Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Periphyton Assemblage and Water Quality Variables to Assess the Ecological Recovery of an Ecologically Engineered Wetland Affected by Acid Mine Drainage after a Dry Spell

The Grootspruit valley bottom wetland in South Africa, due to the impact of acid mine drainage (AMD) from an abandoned coal mine, was severely degraded before ecologically engineered interventions, as a passive treatment process, in 2014. The surface water flow of the wetland was redirected using concrete structures to enlarge the surface area of the wetland by 9.4 ha and to optimize passive treatment. Although the ecologically engineered interventions showed an improvement in water quality after the rewetting of the enlarged wetland areas, the 2016 drought had a devastating effect on the wetland’s water quality. Limited natural removal of metals and sulfate concentrations by the wetland occurred during the 2016 drought, when compared with the 2015 pre-drought conditions. This period showed higher concentrations of metals, sulfate (SO42−), and electrical conductivity (EC) associated with the acidic surface water. Of particular interest was an observation of a substantial shift in pollutant-tolerant algae species in the ecologically engineered wetland outflow between the years 2015 and 2016. During the dry spell period of 2016, the diatoms Gyrosigma rautenbachiae (Cholnoky), Craticula buderi (Brebisson), and Klebsormidium acidophilum (Noris) were observed at the outflow. The latter species were not observed during the wetland surveys of 2015, before the dry spell. From late 2017 onwards, after the drought, environmental conditions started improving. In 2018, periphyton indicator species and the surface water quality were comparable to the wetland’s recorded status pre-2016. The study revealed not only a regime shift, but also an ecological function loss during the drought period of 2016, followed by recovery after the dry spell. A distinct reduction in SO42−, sodium (Na), magnesium (Mg), EC, manganese (Mn), iron (Fe), silicon (Si), aluminum (Al), and pH, following the 2016 drought, highlights the utilization of water quality variables to not only assess the passive treatment responses of an ecologically engineered wetland, but also the progress relating to ecological recovery.
Constitutive Pathway Surface MHC Class II Molecules via a HIV-1 Nef Promotes Endocytosis of Cell

HIV-1 Nef has been reported to disrupt MHC class II (MHCII)-mediated Ag presentation by a dual strategy that comprises a reduction in cell surface levels of peptide-loaded mature MHCII molecules and a up-regulation of immature MHCII molecules. We show that Nef achieves relocation of MHCII away from the cell surface in monocytic cells by both delaying its transport to the cell surface and by accelerating endocytic removal of cell surface MHCII to a lysosomal compartment. Nef-induced MHCII endocytosis is cholesterol-sensitive but clathrin- and dynamin-independent. Internalized MHCII molecules traverse the early endosomal system and colocalize with pinocytic cargo before reaching lysosomes. Nef-triggered MHCII endocytosis requires Rab5 activity and lyst function, whereas lysosomal trafﬁcking of internalized MHCII molecules requires Rab7 activity. We further show that a similar pathway can remove peptide-MHCII complexes from the surface of monocytic cells not expressing Nef. Our data suggest that Nef uses mechanisms involved in normal MHCII recycling and turnover to mediate the delivery of cell surface MHCII to a lysosomal destination. Thus, Nef-mediated endocytosis of MHCII provides a novel perspective on the regulation of normal MHCII trafﬁcking. The Journal of Immunology, 2009, 183: 2415–2424.
Semi-Supervised Detection of Algorithmically Generated Domains using Neural Network-Based Autoencoders

Domain Generation Algorithms (DGA) are typically used by recent botnets to communicate with their command-and-control server, thus exacerbating the complexity of detecting them compared to older botnets using static IP addresses. As such, recent studies have been experimenting with different approaches to detect algorithmically generated domains using a variety of methods, including Deep Learning. This paper presents a Deep Learning approach based on autoencoders as a semi-supervised method requiring only legitimate domains for training. Semi-supervised methods have an advantage over supervised methods in that they require no labelled DGA data. The proposed autoencoder structure is based on a Neural Network (NN) processing the frequency of 2-grams in domain names. The method has been compared with supervised machine learning methods and cross-validated on a second unseen dataset to evaluate the generalization of results. Results confirmed an F-score of 73% on DGA detection outperforming a NN based on letter frequencies and a Random Forest approach based on 𝑛 -grams scoring 71% and 65% respectively.
Cross-LinkingApoptosis of Murine Thymocytes by CD24 TCR-Independent and Caspase-Independent

