Miracle-dz/UniFAR-FTUs huggingface dataset:
Backdoor Attack on 3D Grey Image Segmentation

3D grey image segmentation has become a promising approach to facilitate practical applications with the help of advanced deep learning models. Although a number of previous works have investigated the vulnerability of deep learning models to backdoor attack, there is no work to study the severe risk of backdoor attack on 3D grey image segmentation. To this end, we propose two backdoor attack methods on 3D grey image segmentation, including Full-control Backdoor Attack (FCBA) and Partial-control Backdoor Attack (PCBA), on 3D grey image segmentation by leveraging a frequency trigger injection function and a rotation-based label corruption function. Our proposed trigger injection function is applied to insert a 3D trigger pattern into the benign 3D grey images in the frequency domain while ensuring the invisibility of the trigger pattern. And the proposed rotation-based label corruption function is employed to yield the crafted labels with the aim of decreasing the performance of segmentation. Finally, through comprehensive experiments on a real-world dataset, we demonstrate the effectiveness of our proposed backdoor models, the frequency trigger injection function, and the rotation-based label corruption function.
Assessment of BoAHV-1 Seronegative Latent Carrier by the Administration of Two Infectious Bovine Rhinotracheitis Live Marker Vaccines in Calves

Seronegative latent carriers (SNLCs) are animals that carry the virus without detectable antibodies and pose a risk for disease transmission and diagnostic challenges, suggesting the importance of consideration of marker vaccines in managing them. Therefore, in this study, we evaluated two modified live infectious bovine rhinotracheitis (IBR) marker vaccines (single and double deletions) for their ability to generate SNLC calves. These vaccines were administered to four groups (n = 3 in each group) of three-month-old calves in the presence or absence of passive immunity. Three hundred days after the first vaccination and after confirming the IBR seronegativity of all animals, dexamethasone was administered intravenously for five consecutive days. Only animals immunized with the modified live IBR marker vaccine (single deletion) in the absence of passive immunity exhibited a more enduring immune response than those vaccinated in the presence of passive immunity. Moreover, the administration of a modified live IBR marker vaccine (double deletion) to calves with passive immunity generated SNLC. These findings underscore the potential of live IBR marker vaccine (double-deletions) to aid serological diagnostic tools and develop vaccination protocols in achieving the desired immune response, particularly in the context of latent carrier status, offering valuable insights into optimizing vaccination strategies for effective IBR control.
Thermal and Structural Study of a Brake Disc Using COMSOL

This study presents an analysis of the thermal phenomena operating in a brake disc in service (high temperature amplitudes, high thermal gradients between disc/pad friction, etc.). From this analysis, two numerical modeling of the pad are proposed which are based on relevant hypotheses. This modeling uses the finite element method which makes it possible to first solve the problem of heat transfer, due to the friction of the pads on the disc.
Gene Expression of Ethanol and Acetate Metabolic Pathways in the Acinetobacter baumannii EmaSR Regulon

Background: Previous studies have confirmed the involvement of EmaSR (ethanol metabolism a sensor/regulator) in the regulation of Acinetobacter baumannii ATCC 19606 ethanol and acetate metabolism. RNA-seq analysis further revealed that DJ41_568-571, DJ41_2796, DJ41_3218, and DJ41_3568 regulatory gene clusters potentially participate in ethanol and acetate metabolism under the control of EmaSR. Methods: This study fused the EmaSR regulon promoter segments with reporter genes and used fluorescence expression levels to determine whether EmaSR influences regulon expression in ethanol or acetate salt environments. The enzymatic function and kinetics of significantly regulated regulons were also studied. Results: The EmaSR regulons P2796 and P3218 exhibited > 2-fold increase in fluorescence expression in wild type compared to mutant strains in both ethanol and acetate environments, and PemaR demonstrated a comparable trend. Moreover, increases in DJ41_2796 concentration enhanced the conversion of acetate and succinyl-CoA into acetyl-CoA and succinate, suggesting that DJ41_2796 possesses acetate: succinyl-CoA transferase (ASCT) activity. The kcat/KM values for DJ41_2796 with potassium acetate, sodium acetate, and succinyl-CoA were 0.2131, 0.4547, and 20.4623 mM−1s−1, respectively. Conclusions: In A. baumannii, EmaSR controls genes involved in ethanol and acetate metabolism, and the EmaSR regulon DJ41_2796 was found to possess ASCT activity.
Deep Multi-kernel Clustering Network

