Miracle-dz/UniFAR-FTUs huggingface dataset:
LiDAR from drones employed for mapping archaeology – Potential, benefits and challenges

Although the use of both drones and LiDAR (light detection and ranging) has become common in archaeology in recent years, LiDAR scanning from drones is still in its infancy. The technological development related to drones as well as laser scanner instruments has gradually reached the point where these can be integrated. In this paper we present the results from a test where the applicability of LiDAR used from a drone was studied. The study had two objectives – both based on comparative studies: (i) whether LiDAR from drones represents an improvement in terms of detection success; and (ii) whether LiDAR from drones can increase the quality of the documentation of archaeological features and their physical properties based on remote sensing. A modest improvement of detection success was found, but was not as convincing as one would perhaps expect given the relatively large increase in terms of ground points. This has led us to the conclusion that very dense vegetation obstructs laser beams from reaching all the way to the bare earth. As regards accuracy in documenting archaeological features, the study showed more significant improvements. The last part of the paper is dedicated to a discussion of the pros and cons of using LiDAR from drones compared to conventional airborne laser scanning from aeroplanes or helicopters. The main advantages concern flexibility, low flight altitude and small laser footprint as well as the advantages of a far‐reaching field of view. The disadvantages are related to price, battery capacity, size of area and especially the requirement of line of sight between the drone operator and the drone, a fact that restricts the efficiency in terms of mapping large areas. Nevertheless, the final conclusion is that LiDAR from drones has the potential to make a substantial improvement to archaeological remote sensing.
Evidence for an epigenetic role in inbreeding depression

Inbreeding depression (i.e. negative fitness effects of inbreeding) is central in evolutionary biology, affecting numerous aspects of population dynamics and demography, such as the evolution of mating systems, dispersal behaviour and the genetics of quantitative traits. Inbreeding depression is commonly observed in animals and plants. Here, we demonstrate that, in addition to genetic processes, epigenetic processes may play an important role in causing inbreeding effects. We compared epigenetic markers of outbred and inbred offspring of the perennial plant Scabiosa columbaria and found that inbreeding increases DNA methylation. Moreover, we found that inbreeding depression disappears when epigenetic variation is modified by treatment with a demethylation agent, linking inbreeding depression firmly to epigenetic variation. Our results suggest an as yet unknown mechanism for inbreeding effects and demonstrate the importance of evaluating the role of epigenetic processes in inbreeding depression.
CXC Chemokine Receptor 7 (CXCR7) Regulates CXCR4 Protein Expression and Capillary Tuft Development in Mouse Kidney

Background The CXCL12/CXCR4 axis is involved in kidney development by regulating formation of the glomerular tuft. Recently, a second CXCL12 receptor was identified and designated CXCR7. Although it is established that CXCR7 regulates heart and brain development in conjunction with CXCL12 and CXCR4, little is known about the influence of CXCR7 on CXCL12 dependent kidney development. Methodology/Principal Findings We provided analysis of CXCR7 expression and function in the developing mouse kidney. Using in situ hybridization, we identified CXCR7 mRNA in epithelial cells including podocytes at all nephron stages up to the mature glomerulus. CXCL12 mRNA showed a striking overlap with CXCR7 mRNA in epithelial structures. In addition, CXCL12 was detected in stromal cells and the glomerular tuft. Expression of CXCR4 was complementary to that of CXCR7 as it occurred in mesenchymal cells, outgrowing ureteric buds and glomerular endothelial cells but not in podocytes. Kidney examination in CXCR7 null mice revealed ballooning of glomerular capillaries as described earlier for CXCR4 null mice. Moreover, we detected a severe reduction of CXCR4 protein but not CXCR4 mRNA within the glomerular tuft and in the condensed mesenchyme. Malformation of the glomerular tuft in CXCR7 null mice was associated with mesangial cell clumping. Conclusions/Significance We established that there is a similar glomerular pathology in CXCR7 and CXCR4 null embryos. Based on the phenotype and the anatomical organization of the CXCL12/CXCR4/CXCR7 system in the forming glomerulus, we propose that CXCR7 fine-tunes CXCL12/CXCR4 mediated signalling between podocytes and glomerular capillaries.
Design and experimentation of fuzzy logic control for an anti-lock braking system

A multi-input, single-output fuzzy logic controller for anti-lock braking system is proposed, where both the slip and the vehicle velocity are considered as the inputs and are regulated equally influencing on the controller decision. The system developed provides both the minimal slip ratio to avoid the wheel blockage and the shortest braking distance of the vehicle thus mitigating the collision with other traffic objects. The comparison of several rule-base blocks are studied aiming to offer the recommendations regarding their use. The experimental results prove the applicability of the proposed adaptive to different speed control previously designed by the authors for other applications.
Two-Photon Luminescence and Second Harmonic Generation from Gold Micro-Plates