CD24, also referred to as the heat-stable Ag, is a T cell differentiation Ag that is highly expressed on both CD4 (cid:1) CD8 (cid:1) double negative and CD4 (cid:2) CD8 (cid:2) double positive thymocytes. Here, we report that CD24 ligation by a new anti-CD24 Ab, mT-20, induced the apoptosis of both double negative and double positive thymocytes, as well as the Scid.adh thymic lymphoma cell line, in the absence of TCR/CD3 engagement. CD24-mediated apoptosis of mouse thymocytes and its signaling pathway appeared not to be associated with p53, CD95, TNFR, or caspases. Furthermore, we found that cell death was blocked by the addition of scavengers of reactive oxygen species or by Bcl-2 overexpression, implying the role of CD24 signaling in the mitochondrial regulation. In this study, we suggest that CD24 ligation induced the apoptosis of immature thymocytes independently of both caspase and TCR. The Journal of Immunology, 2004, 172: 795–802. the anti-AIF antiserum, and they were incubated for 30 min at room temperature in a humidiﬁed chamber. Glass slides were then washed once with a 0.1% solution of saponin in PBS and were incubated in the same way with a 1/200 dilution of an anti-rabbit IgG Ab labeled with Cy-3 (Molecular Probes, Eugene, OR). Finally, glass slides were washed sequentially with 0.1% saponin, PBS, and distilled water and were mounted. Preparations were observed with a confocal mi-croscope (Radiance 2000; Bio-Rad, Hercules, CA).
Temperature Compensation of Fiber Bragg Grating Sensors in Smart Strand

Compared to other types of sensors, fiber optic sensors have improved accuracy and durability. Recently, the Smart Strand was developed to maximize the advantages of fiber optic sensors for measuring the cable forces in prestressed concrete structures or cable-supported bridges. The Smart Strand has fiber Bragg gratings (FBGs) embedded in a core wire of the seven-wire strand. Similar to other sensors, the strain measured at an FBG is affected by temperature; therefore, the temperature effect that is not related to the mechanical strain should be compensated for or corrected in the long-term measurement subjected to temperature variation. However, a temperature compensation procedure for the FBG has yet to be established, and relevant studies have used different formulas for the compensation. Moreover, when the FBG sensors are packaged with a certain material—such as fiber reinforced polymer—for protection, it is important to consider the interaction between the FBG, packaging material, and host material during thermal behavior. Therefore, this study proposed a reasonable procedure for temperature compensation for the FBG sensors embedded in packaging material and host material. In particular, the thermal sensitivity of the Smart Strand was intensively investigated. The proposed theoretical formulas were validated through comparison with data obtained from various specimens in a temperature-controlled chamber. Finally, the procedure was applied to correct the data measured using the Smart Strands in a 20-m-long full-scale specimen for about a year, thus resulting in a realistic trend of the long-term prestressing force.
Web application for facial wrinkle recognition

Facial recognition technology is named one of the main trends of recent years. It’s wide range of applications, such as access control, biometrics, video surveillance and many other interactive humanmachine systems. Facial landmarks can be described as key characteristics of the human face. Commonly found landmarks are, for example, eyes, nose or mouth corners. Analyzing these key points is useful for a variety of computer vision use cases, including biometrics, face tracking, or emotion detection. Different methods produce different facial landmarks. Some methods use only basic facial landmarks, while others bring out more detail. We use 68 facial markup, which is a common format for many datasets. Cloud computing creates all the necessary conditions for the successful implementation of even the most complex tasks. We created a web application using the Django framework, Python language, OpenCv and Dlib libraries to recognize faces in the image. The purpose of our work is to create a software system for face recognition in the photo and identify wrinkles on the face. The algorithm for determining the presence and location of various types of wrinkles and determining their geometric determination on the face is programmed.
Naive/Resting Required for IL-2 Synthesis by The Jak Family Tyrosine Kinase Jak3 Is

