Miracle-dz/UniFAR-FTUs huggingface dataset:
DDoS attack detection model based on CNN-LSTM

DDoS attacks exhaust computer resources, such as computational power and network connectivity, leading to resource depletion and hindering the service availability for legitimate users or providing degraded services. In this paper, we propose a machine learning model that combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) for effective DDoS attack detection. We validate the performance of our model on the CIC-IDS2017 dataset, achieving accuracies of 99.67% and 99.55% on the training and testing sets, respectively. In addition, we also computed metrics such as Recall, False Discovery Rate (FDR), False Negative Rate (FNR), F1-Score, etc., which all serve as indicators reflecting the high effectiveness of our model.
Transcriptome Changes and Metabolic Outcomes After Bariatric Surgery in Adults With Obesity and Type 2 Diabetes

Abstract Context Bariatric surgery has been shown to be effective in inducing complete remission of type 2 diabetes in adults with obesity. However, its efficacy in achieving complete diabetes remission remains variable and difficult to predict before surgery. Objective We aimed to characterize bariatric surgery-induced transcriptome changes associated with diabetes remission and the predictive role of the baseline transcriptome. Methods We performed a whole-genome microarray in peripheral mononuclear cells at baseline (before surgery) and 2 and 12 months after bariatric surgery in a prospective cohort of 26 adults with obesity and type 2 diabetes. We applied machine learning to the baseline transcriptome to identify genes that predict metabolic outcomes. We validated the microarray expression profile using a real-time polymerase chain reaction. Results Sixteen patients entered diabetes remission at 12 months and 10 did not. The gene-expression analysis showed similarities and differences between responders and nonresponders. The difference included the expression of critical genes (SKT4, SIRT1, and TNF superfamily), metabolic and signaling pathways (Hippo, Sirtuin, ARE-mediated messenger RNA degradation, MSP-RON, and Huntington), and predicted biological functions (β-cell growth and proliferation, insulin and glucose metabolism, energy balance, inflammation, and neurodegeneration). Modeling the baseline transcriptome identified 10 genes that could hypothetically predict the metabolic outcome before bariatric surgery. Conclusion The changes in the transcriptome after bariatric surgery distinguish patients in whom diabetes enters complete remission from those who do not. The baseline transcriptome can contribute to the prediction of bariatric surgery-induced diabetes remission preoperatively.
Toward Emotional Machine-Awareness: An A.I. Based Model for Artificial Aesthetic Perception

To make cohabit humans and robots in the same living space, robots have not only develop rational awareness but also acquire emotional awareness regarding their surrounding environment proffering them autonomy alike to the human's self-sufficiency. We are investigating Emotional Machine-Awareness (EMA) tending to provide response-elements to the following question: “likewise to human's emotional awareness, could the machine acquire Artificial Aesthetic Perception (AAP) proffering it kind of emotional esteem of its environment? ” In other words, could the Machine become aware of the cuteness? In this paper we present a computational model of AAP, founded on art-philosophy's and psychology's basements. Such an approach allows, on the one hand, to develop a model based on human being's intellectual and visual mechanisms, and on the other hand, makes the investigated model comprehensive (interpretable) with regard to the subjectivity inherent in the notion of “beauty”. By utilizing two experimental datasets (Wiki-Art and a custom human eye-fixation dataset annotated with emotions), the paper presents experimental results that demonstrate the relevance of the investigated model.
Distributed-Circuit Method for Replication of Fast-Ramping of Saddle-Shaped REBCO Dipole Magnet Wound With Two-Tape Bundled Conductor

This work presents a distributed-circuit model for analyzing experimental results of fast-ramping behaviors of a saddle-shaped REBCO dipole magnet wound with a bundled conductor. Terminal voltage and center magnetic field were measured during the test performed at 77 K temperature. Our distributed-circuit model accurately reproduced the observed electromagnetic behaviors, demonstrating its validity for the fast-ramping operation of an HTS magnet. We also analyzed the current discrepancy between bundled conductors and Joule dissipation due to the various ranges of contact resistivity.
Molecular Identification and Characterization of Five Ganoderma Species from the Lower Volta River Basin of Ghana Based on Nuclear Ribosomal DNA (nrDNA) Sequences

