Miracle-dz/UniFAR-FTUs huggingface dataset:
Eutrophication and algal growth in the North Sea. In: Symposium Mediterranean Seas 2000

The North Sea is a shallow shelf sea with an area of 0.6 million km2, surrounded by densely populated land areas. The general water circulation is counterclockwise , and an annua1 freshwater input of 400 km3 results in characteristic coastal water masses and currents. The North Sea receives an annual input of about l million tohs of nitrogen (N) per year by 3rivers and runoff. Most of this nitrogen input is of anthropogenic origin and comes to the shallow southern part of the North Sea. The nitrate concentration of major rivers is 300-500pM in winter and the annua1 mean N concentration of the freshwater discharge to the southern North Sea is about 300 pM. When diluted 23-fold, corresponding to a salinity of 33.5 if diluted with Atlantic water, the freshwater N is approximately equal to the natural N content of the Atlantic seawater. This level of anthropogenic N loading affects about 30 % of the volume flow through the central and southern North Sea. The average NIP ratio for the annua1 inputs of N and phosphorus (P) in 1990 was 30, which is almost twice as high as the typical ratio of 16 for marine waters. This leaves a large surplus of about 400 thousand tons of N remaining when P is depleted by algal growth in the coastal water. The excess N is exported with the coastal currents and is utilized under P limitation over an extended area. The increase in nitrate-based new production due to anthropogenic eutrophication is about 30 % for the whole North Sea. The change to P limitation of large coastal water masses is perhaps the most significant ecological change due to eutrophication. This could have particular importance for the strongly stratified waters of Kattegat and inner Skagerrak. Here nutrients advected from the southern North Sea by the Jutland Current are entrained from below the pycnocline into the euphotic zone, whereas local input of nutrients comes primarily to the upper layer. Eutrophication of stratified waters may be particulary inducive of promoting growth of flagellates, including harmful and toxic species. P limitation may aggrevate this situation. Dinoflagellates are as a group characterized by slow growth, and their ecological success is assumed to reflect a compensatory high ability to survive. A relationship between P requirement and growth rate is postulated, refiecting the general proportionality between content of nucleic acids and growth rate. Based on this, a hypothesis …
Time-series momentum across borders : a study of price TSM in 21 countries

This thesis investigates if a simple technical trading signal, based on absolute price momentum, will realize higher profits across market equity portfolios from 21 different countries. By looking at if the current price (Pt) exceeds a historic price (Pt−k) it determines if an investor is long in the market portfolio or a risk-free asset, the strategy is there for ”long only”. Hypothesis testing is conducted to find the optimal look-back period and linear regression based on the the Index-model is used to evaluate the size and validity of potential excess return. The results are encouraging, a time-series momentum trading strategy will yield better risk-adjusted returns (higher Sharpe-ratio) than the market portfolio in 16 of the 21 countries tested. The results for excessive return based on the Index-model are encouraging with positive statistically significant alphas in 15 of the 16 countries where momentum also is significant. Several potential sources of the momentum anomaly and different strategies discussed in relevant literature is also included.
Anomaly Recognition from surveillance videos using 3D Convolutional Neural Networks

Anomalous activity recognition deals with identifying the patterns and events that vary from the normal stream. In a surveillance paradigm, these events range from abuse to fighting and road accidents to snatching, etc. Due to the sparse occurrence of anomalous events, anomalous activity recognition from surveillance videos is a challenging research task. The approaches reported can be generally categorized as handcrafted and deep learning-based. Most of the reported studies address binary classification i.e. anomaly detection from surveillance videos. But these reported approaches did not address other anomalous events e.g. abuse, fight, road accidents, shooting, stealing, vandalism, and robbery, etc. from surveillance videos. Therefore, this paper aims to provide an effective framework for the recognition of different real-world anomalies from videos. This study provides a simple, yet effective approach for learning spatiotemporal features using deep 3-dimensional convolutional networks (3D ConvNets) trained on the University of Central Florida (UCF) Crime video dataset. Firstly, the frame-level labels of the UCF Crime dataset are provided, and then to extract anomalous spatiotemporal features more efficiently a fine-tuned 3D ConvNets is proposed. Findings of the proposed study are twofold 1)There exist specific, detectable, and quantifiable features in UCF Crime video feed that associate with each other 2) Multiclass learning can improve generalizing competencies of the 3D ConvNets by effectively learning frame-level information of dataset and can be leveraged in terms of better results by applying spatial augmentation.
Evading Deep Learning-Based Malware Detectors via Obfuscation: A Deep Reinforcement Learning Approach