The Jak family tyrosine kinase, Jak3, is involved in signaling through cytokine receptors using the common g -chain. Mice deﬁcient in Jak3 have mature T cells, all of which have an activated/memory cell phenotype but are unresponsive to in vitro stimulation. Due to this activated phenotype, it has been impossible to determine whether Jak3 plays a role in the responsiveness of naive/ resting T cells. To circumvent this difﬁculty, we generated naive/resting Jak3-negative T cells by two genetic approaches. After stimulation, these cells failed to produce signiﬁcant amounts of IL-2. Although no signaling defect could be detected, we did ﬁnd that naive/resting Jak3-negative T cells have substantially reduced levels of the transcription factor NF-AT1 and moderately reduced levels of c-Jun and c-Fos. On the basis of these data, we propose that Jak3-dependent cytokine signals may be required to maintain the normal levels of basal transcription factors required for immediate responsiveness to Ag activation. The Journal of Immunology, 1999, 163: 5411–5417. It fulﬁlls
Application of Convolution Neural Networks of the DeepLabv3 Architecture for Preprocessing of Magnetic Resonance Imaging for the Differential Diagnosis of Parkinson’s Disease and Essential Tremors

Preprocessing of data for implementing an artificial intelligence system solving the problem of differential diagnosis of Parkinson’s disease and essential tremor based on the data of nuclear magnetic resonance imaging is discussed. A database of 500 images of magnetic resonance imaging and positron emission tomography of patients with Parkinson’s disease, essential tremor, and unclear diagnoses is used. For preprocessing a neural network of the DeepLab v3 + architecture was used. The accuracy of preprocessing “raw” images reached 87 %. Furthermore, the proposed solution adequately highlights the area corresponding to the brain tissue on the magnetic resonance tomography. Therefore, the solution provides a feasible mechanism to prepare data for a neural network implemented for the differential diagnosis of Parkinson’s disease and essential tremor.
Perpetrate Cyber-threats using IoT Devices as Attack Vector: The ESP8266 Use Case

Security of the Internet of Things is a crucial topic, due to the criticality of the networks and the sensitivity of exchanged data. In this paper, we evaluate the adoption of IoT devices to execute cyber-threats by using a specific Wi-Fi module called ESP8266. This module may implement custom user applications, but it could also be adopted for malicious purposes, as to perpetrate cyber-attacks. In particular, we implemented a social engineering attack to steal sensitive information and a slow denial of service attack to saturate the resources of a web service based on an Apache2 server. Obtained results report that the ESP8266 module is able to perform both attacks successfully. Hence, we demonstrate that even a simple and cheap module is able to execute critical cyber-attacks.
Modeling the impact on cost and schedule of software quality engineering practices

Achieving high software quality, in particular high reliability, is vital for the competitiveness in today's world. The problem investigated by this research is how to design the process for developing software with given quality requirements, in order to achieve product requirements while maintaining the balance between software quality, project cost, and delivery time. The solution proposed here is to develop a framework for customizing a project by selecting software reliability engineering practices for achieving specified software reliability requirements, and modeling the resulting process in order to assess, by simulation, the impact of these practices on project cost, schedule and software quality throughout the development life cycle. The framework is implemented by a decision support system (DSS) for software reliability engineering strategy selection and assessment. This dissertation describes the framework, presents the methodology used for developing it, as well as framework implementation and the results of using the fuzzy expert system for strategy selection and the system dynamics process simulator for practices effect evaluation.
Histologic and Genotypic Characterization of Lung Cancer in the Inuit Population of the Eastern Canadian Arctic