In this paper, a deep multi-kernel clustering network, named DMKCN, is proposed to learn a high-quality and structurally separable kernel representation for the clustering task. Specifically, a multi-kernel learner is proposed to choose a suitable kernel function by learning a suitable combination of kernel functions automatically. A kernel-aid encoder module, consisting of a series of multi-kernel learners, is proposed to learn the structurally separable kernel representation. Besides, a dual self-supervised mechanism, consisting of a kernel self-supervised strategy and a representation self-supervised strategy, is designed to uniformly optimize the kernel representation learning and structural partition. The kernel self-supervised strategy is developed to supervise the multi-kernel learners with the consideration of an objective of clustering task, the representation self-supervised strategy is developed to guide the optimization of kernel representation learning by reconstructing the raw data. Extensive experiments on six real-world datasets demonstrate the outstanding performance of our proposed DMKCN.
A Dual-Feedback Adaptive Clone Selection Algorithm With Golden Sine Search for Parameter Identification of Photovoltaic Models

Converting solar energy to electricity efficiently requires an accurate model with well-estimated parameters in a photovoltaic (PV) system. However, identifying parameters for the PV model remains challenging attributed to the nonlinearity and multimodality inherent in diode circuit models. In this paper, we propose a dual-feedback adaptive clone selection algorithm with a golden sine search. The clonal selection algorithm (CSA), known for its inherent diversity maintenance ability, offers an advantage in handling multimodal optimization problems. The critical factor is the cloning operator, particularly the determination of clone size, crucial for balancing exploration and exploitation. To address the conflict between clone size and convergence speed, we introduce a dual feedback adaptive cloning strategy. This strategy considers both the fitness difference between the hypermutated population and the original population and the harmonic mean distance of the population. Additionally, to improve accuracy, we introduce an elite learning strategy based on the golden sine mechanism. The proposed algorithm’s effectiveness is assessed through comprehensive experiments on PV cells and three PV modules, considering both single diode and double diode models, respectively. The experimental results demonstrate that the accuracy of parameter identification achieved by the proposed algorithm exceeds 99.9% for all three types of PV modules. Moreover, we validate the algorithm’s performance using manufacturer’s datasheets with varying irradiations and temperatures. All experiments consistently indicate the stability and effectiveness of the proposed method in accurately identifying the parameters of PV models.
Wave Events: Climatology, Trends, and Relationship to Northern Hemisphere Winter Blocking and Weather Extremes

AbstractDiagnostics of finite-amplitude local wave activity (LWA) are applied to the 500-hPa geopotential height field to diagnose persistent synoptic weather events of anomalously large wave activity in the Northern Hemisphere. By considering the cyclonic and anticyclonic components of LWA separately, persistent weather systems associated with large-amplitude troughs and ridges are detected. While anticyclonic wave events are predominantly found over Europe and Alaska, cyclonic wave events usually occur over East Asia and northeastern Canada. Those preferred regions correspond to the location of planetary-scale ridges and troughs, which contribute, together with transient anomalies, to the formation of wave events. Although wave events are not blocking events per definition, they are typically associated with increased blocking in their vicinity. Their spatial relationship to blocking, however, varies depending on their cyclonic or anticyclonic nature and the type of wave-breaking signatures. Wave events.
Evaluation of Cytotoxicity and Oxidative Stress of Whole Aerosol from Vuse Alto ENDS Products