Adversarial Malware Generation (AMG), the generation of adversarial malware variants to strengthen Deep Learning (DL)-based malware detectors has emerged as a crucial tool in the development of proactive cyberdefense. However, the majority of extant works offer subtle perturbations or additions to executable files and do not explore full-file obfuscation. In this study, we show that an open-source encryption tool coupled with a Reinforcement Learning (RL) framework can successfully obfuscate malware to evade state-of-the-art malware detection engines and outperform techniques that use advanced modification methods. Our results show that the proposed method improves the evasion rate from 27%-49% compared to widely-used state-of-the-art reinforcement learning-based methods.
Generation and evolution of internal solitary waves in the southern Taiwan Strait

ABSTRACT The generation processes and potential energy sources of internal solitary waves (ISWs) in the southern Taiwan Strait are investigated by driving a high resolution non-hydrostatic numerical model with realistic background conditions. Two main types of ISWs are clarified according to their different energy sources. One is generated by the nonlinear disintegration of remote internal tides emanating from Luzon Strait, and the other type is generated by local tide-topography interaction at the continental slope. The basic properties and evolution processes differ between these two kinds of ISWs. The waves originated from the remote internal tides at Luzon Strait have amplitudes comparable to previous field observations. In contrast, the ISWs generated locally are much weaker than observed waves, even in the presence of a steady offshore background current, which intensifies the generation of onshore ISWs. The ISWs induced by remotely generated M2 internal tides are stronger than those induced by K1 internal tides, and the fraction of internal wave energy transmitted onto the shelf is not significantly influenced by the intensity of remotely generated internal tides.
Evaluating the Feasibility of a Software Prototype Supporting the Management of Multimorbid Seniors: Mixed Methods Study in General Practices

Background Longitudinal, patient-centered care represents a challenge for general practices. Decision support and reminder systems can offer targeted support. Objective The objective of this study was to follow a user-oriented, stepwise approach to develop an add-on for German electronic health record (EHR) systems, which aims to support longitudinal care management of multimorbid seniors, using a flag system displaying patient-centered information relevant for comprehensive health care management. This study evaluated the prototype’s feasibility from both a technical and users’ perspective. Methods The study was conducted with 18 general practitioners (GPs) and practice assistants (PAs) from 9 general practices using a mixed methods approach. In all practices, 1 GP and 1 PA tested the software each for 4 multimorbid seniors selected from the practice patient data. Technical feasibility was evaluated by documenting all technical problems. To evaluate the feasibility from the users’ perspective, participants’ responses during the software test were documented. In addition, they completed a self-administered questionnaire, including the validated System Usability Scale (SUS). Data were merged by transforming qualitative data into quantitative data. Analyses were performed using univariate statistics in IBM SPSS statistics. Results From a technical perspective, the new software was easy to install and worked without problems. Difficulties during the installation occurred in practices lacking a 64-bit system or a current version of Microsoft . NET. As EHRs used in German practices do not provide an interface to extract the data needed, additional software was required. Incomplete flags for some laboratory data occurred, although this function was implemented in our software as shown in previous tests. From the users’ perspective, the new add-on provided a better overview of relevant patient information, reminded more comprehensively about upcoming examinations, and better supported guideline-based care when compared with their individual practice strategies. A total of 14 out of 18 participants (78%) were interested in using the software long-term. Furthermore, 8 of 9 GPs were willing to pay 5 to 25 Euros (mean 14.75, SD 5.93) monthly for its use. The usability was rated as 75% (43%-95%). Conclusions The new EHR add-on was well accepted and achieved a good usability rating measured by the validated SUS. In perspective, the legally consolidated, standardized interface to German EHRs will facilitate the technical integration. In view of the high feasibility, we plan to study the software’s effectiveness in everyday primary care. Trial Registration German Clinical Trials Register DRKS00008777; https://www.drks. de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00008777
The Biography of a Settlement: An Analysis of Middle Iron Age Deposits and Houses at Howe, Orkney