Inuit are the Indigenous Arctic peoples and residents of the Canadian territory of Nunavut who have the highest global rate of lung cancer. Given lung cancer’s mortality, histological and genomic characterization was undertaken to better understand the disease biology. We retrospectively studied all Inuit cases from Nunavut’s Qikiqtani (Baffin) region, referred to the Ottawa Hospital Cancer Center between 2001 and 2011. Demographics were compiled from medical records and tumor samples underwent pathologic/histologic confirmation. Tumors were analyzed by next generation sequencing (NGS) with a cancer hotspot mutation panel. Of 98 patients, the median age was 66 years and 61% were male. Tobacco use was reported in 87%, and 69% had a history of lung disease (tuberculosis or other). Histological types were: non-small cell lung carcinoma (NSCLC), 81%; small cell lung carcinoma, 16%. Squamous cell carcinoma (SCC) represented 65% of NSCLC. NGS on 55 samples demonstrated mutation rates similar to public lung cancer datasets. In SCC, the STK11 F354L mutation was observed at higher frequency than previously reported. This is the first study to characterize the histologic/genomic profiles of lung cancer in this population. A high incidence of SCC, and an elevated rate of STK11 mutations distinguishes this group from the North American population.
Photonics and Optical Communication Research at the Hong Kong Polytechnic University

The Photonics Research Centre of the Hong Kong Polytechnic University is a multidisciplinary research centre with members from the Electrical, Electronic and Information Engineering, Industrial and Systems Engineering and Mechanical Engineering Departments. The main objective of the group is to form the basis of collaborations among the members of the Group. The broad background of the members in the centre has led to synergism in a broad range of topics including fibre communication systems, fibre sensors, GaN-based detectors and light emitters and application of laser technology in GaNbased optoelectronic and electronic devices. In some cases we have already found useful applications of our work relevant to the need of Hong Kong. In the sections below we will introduce the three major areas of research in the field of photonics at The Hong Kong Polytechnic University.
Correlations of multiplicative functions with automorphic L-functions

Let $\lambda_{\phi}(n)$ be the Fourier coefficients of a Hecke holomorphic or Hecke--Maass cusp form on ${\rm SL}_2(\mathbb Z)$, and $f$ be any multiplicative function that satisfies two mild hypotheses. We establish a non-trivial upper bound for the correlation $\sum_{n \leq X}f(n)\lambda_{\phi}(n+h)$ uniformly in $0<|h|\ll X$. As applications, we consider some special cases, including $\lambda_{\pi}(n), \,\mu(n)\lambda_{\pi}(n)$ and any divisor-bounded multiplicative function. Here $\lambda_{\pi}(n)$ denotes the $n$-th Dirichlet coefficient of $\text{GL}_m$ automorphic $L$-function $L(s,\pi)$ for an automorphic irreducible cuspidal representation $\pi$, and $\mu(n)$ denotes the M\"obius function. In particular, some savings are achieved for shifted convolution problems on ${\rm GL}_m\times {\rm GL}_2\, (m\geq 4)$ and Hypothesis C for the first time.
Tritium as a Tracer of Leachate Contamination in Groundwater: A Brief Review of Tritium Anomalies Method

Environmental isotopes are essential in hydrogeological studies, thanks to their contribution to the understanding of aquifers dynamics, vulnerability, water resources assessment, and management issues. The environmental isotopic approach plays a vital role in tracing the hydrological cycle and identifying various sources of contamination in the environment and gives independent information concerning what can be determined by a traditional hydrogeological study. Even in the framework of COP-26, isotopes have been indicated as fingerprints of climate change and therefore suitable for the evaluation of water balance and assessment of processes involved therein; in pollution studies they are used as fundamental support of traditional geochemical measures. Tritium, in particular, has been used since the 1960s to identify potential leaks in the containment walls of waste disposal sites, since its presence in the leachate (at very high levels in some cases) depends on the incorrect waste disposal of some peculiar items. Its use as a tracer of pollution by landfills is highlighted and emphasized by the very low concentrations of tritium in the natural environment. By comparing tritium content of leachate to that of water downflow from the waste disposal site, it is therefore possible to establish with a good success rate whether leachate have migrated or not out of the landfill, in the surrounding environment. An additional potential of tritium is to give a prompt indication of pollution risk in the environment indicating leaching even before the chemical indicator of pollution can be detected. This article wants to provide a contribution to the scientific community, collecting all the existing research in this field and providing data and benchmarks about this method, in particular stressing the role of tritium as an indicator of leachate transfer out of waste disposal sites.
Modal pushover analysis for seismic vulnerability analysis