Micron-sized gold plates were prepared by reducing chloroauric acid with lemongrass extract. Their two-photon luminescence (TPL) and second harmonic generation (SHG) were investigated. The results show that the TPL and SHG intensity of gold plates is dependent on the wavelength and polarization of excitation laser. The TPL intensity of gold plates decreases with the increase of the excitation wavelength except for a small peak around 820–840 nm, while SHG intensity increases with the excitation wavelength redshift. In addition, it is found that the TPL intensity of the gold plate’s edge is related with the angle between the edge orientation and the polarization direction of the excitation light. The TPL intensity increases with the angle increase from 0° to 90°.
Casting Off

Growth in tourism during the past 20 years means more people are using physical spaces away from home for vacation. Yet research on vacation spaces is noticeably absent. Focusing on a cruise ship, the primary purpose of this article is to draw attention to how social interaction in a group vacation context intersects with vacation experiences. A secondary purpose is to introduce space and how it can extend thinking about the role that tourism spaces play in the development of social interaction. The results indicate that individuals use cruise ships to feel at ease and comfortable with themselves, as well as in control and liberated. They also develop social interactions during a cruise and make “playful” spaces on the cruise ship. Using these themes, the authors highlight limitations in current conceptualizations of tourism behavior. The authors also suggest how cruise lines might use the study to create more meaningful passenger experiences.
Exploring Social Networks with Topical Analysis

As the number of social networking services (SNS) and their users grow, so does the complexity of individual networks as well as the amount of information to be consumed by the users. It is inevitable to reduce the complexity and information overload, and we have embarked exploring topical aspects of SNS to form refined topic-based semantic social networks. Our current work focuses on conversational aspects of SNS and attempt to utilize the notions of topic diversity and topic purity between two users sharing conversations. This topic-based analysis of SNS makes it possible to show different types of users and their conversational characteristics. It also shows the possibility of breaking down a huge “syntactic” social network into topic-based ones based on different interaction types, so that the resulting semantic social networks can be useful in designing various targeted services on online social networks.
Human actions recognition from streamed Motion Capture

This paper introduces a new method for streamed action recognition using Motion Capture (MoCap) data. First, the histograms of action poses, extracted from MoCap data, are computed according to Hausdorf distance. Then, using a dynamic programming algorithm and an incremental histogram computation, our proposed solution recognizes actions in real time from streams of poses. The comparison of histograms for recognition was achieved using Bhattacharyya distance. Furthermore, the learning phase has remained very efficient with respect to both time and complexity. We have shown the effectiveness of our solution by testing it on large datasets, obtained from animation databases. In particular, we were able to achieve excellent recognition rates that have outperformed the existing methods.
Surveillance detection in high bandwidth environments

In this paper, we describe System Detection's surveillance detection techniques for enclave environments (ESD) and peering center environments (PSD) and evaluate each technique over data gathered from two different network environments. ESD is evaluated over 74 hours of tcpdump packet traces (344 million packets) from a large enclave; PSD is evaluated over 5 hours of tcpdump packet traces (110 million packets) gathered from a peering center. Both surveillance detection modules were executed over the audit data offline to generate surveillance detection alerts, though the systems can be run in real-time as well. Our results show that both ESD and PSD accurately discover great quantities of surveillance activities (including long-lived and distributed scans) and can be tuned to reduce the volume of alerts. Furthermore, existing IDS technology may be blind to many activities discovered by ESD and PSD.
A Test of the Snowball Theory for the Rate of Evolution of Hybrid Incompatibilities

Rolling Snowballs The genetic incompatibilities that separate ongoing speciation events have been hypothesized by the Dobzhansky-Muller model of speciation to snowball—that is, accumulate mutations causing postzygotic isolation at a faster rate than the linear accumulation of mutations. This occurs because of potential deleterious epistatic interactions in hybrids involving two or more interacting genes. Testing QTLs (quantitative trait loci) in seed and pollen sterility between multiple species pairs in the plant group Solanum, Moyle and Nakazato (p. 1521) show that hybrid female (seed) sterility accumulates exponentially between increasingly distant species pairs, although not for hybrid male (pollen) sterility. In contrast, loci contributing to differences in other traits show no evidence for nonlinear accumulation over time. Matute et al. (p. 1518) come to similar conclusions through the use of deletion mapping in comparisons between two pairs of species of Drosophila. The number of genes causing postzygotic isolation grows as fast as the square of the number of substitutions between two species. Thus, a hybrid snowball effect is found in both plants and animals. Two studies support the theory that the number of genes involved in hybrid incompatibility increases faster than linearly. Hybrids between species are often sterile or inviable because the long-diverged genomes of their parents cause developmental problems when they come together in a single individual. According to the Dobzhansky-Muller (DM) model, the number of genes involved in these “intrinsic postzygotic incompatibilities” should increase faster than linearly with the divergence time between species. This straightforward prediction of the DM model has remained contentious owing to a lack of explicit tests. Examining two pairs of Drosophila species, we show that the number of genes involved in postzygotic isolation increases at least as fast as the square of the number of substitutions (an index of divergence time) between species. This observation verifies a key prediction of the DM model.
Net generation distance learners and patterns of their digital technology use