Assessment of in vitro cytotoxicity is an important component of tobacco product toxicological evaluations. However, current methods of regulatory testing involve exposing monolayer cell cultures to various preparations of aerosols from cigarettes or other emerging products such as electronic nicotine delivery systems (ENDS), which are not representative of human exposure. In the present study, a whole aerosol (WA) system was used to expose lung epithelial cultures (2D and 3D) to determine the potential of six Vuse Alto ENDS products that varied in nicotine content (1.8%, 2.4%, and 5%) and flavors (Golden Tobacco, Rich Tobacco, Menthol, and Mixed Berry), along with a marketed ENDS and a marked cigarette comparator to induce cytotoxicity and oxidative stress. The WA from the Vuse Alto ENDS products was not cytotoxic in the NRU and MTT assays, nor did it activate the Nrf2 reporter gene, a marker of oxidative stress. In summary, Vuse Alto ENDS products did not induce cytotoxic or oxidative stress responses in the in vitro models. The WA exposures used in the 3D in vitro models described herein may be better suited than 2D models for the determination of cytotoxicity and other in vitro functional endpoints and represent alternative models for regulatory evaluation of tobacco products.
Intramuscular vaccination against SARS-CoV-2 transiently induces neutralizing IgG rather than IgA in the saliva

The mucosal immunity is crucial for restricting SARS-CoV-2 at its entry site. Intramuscularly applied vaccines against SARS-CoV-2 stimulate high levels of neutralizing Abs in serum, but the impact of these intramuscular vaccinations on features of mucosal immunity is less clear. Here, we analyzed kinetic and functional properties of anti-SARS-CoV-2 Abs in the saliva after vaccination with BNT162b2. We analyzed a total of 24 healthy donors longitudinally for up to 16 months. We found that specific IgG appeared in the saliva after the second vaccination, declined thereafter and reappeared after the third vaccination. Adjusting serum and saliva for the same IgG concentration revealed a strong correlation between the reactivity in these two compartments. Reactivity to VoCs correlated strongly as seen by ELISAs against RBD variants and by live-virus neutralizing assays against replication-competent viruses. For further functional analysis, we purified IgG and IgA from serum and saliva. In vaccinated donors we found neutralizing activity towards authentic virus in the IgG, but not in the IgA fraction of the saliva. In contrast, IgA with neutralizing activity appeared in the saliva only after breakthrough infection. In serum, we found neutralizing activity in both the IgA and IgG fractions. Together, we show that intramuscular mRNA vaccination transiently induces a mucosal immunity that is mediated by IgG and thus differs from the mucosal immunity after infection. Waning of specific mucosal IgG might be linked to susceptibility for breakthrough infection.
Neogene sloth assemblages (Mammalia, Pilosa) of the Cocinetas Basin (La Guajira, Colombia): implications for the Great American Biotic Interchange

We describe sloth assemblages from the Cocinetas Basin (La Guajira peninsula, Colombia), found in the Neogene Castilletes and Ware formations, located in northernmost South America, documenting otherwise poorly known biotas. The tentative referral of a specimen to a small megatherioid sloth, Hyperleptus? , from the early–middle Miocene Castilletes Formation, suggests affinities of this fauna with the distant Santa Cruz Formation and documents a large latitudinal distribution for this taxon. The late Pliocene Ware Formation is much more diverse, with five distinct taxa representing every family of ‘ground sloths’. This diversity is also remarkable at the ecological level, with sloths spanning over two orders of magnitude of body mass and probably having different feeding strategies. Being only a few hundred kilometres away from the Isthmus of Panama, and a few hundred thousand years older than the classically recognized first main pulse of the Great American Biotic interchange (GABI 1), the Ware Formation furthermore documents an important fauna for the understanding of this major event in Neogene palaeobiogeography. The sloths for which unambiguous affinities were recovered are not closely related to the early immigrants found in North America before GABI 1.
Performance Evaluation of Machine Learning Classifiers for Predicting Denial-of-Service Attack in Internet of Things

