic signal between three states with 2π/3 phase contrast. The phase of such a parametric oscillator behaves like a three-state spin system. Next, we show that a network of dissipatively coupled three-photon down-conversion oscillators emulates the three-state planar Potts model. We discuss potential applications of the proposed system for all-optical optimization of combinatorial problems such as graph 3-COL and MAX 3-CUT.
Force estimation from 4D OCT data in a human tumor xenograft mouse model

Abstract Minimally invasive robotic surgery offer benefits such as reduced physical trauma, faster recovery and lesser pain for the patient. For these procedures, visual and haptic feedback to the surgeon is crucial when operating surgical tools without line-of-sight with a robot. External force sensors are biased by friction at the tool shaft and thereby cannot estimate forces between tool tip and tissue. As an alternative, vision-based force estimation was proposed. Here, interaction forces are directly learned from deformation observed by an external imaging system. Recently, an approach based on optical coherence tomography and deep learning has shown promising results. However, most experiments are performed on ex-vivo tissue. In this work, we demonstrate that models trained on dead tissue do not perform well in in vivo data. We performed multiple experiments on a human tumor xenograft mouse model, both on in vivo, perfused tissue and dead tissue. We compared two deep learning models in different training scenarios. Training on perfused, in vivo data improved model performance by 24% for in vivo force estimation.
The Impact of FDI on Economic Development: The Case of Georgia

Abstract From the strategic point of view, not all foreign direct investments (FDI) are always positively benefiting the host economy, i.e. not all multinational enterprises (MnEs) are promoting local host economies. Even more, not all FDIs are equally beneficial to different sectors within the same economy. The fact is that fdi can impact different sectors in various ways, and the impact is not only based on the amount of fdi itself but on MnEs’ motivations and the peculiarities of the host economy, which can differ from country to county. in other words, only fdi numbers aggregated per year are not really giving a comprehensive picture of the situation and in many cases lead to incorrect strategic decisions, as it has happened in many countries, including Georgia.
A meta-analysis of tumor necrosis factor-α-308 G>A polymorphism in gastric cancer

Abstract Background Gastric cancer (GC) is the common cause of cancer-related deaths worldwide and inflammation represents the early phases in the GC. Objective To review the tumor necrosis factor (TNF)-α-308 G>A (GG, GA, and AA) in GC by meta-analysis studies for any differences in TNF-α-308 G>A gene polymorphisms. Methods Case–control studies published from 2003 to 2017 were identified by searching PubMed, EMASE, and the Internet with the English language. The analysis published on TNF-α-308 G>A polymorphism was analyzed and a limited number of articles were included in the present study. TNF-α-308 G>A from 4,157 patients and 5,185 healthy controls was evaluated. Studies were evaluated using Cochrane Q-test and publication bias was evaluated by constructing funnel plots. Results Overall, TNF-α-308 GA genotype showed significant association [P < 0.0001, odds ratio (OR), 95% confidence interval (CI) = 0.82 (0.74–0.91)]. However, meta-analysis of TNF-α-308 genotypes (GG, GA, AA, and GA + AA) between GC patients and controls showed nonsignificant association with GC [P > 0.05, recessive model: OR = 1.38, 95% CI: 1.15–1.66; dominant model: OR = 1.23, 95% CI: 1.09–1.39; (G/A) vs. (G/G): OR = 1.15, 95% CI: 1.02–1.28; (A/A) vs. (G/G): OR = 1.44, 95% CI: 1.19–1.73]. Analysis stratified by ethnicity showed same results in Asian and Caucasian populations. Conclusions Results revealed nonsignificant association of TNF-α-308 genotypes (GG, GA, AA, and GA + AA) and GC. TNF-α-308GA genotype showed significant association whereas homozygous genotype AA did not show association with GC risk.
Effects of Synthetic Foam on the Properties of Stabilized Lateritic Bricks

Abstract Managing the production costs of construction projects is crucial especially in the aspect of material management. The use of lightweight materials reduces the dead load in structures, thus the reduction in the use of reinforcement and concrete in the foundation. To this end, this study examined the effect of synthetic foam on the properties of stabilized lateritic brick with a view to producing lightweight stabilized laterite brick for use on weak soils with low bearing capacity. Laboratory tests were conducted on the bricks produced to determine the density, compressive strength, and water absorption properties at 7, 14, 21, and 28 days. Preformed foam using synthetic foaming agent was used at 0%, 25%, 50%, 75% and 100% to replace the water in the experiment. One hundred twenty samples of stabilized foamed lateritic bricks were produced at a mixed ratio of 1:4 (cement: laterite) using a 0.6 water/cement ratio. The result showed that the bricks at all percentages of foam content meet up with the minimum requirement of compressive strength of 1.6N/mm2, 2.0N/mm2 and 3.5N/mm2 recommended by the Nigerian Building code, Nigerian Building and Road Research Institute, and the third class brick of the BS 3921:1985 respectively. The water absorption is within the limits of bricks specified in standards as 15%. The highest compressive strength was recorded at 25% foam inclusion (4.839N/mm2) on 28th day hence concluding that foaming agent stabilizes the characteristics strength of laterite bricks and also reduces its density.
Physiological Performance of a Coastal Marsh Plant Hydrocotyle vulgaris in Natural Conditions in Relation to Mineral Nutrition and Mycorrhizal Symbiosis