This paper reports on the results of a two-year study carried out in five different universities in the UK on different facets of learner experiences of digital technology use. Two self-completion surveys were administered- one in the beginning and another one towards the end of the academic year. The results showed that distance learners aged 25 years of age and younger were a distinct demographic group, in so far as they displayed some characteristics and behaviours typical of students of the same age group, but studying in a place-based university, while in terms of other characteristics they were more akin to older distance learners. The differences between distance learners of different age groups were fewer towards the end of the year, which stresses the impact of university experience in analyzing student learning. Limitations of the study and its implications are considered in the light of their likely significance for research and practice in the field. © 2011 IADIS.
Theoretical Studies of DNA Microarray Present Potential Molecular and Cellular Interconnectivity of Signaling Pathways in Immune System Dysregulation

Autoimmunity is defined as the inability to regulate immunological activities in the body, especially in response to external triggers, leading to the attack of the tissues and organs of the host. Outcomes include the onset of autoimmune diseases whose effects are primarily due to dysregulated immune responses. In past years, there have been cases that show an increased susceptibility to other autoimmune disorders in patients who are already experiencing the same type of disease. Research in this field has started analyzing the potential molecular and cellular causes of this interconnectedness, bearing in mind the possibility of advancing drugs and therapies for the treatment of autoimmunity. With that, this study aimed to determine the correlation of four autoimmune diseases, which are type 1 diabetes (T1D), psoriasis (PSR), systemic sclerosis (SSc), and systemic lupus erythematosus (SLE), by identifying highly preserved co-expressed genes among datasets using WGCNA. Functional annotation was then employed to characterize these sets of genes based on their systemic relationship as a whole to elucidate the biological processes, cellular components, and molecular functions of the pathways they are involved in. Lastly, drug repurposing analysis was performed to screen candidate drugs for repositioning that could regulate the abnormal expression of genes among the diseases. A total of thirteen modules were obtained from the analysis, the majority of which were associated with transcriptional, post-transcriptional, and post-translational modification processes. Also, the evaluation based on KEGG suggested the possible role of TH17 differentiation in the simultaneous onset of the four diseases. Furthermore, clomiphene was the top drug candidate for regulating overexpressed hub genes; meanwhile, prilocaine was the top drug for regulating under-expressed hub genes. This study was geared towards utilizing transcriptomics approaches for the assessment of microarray data, which is different from the use of traditional genomic analyses. Such a research design for investigating correlations among autoimmune diseases may be the first of its kind.
Arc Regulates Experience-Dependent Persistent Firing Patterns in Frontal Cortex

The brain encodes information about past experience in specific populations of neurons that communicate with one another by firing action potentials. Studies of experience-dependent neural plasticity have largely focused on individual synaptic changes in response to neuronal input. Indicative of the neuronal output transmitted to downstream neurons, persistent firing patterns are affected by prior experience in selective neuronal populations. However, little is known about the molecular and cellular mechanisms by which experience-related persistent firing patterns are regulated in specific neuronal populations. Using frontal cortical slices prepared from transgenic mice carrying a fluorescent reporter of Arc gene expression, this study investigates how behavioral experience and the activity-regulated Arc gene affect patterns of neuronal firing. We found that motor training increases Arc expression in subsets of excitatory neurons. Those neurons exhibit persistent firing in contrast to Arc-negative neurons from the same mice or neurons from the untrained mice. Furthermore, in mice carrying genetic deletion of Arc, the frontal cortical circuitry is still in place to initiate experience-dependent gene expression, but the level of persistent firing thereafter is diminished. Finally, our results showed that the emergence of persistent activity is associated with Arc-dependent changes in the function of NMDA-type glutamate receptors, rather than changes in AMPA-type receptors or membrane excitability. Our findings therefore reveal an Arc-dependent molecular pathway by which gene–experience interaction regulates the emergence of persistent firing patterns in specific neuronal populations.
An Intrusion Detection and Prevention System based on Automatic Learning of Traffic Anomalies