—Eliminating security threats on the Internet of Things (IoT) requires recognizing threat attacks. IoT and its implementations are currently the most common scientific field. When it comes to real-world implementations, IoT's attributes, on the one hand, make it simple to apply, but on the other hand, they expose it to cyber-attacks. Denial of Service (DoS) attack is a type of threat that is now widespread in the field of IoT. Its primary goal is to stop or damage service or capability on a target. Conventional Intrusion Detection Systems (IDS) are no longer sufficient for detecting these sophisticated attacks with unpredictable behaviors. Machine learning (ML)--based intrusion detection does not need a massive list of expected activities or a variety of threat signatures to create detection rules. This study aims to evaluate different ML classifiers for network intrusion detection that focus on DoS attacks in the IoT environment to determine the best ML classifier that can detect the DoS attack. The XGBoost, Decision Tree (DT), Gaussian Naive Bayes (NB), Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM) ML classifiers are used to evaluate the DoS attack. The UNSW-NB15 dataset was used for this study. The obtained accuracy rate for XGboost was 98.92%, SVM 98.62%, Gaussian NB 83.75%, LR 97.74%, RF 99.48%, and DT 99.16%. where the precision rate for XGboost, SVM, Gaussian NB, LR, RF, and DT was 98.40%, 98.29%, 77.50%, 97.14%, 99.21%, and 99.12%, respectively. The sensitivity rate for XGboost, SVM, Gaussian NB, LR, RF, and DT was 99.29%, 98.76%, 91.87%, 98.06%, 99.69%, and 99.08%, respectively. The results show that the RF classifier outperformed other classifiers in terms of Accuracy, Precision, and Sensitivity.
Rainfall and runoff variability in the southwestern river system of Ghana

A number of water resources development schemes including hydroelectric and water supply projects, have been planned in the southwestern river system of Ghana. However, most of the data sets used in the hydrological studies were short and the present study examined the temporal variation and changes in the rainfall and runoff series of the river system. Plots of annual, wet and dry season rainfall and runoff revealed a reduction in magnitudes from 1950-1970 high values to 1971-1991 low values. The changes in the dry season runoff were in particular remarkable. Statistical tests showed that the changes in rainfall and runoff for the two time periods were significant at the 5% level. The flows exceeded 95% of the time can give some indications of low flow dependabilities. Values computed from 1950-1970 and 1971-1991 gave 71 and 17 m 3 s -1 respectively. Thus the reliability of using runoff for water resources schemes without impoundment could be very optimistic if only data ending in the seventies are used.
Opinion: The Key Steps in the Origin of Life to the Formation of the Eukaryotic Cell

The path from life’s origin to the emergence of the eukaryotic cell was long and complex, and as such it is rarely treated in one publication. Here, we offer a sketch of this path, recognizing that there are points of disagreement and that many transitions are still shrouded in mystery. We assume life developed within microchambers of an alkaline hydrothermal vent system. Initial simple reactions were built into more sophisticated reflexively autocatalytic food-generated networks (RAFs), laying the foundation for life’s anastomosing metabolism, and eventually for the origin of RNA, which functioned as a genetic repository and as a catalyst (ribozymes). Eventually, protein synthesis developed, leading to life’s biology becoming dominated by enzymes and not ribozymes. Subsequent enzymatic innovation included ATP synthase, which generates ATP, fueled by the proton gradient between the alkaline vent flux and the acidic sea. This gradient was later internalized via the evolution of the electron transport chain, a preadaptation for the subsequent emergence of the vent creatures from their microchamber cradles. Differences between bacteria and archaea suggests cellularization evolved at least twice. Later, the bacterial development of oxidative phosphorylation and the archaeal development of proteins to stabilize its DNA laid the foundation for the merger that led to the formation of eukaryotic cells.
Providing an in vitro depiction of microglial cells challenged with immunostimulatory extracellular vesicles of Naegleria fowleri

Naegleria fowleri is the causative agent of primary amoebic meningoencephalitis, a rapid and acute infection of the central nervous system with a fatal outcome in >97% of cases. Due to the infrequent report of cases and diagnostic gaps that hinder the possibility of recovering clinic isolates, studies related to pathogenesis of the disease are scarce. However, the secretion of cytolytic molecules has been proposed as a factor involved in the progression of the infection. Several of these molecules could be included in extracellular vesicles (EVs), making them potential virulence factors and even modulators of the immune response in this infection. In this work, we evaluated the immunomodulatory effect of EVs secreted by two clinic isolates of Naegleria fowleri using in vitro models. For this purpose, characterization analyses between EVs produced by both isolates were first performed, for subsequent gene transcription analyses post incubation of these vesicles with primary cultures from mouse cell microglia and BV-2 cells. Analyses of morphological changes induced in primary culture microglia cells by the vesicles were also included, as well as the determination of the presence of nucleic acids of N. fowleri in the EV fractions. Results revealed increased expression of NOS, proinflammatory cytokines IL-6, TNF-α, and IL-23, and the regulatory cytokine IL-10 in primary cultures of microglia, as well as increased expression of NOS and IL-13 in BV-2 cells. Morphologic changes from homeostatic microglia, with small cellular body and long processes to a more amoeboid morphology were also observed after the incubation of these cells with EVs. Regarding the presence of nucleic acids, specific Naegleria fowleri DNA that could be amplified using both conventional and qPCR was confirmed in the EV fractions. Altogether, these results confirm the immunomodulatory effects of EVs of Naegleria fowleri over microglial cells and suggest a potential role of these vesicles as biomarkers of primary acute meningoencephalitis.
The Impact Of School Feeding Programme On Performance Of Pre-school Children In Kikuyu District – Central Province