Ganoderma is a genus of biomedical fungus that is used in the development of numerous health products throughout the world. The Lower Volta River Basin of Ghana is an undulating land surface covered by extensive vegetation and water bodies and is rich in polypore mushrooms resembling various members of the Ganoderma genus. Despite the extensive biopharmaceutical benefits of Ganoderma spp. , the isolates from the Lower Volta River Basin have not been properly characterized, thus limiting their use in the development of biotechnological products. In this study, Ganoderma spp. collected from the Lower Volta River Basin were genetically analyzed using the nuclear ribosomal sequences, the internal transcribed spacer 2 (ITS 2), the complete internal transcribed spacer (ITS), and the nuclear large subunit (nLSU). Blastn search and sequence analysis revealed that the sample we coded as Ganoderma LVRB-2 belongs to G. mbrekobenum, whereas Ganoderma LVRB-1, Ganoderma LVRB-14, and Ganoderma LVRB-16 belong to the species G. enigmaticum. Our analysis further demonstrates that Ganoderma LVRB-17 belongs to the species G. resinaceum. Thus, the five samples collected in the present study were positioned in three different distinct groups, namely G. mbrekobenum, G. enigmaticum, and G. resinaceum. The current data may serve as reference points for future studies.
Data from: Discussion of ‘A Bayesian multinomial regression model for paleoclimate reconstruction with time uncertainty’

It is a pleasure to be a discussant on this paper; one that exhibits the best of both applied statistics and cutting edge methodology. The authors should be congratulated for the clarity of their expression and I hope this paper reaches a wide audience of palaeoclimate scientists, statisticians and environmental scientists more generally. Palaeoclimate is important: it provides useful constraints on the speed at which the climate changes; it helps us learn more about the fragility of our existence (all human history is encompassed in a uniquely warm and stable climate), and provides a method by which to test our physics-based models which allow us to predict future climate change.
Highly Reinforced Acrylic Resins for Hard Tissue Engineering and Their Suitability to Be Additively Manufactured through Nozzle-Based Photo-Printing

Mineralized connective tissues represent the hardest materials of human tissues, and polymer based composite materials are widely used to restore damaged tissues. In particular, light activated resins and composites are generally considered as the most popular choice in the restorative dental practice. The first purpose of this study is to investigate novel highly reinforced light activated particulate dental composites. An innovative additive manufacturing technique, based on the extrusion of particle reinforced photo-polymers, has been recently developed for processing composites with a filler fraction (w/w) only up to 10%. The second purpose of this study is to explore the feasibility of 3D printing highly reinforced composites. A variety of composites based on 2,2-bis(acryloyloxymethyl)butyl acrylate and trimethylolpropane triacrylate reinforced with silica, titanium dioxide, and zirconia nanoparticles were designed and investigated through compression tests. The composite showing the highest mechanical properties was processed through the 3D bioplotter AK12 equipped with the Enfis Uno Air LED Engine. The composite showing the highest stiffness and strength was successfully processed through 3D printing, and a four-layer composite scaffold was realized. Mechanical properties of particulate composites can be tailored by modifying the type and amount of the filler fraction. It is possible to process highly reinforced photopolymerizable composite materials using additive manufacturing technologies consisting of 3D fiber deposition through extrusion in conjunction with photo-polymerization.
Catecholaminergic Polymorphic Ventricular Tachycardia: Multiple Clinical Presentations of a Genetically Determined Disease