Abstract Fluctuating soil salinity and competition for light are the main factors affecting plant distribution and performance in coastal salt marshes. The aim of the present study was to assess plant performance by means of non-destructive instrumental methods in a highly heterogeneous natural habitat. More specifically, environmental factors affecting growth and physiological performance of a clonal plant Hydrocotyle vulgaris L. were investigated. Changes in soil salinity, soil mineral characteristics, leaf nutrient concentrations, morphological parameters, chlorophyll fluorescence, and mycorrhizal symbiosis were analysed in different experimental plots of naturally growing H. vulgaris plants. The dynamic nature of interaction between sea water flooding-affected changes in soil salinity and competition-dependent changes in light availability led to micro-environmental heterogeneity differentially affecting physiological performance and growth of H. vulgaris in natural conditions. Plant growth was mostly affected by intensity of photosynthetically active radiation in the respective plots. Increased growth rate in shaded conditions specifically pointed to shade tolerance strategy of H. vulgaris. High heterogeneity of mineral nutrients between the plots was established. However, considerable plasticity of metabolism in respect to highly variable soil concentration of mineral nutrients together with effective mineral adaptation mechanisms ensured optimal supply of material for growth. Photochemistry of photosynthesis was only marginally affected by differences in microenvironmental conditions as shown by respective changes in chlorophyll a fluorescence parameters. Mycorrhizal symbiosis was stimulated by moderately increasing soil salinity and suppressed by relatively high salinity. When the effect of soil salinity was omitted, intensity of mycorrhizal symbiosis was positively associated with intensity of photo-synthetically active radiation. In general, a relatively high stable level of photosynthetic performance across a wide range of micro-environmental conditions indicates an adequate level of physiological adaptation of H. vulgaris to conditions of a coastal salt marsh. The present data clearly reflect complex interactions between environmental factors and plastic physiological responses of H. vulgaris.
The Pauli–Jung Conjecture and Its Relatives: A Formally Augmented Outline

Abstract The dual-aspect monist conjecture launched by Pauli and Jung in the mid-20th century will be couched in somewhat formal terms to characterize it more concisely than by verbal description alone. After some background material situating the Pauli–Jung conjecture among other conceptual approaches to the mind–matter problem, the main body of this paper outlines its general framework of a basic psychophysically neutral reality with its derivative mental and physical aspects and the nature of the correlations that connect these aspects. Some related approaches are discussed to identify key similarities to and deviations from the Pauli–Jung framework that may be useful for cross-fertilization.
Improved mechanical and viscoelastic properties of CNT-composites fabricated using an innovative ultrasonic dual mixing technique

Abstract Carbon nanotube (CNT) acts as the most promising nanofiller due to its high aspect ratio and exceptional nanoscale-level properties. However, the dispersibility of CNTs in the conventional polymer matrices is a very critical issue in developing the high-strength and light-weight polymer-based nanocomposites. In this study, an attempt was made to develop cluster-free and uniform dispersion of multiwalled carbon nanotubes (MWCNTs) in the epoxy matrix using an innovative ultrasonic dual mixing technique. The effect of dispersion of MWCNTs on the mechanical and viscoelastic properties of MWCNT-epoxy nanocomposites was comprehensively studied. Our results reveal that the tensile strength and toughness of epoxy nanocomposites with 0.50 wt. % of MWCNTs improved by 21% and 46%, respectively, as compared to neat epoxy. The nanocomposite samples with the same CNT loading show maximum enhancements of 22% and 26% in the lap shear strength and storage modulus, respectively. The tensile fracture surface examination of MWCNT-epoxy nanocomposites using field emission scanning electron microscopy indicated the cluster-free and uniform dispersion of MWC-NTs in the epoxy matrix.
The Impact of Artificial Intelligence on the Right to a Fair Trial: Towards a Robot Judge?

Abstract This paper seeks to examine the potential influences AI may have on the right to a fair trial when it is used in the courtroom. Essentially, AI systems can assume two roles in the courtroom. On the one hand, “AI assistants” can support judges in their decision-making process by predicting and preparing judicial decisions; on the other hand, “robot judges” can replace human judges and decide cases autonomously in fully automated court proceedings. Both roles will be tested against the requirements of the right to a fair trial as protected by Article 6 ECHR. An important element in this test is the role that a human judge plays in legal proceedings. As the justice system is a social process, the AI assistant is preferred to a situation in which a robot judge would completely replace human judges. Based on extensive literature, various examples and case studies, this paper concludes that the use of AI assistants can better serve legitimacy and guarantee a fair trial.
IoT-PEN: An E2E Penetration Testing Framework for IoT