The ever changing network traffic reveals new attack types, which represent a security threat that poses a serious risk for enterprise resources. Therefore, the security administrators are in a real need to employ efficient Intrusion Detection and Prevention Systems, IDPS. Such systems might be capable to learn from the network behavior. In this paper, we present an incremental Learnable Model for Anomaly Detection and Prevention of Zero-day attacks, LMAD/PZ. To facilitate the ability of learning from observations that can provide a reliable model for automatic prevention, a comparison has been carried out between supervised and unsupervised learning techniques. Thus, in LMAD/PZ, the intrusion detection step is integrated with an intrusion prevention plan. To ensure that the prevention plan is dependable and automatic, it must be backed and sustained with robust and accurate detection process. Therefore, two incremental data mining techniques are deeply investigated and implemented on NSL-KDD’99 intrusion dataset. The first technique is the Algorithm Quasi-optimal (AQ), which is a supervised Attributional Rules Learner, ARL, while the second is the Cobweb; an unsupervised hierarchical conceptual clustering algorithm. These algorithms categorize the network connections as either normal or anomalous. The performance of AQ is compared to Cobweb, and the best performance result is integrated with the prevention plan, to afford a fully automated system. The experimental results showed that, the model automatically adapts its knowledge base from continuous network streams, in addition to offering the advantage of detecting novel and zero day attacks. Many experiments have verified that AQ performance outperforms the Cobweb clustering, in terms of accuracy, detection rate and false alarm rate.
Noise robust speech dereverberation with Kalman smoother

A speech dereverberation method is proposed that is robust against background noise. In contrast to conventional methods based on the linear prediction of the given microphone input signal, in which the linear prediction coefficients are not fully optimized when there is background noise, the proposed method optimizes the coefficients by linear prediction of the noiseless reverberant speech signal even when there is background noise. The noiseless reverberant speech signal and the parameters are iteratively updated on the basis of the expectation maximization algorithm. In the expectation step, sufficient statistics of latent variables which include noiseless reverberant speech signal are estimated using the Kalman smoother. Unlike the standard Kalman smoother, which uses a time-invariant covariance matrix as a state-transition covariance matrix, the proposed method utilizes a time-varying covariance matrix, enabling it to meet the time-varying speech characteristics. The parameters are updated so that the Q function is increased in the maximization step. Experimental results show that the proposed method is superior to conventional methods under noisy conditions.
Technology Adoption as a Factor for Financial Performance in the Banking Sector Using UTAUT Model

This study investigated the complex relationship between technology adoption and the overall performance of selected Zambian banks. The analysis focuses on four prominent banks in Lusaka, namely Zanaco, Atlasmara, Stanbic, and FNB, which were selected based on characteristics such as footprint and income. The time frame is from 2015 to 2020, allowing for a complete examination of trends in the ever-changing banking business. The study used a mixed-methods approach, combining quantitative financial data analysis with qualitative analysis. Data was gathered through the examination of financial reports, industry databases, interviews with banking specialists, and surveys. For the quantitative and qualitative data, statistical analysis and theme coding were used, respectively. The study aimed to provide significant insights to academia, the banking sector, and industry stakeholders by providing a comprehensive understanding of how technology adoption impacts the performance landscape of banks in Zambia. The findings revealed a positive correlation between technology adoption and financial performance with a Pearson’s two-tailed coefficient of 0.6. The study also investigated perceptions around IT platform stability and total bank efficiency, demonstrating a strong belief in the performance-enhancing potential of a reliable IT infrastructure.
Transferrin receptor polarity and recycling accuracy in "tight" and "leaky" strains of Madin-Darby canine kidney cells

We have characterized the polarity of the transferrin receptor in the epithelial Madin-Darby canine kidney (MDCK) cell line. The receptor is present in approximately 165,000 copies per cell, migrates as a diffuse band upon SDS gel electrophoresis with Mr 90,000, displays a dissociation constant for diferritransferrin at neutral pH of approximately 2 nM, and is active in essentially all of the cells of the population. Transferrin-mediated 55Fe uptake was used to measure the polarity of active transferrin receptors in filter-grown MDCK cells. The ratio of basolateral to apical receptors was approximately 800:1 for the high resistance strain I MDCK cells (typically greater than 2,000 ohm X cm2) and approximately 300:1 for the lower resistance strain II cells (less than 350 ohm X cm2). In combination with morphometric data this shows that a difference in resistance between these two strains is not reflected in a significant difference in cell surface polarity. We used the recycling of transferrin receptor in filter-grown MDCK cells to evaluate the accuracy of the sorting of a basolateral protein during endocytosis. Monitoring the amount of apically released 125I-labeled transferrin after application of 55Fe- and 125I-labeled transferrin to the basolateral surface provided a sensitive assay of the accuracy of sorting during recycling of the receptor from endosomes to the plasma membrane. The accuracy of transferrin receptor sorting (greater than 99.88%) during a single cycle of transit between the endosome and the plasma membrane is sufficient to maintain the high level of polarity of the cell.