Background: Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a rare, inherited heart rhythm disorder that is caused by variants in genes responsible for cardiac calcium homeostasis. The aim of this study was to analyze different genotype-specific clinical manifestations of this disease. Methods and Results: We analyzed five CPVT cases from our institution in the context of specific patient characteristics and genotype–phenotype correlations. In this cohort, three of the index patients were male. The median age at diagnosis was 11 (11–30) years, and median age at disease onset was 12 (12–33) years. Four index patients suffered from syncope, while one female index patient suffered from out-of-hospital cardiac arrest. Two index patients experienced concomitant atrial flutter and atrial fibrillation. Three patients received an implantable cardioverter defibrillator and one patient received an event recorder. All index patients had causative genetic variants in the RYR2-gene. Conclusions: This study presents various phenotypic presentations of patients with CPVT harboring different pathogenic variants in the RYR2 gene, some of which have not previously been described in published studies. Syncope was the most prevalent symptom on admission. Adjustment of beta-blocker therapy may be necessary due to side effects. Moreover, our work further highlights the common occurrence of atrial tachyarrhythmias in these patients.
STIS at the NTCIR-17 MedNLP-SC Task: Incorporating Sentiment to Transformer Architecture for Adverse Drug Event Detection on Social Media

This paper presents the system and results of the STIS team for the Social Media (English) subtasks of the NTCIR-17 MedNLP-SC Task. We proposed incorporating the sentiment of social media texts into a pre-trained Transformer model in detecting adverse drug events on social media. A lexicon-based and rule-based sentiment analysis VADER model was used to predict each tweet sentiment. Based on the experimental results of the ADE vs. non-ADE binary classification task, our proposed fine-tuned model outperformed the baseline by a slight difference. Specifically, our model achieves a better F1 score for 9 of 22 symptoms in the symptom detection task.
Patent Foramen Ovale Percutaneous Closure: Evolution and Ongoing Challenges

Patent foramen ovale (PFO) concerns nearly a quarter of the general population and incidence may reach up to 50% in patients with cryptogenic stroke. Recent randomized clinical trials confirmed that percutaneous closure of PFO-related stroke reduces the risk of embolic event recurrence. PFO also comes into play in other pathogenic conditions, such as migraine, decompression sickness or platypnea–orthodeoxia syndrome, where the heterogeneity of patients is high and evidence for closure is less well-documented. In this review, we describe the current indications for PFO percutaneous closure and the remaining challenges, and try to provide future directions regarding the technique and its indications.
The supercooling point depression is the leading cold tolerance strategy for the variegated ladybug, [Hippodamia variegata (Goezel)]

The variegated ladybug, Hippodamia variegata is one of the most effective predators of various pests that hibernate as adult beetles. During the overwintering period from April 2021 to March 2022, we examined the supercooling point (SCP), cold tolerance, and physiological adaptations of beetles in Kerman, Iran. The beetles exhibited their greatest cold tolerance (63.4% after 24 h at −5°C) when their SCP was lowest (−23.2°C). Conversely, from April to October 2021, the SCP reached its peak (approximately −13.0°C), while cold tolerance was at its lowest level (6.7% after 24 h at −5°C). Cryoprotectant content (trehalose, glycerol, and glucose) was at its highest level in September (11.15, 10.82, and 6.31 mg/g, respectively). The critical thermal minimum (CTmin) reached its lowest point of −2.2°C in January and February. The lowest point of the lower lethal temperature (LLT) coincided with the lowest level of the SCP and the highest level of cold tolerance (in February, LT50 = −5.3°C, SCP = −23.2°C, and survival = 77.78% at −4°C/24 h). Chill-coma recovery time (CCRT) was examined at five different temperatures and two different exposure durations. The CCRT increased with a decrease in exposure temperature and time (68.0 s at −2°C after 2 h and 102.0 s at −2°C after 4 h). As the majority of the overwintering beetle’s mortality occurred at temperatures significantly higher than SCP, the adults of H. variegata are chill-susceptible insects that primarily rely on a depressed supercooling point to cope with unfavorable conditions during the overwintering period.
Theoretical design of uncooled mid-infrared PbSe P+pBn+ barrier detectors