v Table of contents . vi List of Figures . ix List of Tables . x List Abbreviations and Acronyms . xi CHAPTER ONE: INTRODUCTION . 1 1.1 Background to the Study . 1 1.2 Statement of the Problem . 4 1.3 Purpose of the Study . 4 1.4 Objectives of the study . 4 1.5 Research Questions . 5 1.6 Significance of the Study . 5 1.7 Limitations of the Study . 6 1.8 Delimitations of the Study. 6 1.9 Basic Assumption of the Study . 6 1.1. 0 Definition of Key Terms . 6 1.1.1 Organisation of the Study . 7 CHAPTER TWO: LITERATURE REVIEW . 8 2.
An Evaluation of Hemostatic Dysregulation in Canine Multicentric Lymphoma

Simple Summary Canine lymphoma is the most common malignant hematopoietic tumor. It is mainly seen in middle-aged or older dogs, and it is characterized by a clonal proliferation of B or T lymphocytes. The development of hemostatic changes is associated with malignant tumors in human medicine and is also reported in dogs. These hemostatic alterations may contribute unfavorably to the morbidity and mortality associated with the disease. The aim of this study was to evaluate, in a large group of dogs affected by lymphoma compared to dogs with other diseases, whether there is an alteration of hemostatic parameters in canine lymphoma and, if so, whether these were correlated with the type (B or T) of lymphoma and with the stage of the disease. Abstract Multiple hemostatic abnormalities are associated with paraneoplastic syndrome and some malignant tumors. Lymphoma is the most common hematopoietic neoplasm in dogs, sometimes associated with hemostatic changes. The objectives of this study were to evaluate the behavior of coagulation parameters in dogs with multicentric lymphoma compared with diseased dogs without lymphoma, to separately evaluate the effect of immunophenotype (B lymphoma versus T lymphoma) on the variables of interest as well as the effect of disease stage (stage II to IV versus stage V). Specifically, a cross-sectional study was performed with a matched comparison group considering 170 dogs with B or T lymphoma (group 1) and 170 dogs with no lymphoma or other neoplastic processes but other diseases (group 0). Eight coagulation parameters were evaluated: platelet count (Plt), activated partial thromboplastin time (aPTT), prothrombin time (PT), thrombin time (TT), fibrinogen, fibrin/products of fibrinogen degradation (FDPs), fibrin D-dimers, and antithrombin (AT). Dogs with lymphoma showed prolonged PT and TT, decreased fibrinogen, increased FDP, and decreased Plt compared with group 0. The effect of disease stage was evaluated separately for dogs with stage II to IV lymphoma and dogs with stage V lymphoma; patients with stage II–IV lymphoma showed no significant differences, while in dogs with stage V lymphoma, a prolongation of PT and TT, a decrease in fibrinogen, an increase in FDPs and a decrease in Plt were found compared with the group 0. Finally, the comparison between B lymphoma and T lymphoma showed no significant differences in coagulation parameters between the two groups. Logistic regression analysis demonstrated that low fibrinogen and platelet levels were the most significant predictors of lymphoma in a cohort of canine patients. These hemostatic abnormalities in lymphoma appeared to be associated with the stage of the disease rather than the lymphoma immunophenotype. These findings pave the way for the possible scenario of lymphoma-associated fibrinolysis and the so far undescribed pattern of hyperfibrinolysis associated with the most severe stage of lymphoma.