The extensively excavated enclosed broch village at Howe, near Stromness on Mainland, Orkney, was one of the most important excavations of the latter half of the twentieth century in Scotland. The near-complete excavation of such an extensive and well-preserved settlement, with a large material assemblage, allows a detailed analysis of depositional practices. Little attempt was made in the published report to explore the spatial and contextual distributions of finds, and this article reconsiders the evidence, providing an analysis of settlement deposits during the main phase of occupation in the Middle Iron Age. The study aims to develop a broader understanding of the nature of settlement space on this highly structured and complex settlement. The analysis has demonstrated that a number of patterns are visible in the deposition of materials, and the temporality of the deposits suggest that the majority of depositional events were connected with major structural changes on the site. Transitional moments in the lifecycle of the settlement were thus marked in specific ways by the occupants. The analysis highlights the entangled nature of people, objects and constructed spaces in the Iron Age.
A modified bundle adjustment software for SPOT imagery and photography: tradeoff

A major problem for SPOT imagery is its geometric accuracy in relation to aerial photography, especially from the point of view of digital terrain models (DTM) and orthophotography. Computer simulation using a modified bundle software fosters versatility and high accuracy in terms of mirror tilt angles, distribution of ground control points (GCP), etc., and is a feasible and cost-effective analytical tool. This paper presents a tradeoff study of a modified bundle adjustment program for the simulation of SPOT geometry vis-a-vis conventional photography with regard to precision for various tilt angles, number of GCPS, various positions of control points in different patterns, etc
The Construction of lncRNA/circRNA–miRNA–mRNA Networks Reveals Functional Genes Related to Growth Traits in Schima superba

Schima superba is a precious timber and fire-resistant tree species widely distributed in southern China. Currently, there is little knowledge related to its growth traits, especially with respect to molecular breeding. The lack of relevant information has delayed the development of modern breeding. The purpose is to identify probable functional genes involved in S. superba growth through whole transcriptome sequencing. In this study, a total of 32,711 mRNAs, 525 miRNAs, 54,312 lncRNAs, and 1522 circRNAs were identified from 10 S. superba individuals containing different volumes of wood. Four possible regulators, comprising three lncRNAs, one circRNA, and eleven key miRNAs, were identified from the regulatory networks of lncRNA–miRNA–mRNA and circRNA–miRNA–mRNA to supply information on ncRNAs. Several candidate genes involved in phenylpropane and cellulose biosynthesis pathways, including Ss4CL2, SsCSL1, and SsCSL2, and transcription factors, including SsDELLA2 (SsSLR), SsDELLA3 (SsSLN), SsDELLA5 (SsGAI-like2), and SsNAM1, were identified to reveal the molecular regulatory mechanisms regulating the growth traits of S. superba. The results not merely provide candidate functional genes related to S. superba growth trait and will be useful to carry out molecular breeding, but the strategy and method also provide scientists with an effective approach to revealing mechanisms behind important economic traits in other species.
Effects of Freeze-Drying Processes on the Acoustic Absorption Performance of Sustainable Cellulose Nanocrystal Aerogels