A novel uncooled mid-wavelength infrared (MWIR) P+pBn+ barrier detector based on epitaxial PbSe absorber layer on Ge substrate is theoretically investigated by finite element analysis in order to achieve optimal detection performance. The simulated results show that the P+pBn+ barrier architecture can further effectively reduce the room-temperature dark current to 4.45 mA cm−2 under −0.1 V bias, which is 12 times lower than a PbSe pBn+ unipolar barrier device in a previous study. Moreover, the P+pBn+ barrier architecture exhibits excellent responsivity and detectivity of 1.83 A W −1 and 3.23 × 1010 cm Hz1/2 W−1 at 3.8 μm, respectively. These results suggest that this P+pBn+ barrier detector based on natural MBE epitaxy technology could have potential in the emerging high-sensitivity and high-detectivity uncooled MWIR applications.
In situ simulation and its effects on patient outcomes: a systematic review

Background The use of in situ simulation has previously been shown to increase confidence, teamwork and practical skills of trained professionals. However, a direct benefit to patient outcomes has not been sufficiently explored. This review focuses on the effect of in situ simulation training in a hospital setting on morbidity or mortality. Methods A combined search was conducted in PUBMED, OVID, WEB OF SCIENCE, CINAHL, SCOPUS and EMBASE. 478 studies were screened with nine articles published between 2011 and 2017 meeting the inclusion criteria for analysis. Results This review selected eight prospective studies and one prospective-retrospective study. Three studies isolated in situ simulation as an experimental variable while the remaining studies implemented in situ programmes as a component of larger quality improvement initiatives. Seven studies demonstrated a significant improvement in morbidity and/or mortality outcomes following integrated in situ simulation training. Conclusion Existing literature, albeit limited, demonstrates that in situ training improves patient outcomes either in isolation or within a larger quality improvement programme. However, existing evidence contains difficulties such as isolating the impact of in situ training from various potential confounding factors and potential for publication bias.
Reprocessed, Bias-Corrected CMORPH Global High-Resolution Precipitation Estimates from 1998

AbstractThe Climate Prediction Center (CPC) morphing technique (CMORPH) satellite precipitation estimates are reprocessed and bias corrected on an 8 km × 8 km grid over the globe (60°S–60°N) and in a 30-min temporal resolution for an 18-yr period from January 1998 to the present to form a climate data record (CDR) of high-resolution global precipitation analysis. First, the purely satellite-based CMORPH precipitation estimates (raw CMORPH) are reprocessed. The integration algorithm is fixed and the input level 2 passive microwave (PMW) retrievals of instantaneous precipitation rates are from identical versions throughout the entire data period. Bias correction is then performed for the raw CMORPH through probability density function (PDF) matching against the CPC daily gauge analysis over land and through adjustment against the Global Precipitation Climatology Project (GPCP) pentad merged analysis of precipitation over ocean. The reprocessed, bias-corrected CMORPH exhibits improved performance in represen.
Clinico-Hematological Profile of Acute Myeloid Leukemia: Experience From a Tertiary Care Cancer Center in North India

Introduction: Complete diagnosis of acute myeloid leukemia (AML) requires knowledge of clinical information combined with morphologic evaluation, immunophenotyping, karyotyping, and molecular genetic testing. The study intends to evaluate the demographic profile, clinical workup, and investigation, including flow cytometric immunophenotyping, in adult and pediatric age groups of AML. Materials and methods: This is a retrospective study of AML patients treated between January 2017 and December 2021. Clinical and demographic characteristics and investigation findings were recorded from case files and the hematology database. Result: A total of 896 cases of AML were registered during the given period, of which 819 cases were de-novo AML. Among those 819 cases, more than two-thirds of cases, i.e., 78.9% (N = 646), received induction chemotherapy. A significantly higher male-to-female ratio was observed (1.5:1). The median age was 22 years. The median time for diagnosis was three days and the median time for treatment intervention was four days. There were significant differences in the Eastern Cooperative Oncology Group (ECOG) performance status scores between pediatric and adult AML patients. Pediatric AML patients presented with better ECOG performance scores (ECOG performance scores 0 and 1) than adult patients (74.76% vs. 43.14%, p < 0.001). Further comparing adult vs. pediatric AML patients, normal karyotype (60.56% vs. 31.93%, p < 0.001) and NPM1 (22.25% vs. 6.72%, p < 0.001) and FLT3-ITD mutations (20.28% vs. 7.98%, p<0.001) were more common in the adult group, whereas AML-ETO (40.76% vs. 16.34%, p < 0.001) was more common in the pediatric group. Conclusion: The study highlights the presenting age is lower than global figures. The median time for initial diagnosis and the start of treatment is within the acceptable norms. Normal karyotype and NPM1 and FLT3 mutations were common in adult AML patients, whereas AML-ETO was more common in the pediatric cohort. These findings will help plan prospective studies and see the correlation with treatment outcomes. The laboratory workup practice currently complies with the standard guidelines at our center.
Sequential SBAS-InSAR Backward Estimation of Deformation Time Series