A simple introduction of inelastic structural analysis for seismic vulnerability by considering the definition of pushover analysis and using a simple elasto-plastic material model to compare analytical and numerical results. The modal pushover method is explained to approximate the response due to ”El Centro 1940” ground motion for MDOF systems. The properties of Modal Pushover analysis is used to plot capacity curves vs ground motion spectra in order to perform a one limit state fragility curve using the maximum likelihood method. All explanation are done by following a step by step procedure, then it is applied to a benchmark structure, the 9 storey SAC building.
Preparation of ZnO-TiO2-FeMnO3 adsorbent composite

Using FeMnO3 as the main filling material, it is compounded with tetrabutyl titanate and zinc acetate to form corresponding ferromanganese complexes, so as to prepare magnetic semiconductors and catalysts with better performance. Nano FeMnO3 was prepared by sol-gel method. Microwave assisted method was used to compounded FeMnO3 with four butyl titanate and zinc acetate solution to form sol. Then, drying and calcining were carried out to obtain the change of TiO2-FeMnO3 and ZnO-FeMnO3 properties at high temperature.
Ultrasound Localization Microscopy in Liquid Metal Flows

Liquid metal convection plays an important role in natural and technical processes. In experimental studies, an instrumentation with a sub-millimeter spatial resolution is required in an opaque fluid to resolve the flow field near the boundary layer. Using ultrasound methods, the trade-off between the frequency and imaging depth of typical laboratory experiments limits the spatial resolution. Therefore, the method of ultrasound localization microscopy (ULM) was introduced in liquid metal experiments for the first time in this study. To isolate the intrinsic scattering particles, an adaptive nonlinear beamformer was applied. As a result, an average spatial resolution of 188 μm could be achieved, which corresponded to a fraction of the ultrasound wavelength of 0.28. A convection experiment was measured using ULM. Due to the increased spatial resolution, the high-velocity gradients and the recirculation areas of a liquid metal convection experiment could be observed for the first time. The presented technique paves the way for in-depth flow studies of convective turbulent liquid metal flows that are close to the boundary layer.
Hierarchy Descending SFC Provisioning Scheme With Load Balancing in Fog Computing

This letter presents a novel provisioning scheme for service function chain (SFC) requests for delay-sensitive applications. The SFC is comprised of virtual network functions (VNF) to be mapped on a multi-tier fog architecture composed of primary and secondary nodes with limited resources. Now existing provisioning methods establish service paths based on least delay or load, and then map single VNFs on each fog node. However, these approaches can yield early congestion at the primary nodes, thus leaving secondary nodes unoccupied due longer link delays. To solve this problem, the proposed scheme leverages a descending hierarchical approach to enhance admission and utilization rates and reduce provisioning delays. At low traffic volumes, it performs grouped VNF mapping on secondary nodes through shorter paths that skip underloaded primary nodes. At high traffic volumes, it performs single mapping on primary nodes over established paths.
Establishment of Integrated Analysis Method for Probing and Reconstructing Hydrogenation Mechanism of a Model Reaction

The hydrogenation of 4-nitrophenol (4-NP) has attracted much attention, since it is typically used as a model reaction for evaluating newly developed catalysts, but its mechanism is still debated. Herein, Co(OH)2-modified CuO catalyst (Co(OH)2/CuO) was used for the reduction of 4-NP to 4-aminophenol (4-AP) in an aqueous sodium borohydride (NaBH4) solution. The reaction mechanism was investigated by UV-Vis spectroscopy (UV-Vis), high-performance liquid chromatography (HPLC), HPLC-Q-orbitrap high-resolution mass spectrometry (LC-MS/MS), and 1HNMR spectroscopy (1HNMR) as an integrated technology at different concentrations of NaBH4. Samples were taken at specified time intervals and monitored using UV-Vis, HPLC, LC-MS/MS, and 1HNMR. With the help of comprehensive analysis, eight intermediates, including azo and azoxy compounds, were effectively captured, and the variation tendency of each intermediate was determined, revealing that the hydrogenation of 4-NP proceeds via a coexistence of the direct and condensation routes. The integrated analysis methods were powerful technical supports for the study of the catalysis mechanism.