Cellulose aerogels have great prospects for noise reduction applications due to their sustainable value and superior 3D interconnected porous structures. The drying principle is a crucial factor in the preparation process for developing high-performance aerogels, particularly with respect to achieving high acoustic absorption properties. In this study, multifunctional cellulose nanocrystal (CNC) aerogels were conveniently prepared using two distinct freeze-drying principles: refrigerator conventional freezing (RCF) and liquid nitrogen unidirectional freezing (LnUF). The results indicate that the rapid RCF process resulted in a denser CNC aerogel structure with disordered larger pores, causing a stronger compressive performance (Young’s modulus of 40 kPa). On the contrary, the LnUF process constructed ordered structures of CNC aerogels with a lower bulk density (0.03 g/cm3) and smaller apertures, resulting in better thermal stability, higher diffuse reflection across visible light, and especially increased acoustic absorption performance at low–mid frequencies (600–3000 Hz). Moreover, the dissipation mechanism of sound energy in the fabricated CNC aerogels is predicted by a designed porous media model. This work not only paves the way for optimizing the performance of aerogels through structure control, but also provides a new perspective for developing sustainable and efficient acoustic absorptive materials for a wide range of applications.
E-XAI: Evaluating Black-Box Explainable AI Frameworks for Network Intrusion Detection

The exponential growth of intrusions on networked systems inspires new research directions on developing artificial intelligence (AI) techniques for intrusion detection systems (IDS). In particular, the need to understand and explain these AI models to security analysts (managing these IDS to safeguard their networks) motivates the usage of explainable AI (XAI) methods in real-world IDS. In this work, we propose an end-to-end framework to evaluate black-box XAI methods for network IDS. We evaluate both global and local scopes for these black-box XAI methods for network intrusion detection. We analyze six different evaluation metrics for two popular black-box XAI techniques, namely SHAP and LIME. These metrics are descriptive accuracy, sparsity, stability, efficiency, robustness, and completeness. They cover main metrics from network security and AI domains. We evaluate our XAI evaluation framework using three popular network intrusion datasets and seven AI methods with different characteristics. We release our codes for the network security community to access it as a baseline XAI framework for network IDS. Our framework shows the limitations and strengths of current black-box XAI methods when applied to network IDS.
Stacking of 3D-Printed Plant-Microbial Fuel Cells with Green Chili (Capsicum Annuum)

Plant Microbial Fuel Cells are derivatives of Microbial Fuel Cells, which utilize plants' rhizodeposits to generate electricity. PMFCs present the unique capability of continuing renewable power generation in the same plot of land while continuing agricultural activities by taking advantage of the natural rhizodeposition process in plants. In this study, 3D-printed PLA electrodes were used in a PMFC set-up and was tested for its suitability with the use of LTC3108 low energy harvesting circuit. Stacking studies were done Several cells were tested for their power generation individually and stacked in combination and cumulative circuits. The results showed that the power generation of individual cells varied considerably all throughout the experiment, and the cumulative readings gave the best voltage and power density of 363.3 mV and 0.239 J.1W/m2 in the pure parallel connection of 13 cells. There was no observed drop in voltage and current when the LTC3108 circuit was connected to the PMFC instead of a regular resistor load, which is a promising step towards possible on-site energy harvesting with PMFCs.
A Rare Presentation of Laurence-Moon-Bardet-Biedl Syndrome: Atypical Retinitis Punctata Albescens and Non-alcoholic Fatty Liver Disease

This case report emphasizes the varied clinical features of Laurence-Moon-Bardet-Biedl syndrome (LMBBS) in a 10-year-old girl, presenting a rare combination of atypical retinitis punctata albescens, polydactyly, central obesity, and non-alcoholic fatty liver disease (NAFLD). Despite extensive management efforts, the patient's visual impairment remained unchanged, highlighting the challenging and progressive nature of LMBBS, particularly its ocular manifestations. Genetic counseling played a crucial role, stressing the significance of early genetic analysis in consanguineous marriages for anomaly detection and informed family planning. This case enhances our comprehension of LMBBS and emphasizes the necessity for ongoing research and multidisciplinary care to tackle its complexities.
Exploring Endogenous and Exogenous Factors for Successful Artificial Insemination in Sheep: A Global Overview