: The lack of inbuilt security protocols in cheap and resource-constrained Internet of Things (IoT) devices give privilege to an attacker to exploit these device’s vulnerabilities and break into the target device. Attacks like Mirai, Wannacry, Stuxnet, etc. show that a cyber-attack often comprises of a series of exploitations of victim device’s vulnerabilities. Timely detection and patching of these vulnerabilities can avoid future attacks. Penetration testing helps to identify such vulnerabilities. However, traditional penetration testing methods are not End-to-End, which fail to detect multi-hosts and multi-stages attacks. Even if an individual system is secure under some threat model, the attacker can use a kill-chain to reach the target system. In this paper, we introduced ﬁrst-of-its-kind, IoT-PEN , a Penetration Testing Framework for IoT. The framework follows a client-server architecture wherein all IoT nodes act as clients and “a system with resources” as a server. IoT-PEN is an End-to-End, scalable, ﬂexible and automatic penetration testing framework for discovering all possible ways an attacker can breach the target system using target-graphs. Finally, the paper recommends patch prioritization order by identifying critical nodes, critical paths for e ﬃ cient patching. Our analysis shows that IoT-PEN is easily scalable to large and complex IoT networks.
Core and satellite species: theory and artefacts

A widely observed pattern in Nature is a positive correlation between the local abundances of species and their regional distribution, i.e. species which occur at high abundances on any one patch are to be found on more of the patches in a region. Brown (1984) has argued, and we agree, that this pattern is not a sampling artefact. A less widely observed pattern is that the regional distributions of species are bimodally distributed in that most species are either regionally uncommon, occurring on very few patches, or ubiquitous. Hanski (1982) had the insight that the first pattern could be easily incorporated into metapopulation theory and be used to generate the second. In the first part of this communication we will reinterpret Hanski's insight and show that metapopulation theory can easily explain the correlation between local abundance and regional distribution. When we do this, however, we no longer predict a bimodal distribution of regional abundances. We then discuss a number of artefactual reasons why these distributions may sometimes appear to be bimodal. Unless these possibilities can be excluded, it is not clear that bimodality is a phenomenon requiring an ecological explanation. The starting point of the analysis is Levin's (1969) metapopulation model
Identification of Cybersecurity Specific Content Using Different Language Models

: Given the sheer amount of digital texts publicly available on the Internet, it becomes more challenging for security analysts to identify cyber threat related content. In this research, we proposed to build an autonomous sys-tem to identify cyber threat information from publicly available information sources. We examined di ﬀ erent language models to utilize as a cybersecurity-speciﬁc ﬁlter for the proposed system. Using the domain-speciﬁc training data, we trained Doc2Vec and BERT models and compared their performance. According to our evaluation, the BERT-based Natural Language Filter is able to identify and classify cybersecurity-speciﬁc natural language text with 90% accuracy.
Data Warehouses and Big Data: How to Cope With Data Quality

Before the arrival of the Big Data era, data warehouse (DW) systems were considered the best decision support systems (DSS). DW systems have always helped organizations around the world to analyse their stored data and use it in making decisive decisions. However, analyzing and mining data of poor quality can give the wrong conclusions. Several data quality (DQ) problems can appear during a data warehouse project like missing values, duplicates values, integrity constrains issues and more. As a result, organizations around the world are more aware of the importance of data quality and invest a lot of money in order to manage data quality in the DW systems. On the other hand, with the arrival of BD, new challenges have to be considered like the need for collecting the most recent data and the ability to make real-time decisions. This article provides a survey about the exiting techniques to control the quality of the stored data in the DW systems and the new solutions proposed in the literature to face the new Big Data requirements.
Mutagenesis of some conserved residues in human 5-lipoxygenase: Effects on enzyme activity

Abstract Recombinant human 5-lipoxygenase (arachidonate:oxygen 5-oxidoreductase, EC 1.13.11.34) was expressed in Escherichia coli. In incubations of E. coli supernatants with arachidonic acid, 5-hydroxy-7,9,11,14-eicosatetraenoic acid and leukotriene A4 were formed, while incubation with 8,11,14-eicosatrienoic acid gave 8-hydroxy-9,11,14-eicosatrienoic acid. Six conserved histidine residues in 5-lipoxygenase were subjected to site-directed mutagenesis. Exchanges of His-367, -372, or -551 gave mutants for which no enzyme activities were detectable. On the other hand, exchanges of His-362, -390, or -399 gave mutants that were enzymatically active, but less so than the nonmutated control. For two of these (exchanges of His-390 or -399), the activities of the mutants were dependent on the expression temperature. Thus, the histidines in the first group (His-367, -372, -551) were crucial for 5-lipoxygenase activity, possibly because of a function of these residues as metal ligands. Mutagenesis aimed at two other conserved elements in 5-lipoxygenase, Gln-558 and the C terminus, gave mutated proteins with only a small residual activity (substitution of Gln-558), or with no detectable activity (deletion of six C-terminal amino acids), indicating that these regions are important for the function of 5-lipoxygenase.