In recent years, many synthetic aperture radar (SAR) satellites have been launched to provide abundant SAR data, which creates a demand for dynamic monitoring of surface deformation. In general scenarios, we process SAR images within a fixed period to obtain the deformation time series. However, conventional interferometric SAR (InSAR) processing involves manually selecting a specific time period, making it impossible to capture the complete deformation process. Therefore, we propose a novel framework, that is, the sequential small baseline subset InSAR (SBAS-InSAR) backward estimation algorithm, which utilizes sequential least-squares adjustment to dynamically recover previous surface deformation time series. To validate the effectiveness of the proposed method, we conduct both simulated and real data experiments. Also, the simulated results obtained by new method are totally consistent with the traditional SBAS-InSAR method, while the standard deviation of the difference between the deformation time series obtained by InSAR and GNSS results is better than 6 mm. Moreover, the new method has higher computation efficiency.
Multi-Rock Mass Classification Systems for the Assessment of Excavation Method and Support Design of Spillway Tunnel, Sidan Dam, Bali, Indonesia

This paper presents the implementation of rock mass classification systems to determine the excavation method and the support design of the Spillway Tunnel, Sidan Dam, Bali, Indonesia. In order to mitigate the uncertainty associated with using single rock mass classification during designing tunnels, this study provides an evaluation by applying multiple rock mass classifications. Rock Mass Rating (RMR), QSystem, Geological Strength Index (GSI), Japan Society of Civil Engineering (JSCE), and Rock Mass Index (RMi) were among the rock mass classification systems used for comprehensive analysis. Rock mass parameters were determined based on engineering geological mapping and rock & soil core analysis. The rock mass quality of pyroclastic rock along the tunnel is generally poor to fair. Based on the GSI rating, digging and ripping excavation were recommended. The top heading with benching (1-3 m advance in top heading) was the proposed excavation method by RMR and JSCE. Each classification system advised the combination of reinforced shotcrete and rock bolt for the primary tunnel support with varying shotcrete thickness (30-400 mm), rock bolt length (2.6-6 m), and rock bolt spacing (1-2.5 m). However, field investigations during excavation and numerical stability analysis were recommended to eliminate risks and ensure safe construction.
Study on Urban Taxi Drivers’ Out-Dining Characters and Planning Implications in Beijing

In the cities of the 21st century, taxicabs become an important component supporting the urban public transportation system. The convenience and efficiency of taxi services will promote the urban daily activities and business activities, so as to increase the accessibility of urban space. Exploring the approach of time geography, this paper establishes its data base through cluster sampling questionnaire of 350 taxi drivers’ daily activities in Beijing. It’s found that the out-dining space of taxi drivers is more likely to locate between the second and third rings road, near the expressway, and are intended to agglomerate along diagonal direction streets, river banks and administrative boundaries. Typical daily paths based on in-depth interview of taxi drivers reveal that both individual characters and external constrains affect on the dining time- spatial decision. Specifically, individual characters such as the residential location and serving shifts influence the habit of long-term out-dining behavior, while the constrains such as economic affordability, passengers need and the viability to park influence the selection of a certain dining spot. Responding to the mismatch between dining service provision and taxi driver’s needs, suggestions are put forward from the perspective of urban planning. These suggestions include the establishing of more multi-functional driver’s centers in the gateway of a city and driving-through taking away food cafes, and prolonging the business hours of the existing dining facilities. It’s believed to provide some implications to build up an efficient urban public transportation system which meets the various and flexible daily commuting needs of citizens in the contemporary urban China.