Simple Summary In this overview of the literature, we explore the complex endogenous and exogenous factors influencing the success of ovine artificial insemination (AI). From genetic dynamics and age-related fertility variations to the complexities of cervical anatomy and semen quality, we explore the nuances impacting ovine AI. Additionally, we examine the ongoing debate between natural and hormonal synchronization, semen handling, and the profound effects of environmental stressors like heat and nutritional stress. Our findings suggest that a holistic approach, considering both endogenous and exogenous factors, is crucial for optimizing AI outcomes in sheep breeding programs. This overview of the literature serves as a valuable guide for researchers, veterinarians, and sheep breeders, offering practical insights to enhance the efficiency and success of ovine AI programs and contribute to improved reproductive outcomes and genetic progress. Abstract Artificial insemination (AI) plays a vital role in animal breeding programs. AI is applied to enhance animal genetics and facilitate the widespread integration of desirable characteristics with a high potential for productivity. However, in sheep, this biotechnology is not commonly practicable due to multi-factorial challenges, resulting in inconsistent outcomes and unpredictable results. Thoughtful selection of semen donors and recipients based on genetic merit deeply impacts ovine AI outcomes. Additionally, endogenous factors such as breed, age, fertility traits, genetic disorders, and cervical anatomy in ewes contribute to ovine AI success. Extensive research has studied exogenous influences on sexual behavior, reproductive health, and hormonal regulation, all impacting ovine AI success. These exogenous factors include techniques like estrus induction, synchronization, semen handling methods (fresh/chilled/frozen), and insemination methods (cervical/laparoscopic), as well as nutritional factors and climatic conditions. This overview of the literature highlights the endogenous and exogenous challenges facing successful ovine AI and proposes strategies and best practices for improvement. This paper will serve as a guide for understanding and optimizing the success of ovine AI.
Microbial Populations in Ocean Floor Basalt: Results from ODP Leg 187

The microbial population in samples of basalt drilled from the north of the Australian Antarctic Discordance (AAD) during Ocean Drilling Program Leg 187 were studied using deoxyribonucleic acid (DNA)-based methods and culturing techniques. The results showed the presence of a microbial population characteristic for the basalt environment. DNA sequence analysis revealed that microbes grouping within the Actinobacteria, green nonsulfur bacteria, the Cytophaga/Flavobacterium/ Bacteroides (CFB) group, the Bacillus/Clostridium group, and the beta and gamma subclasses of the Proteobacteria were present in the basalt samples collected. The most dominant phylogenetic group, both in terms of the number of sequences retrieved and the intensities of the DNA bands obtained with the denaturing gradient gel electrophoresis analysis, was the gamma Proteobacteria. Enrichment cultures showed phylogenetic affiliation with the Actinobacteria, the CFB group, the Bacillus/ Clostridium group, and the alpha, beta, gamma, and epsilon subclasses of the Proteobacteria. Comparison of native and enriched samples showed that few of the microbes found in native basalt samples grew in the enrichment cultures. Only seven clusters, two clusters within each of the CFB and Bacillus/Clostridium groups and five clusters within the gamma Proteobacteria, contained sequences from both native and enriched basalt samples with significant similarity. Results from cultivation experiments showed the presence of the physiological groups of iron reducers and methane producers. The presence of the iron/manganese-reducing bacterium Shewanella was confirmed with DNA analysis. 1Lysnes, K. , Torsvik, T. , Thorseth, I.H. , and Pedersen, R.B. , 2004. Microbial populations in ocean floor basalt: results from ODP Leg 187. In Pedersen, R.B. , Christie, D.M. , and Miller, D.J. (Eds.), Proc. ODP, Sci. Results, 187, 1–27 [Online]. Available from World Wide Web: . [Cited YYYYMM-DD 2Department of Microbiology, University of Bergen, Jahnebakken 5, N-5020 Bergen, Norway. Correspondence author: Kristine.Lysnes@im.uib. no 3Department of Earth Science, University of Bergen, Allegaten 41, N5007 Bergen, Norway. Initial receipt: 23 May 2002 Acceptance: 17 July 2003 Web publication: 18 February 2004 Ms 187SR-203 K. LYSNES ET AL. 2 MICROBIAL POPULATIONS The results indicate that iron reducers and lithotrophic methanogenic Archaea are indigenous to the ocean crust basalt and that the methanogenic Archaea may be important primary producers in this basaltic environment.