Miracle-dz/UniFAR-FTUs huggingface dataset:
Complex Event Processing for Object Tracking and Intrusion Detection in Internet of Things Environments

With the development of Internet of Things (IoT), there have been more and more services and applicationsdeployed in physical spaces and information systems. The massive number of sensors anddevices are embedded in IoT environments, which produce huge amounts of data continuously forthe IoT systems and platforms. Processing these data stream generated by the IoT networks with differentpatterns has raised new challenges for the real-time performance of intrusion detection system(IDS) in IoT environments, which has to react quickly to the hacking attacks and malicious activitiesto IoT. In this paper, a complex event processing (CEP) based IDS model for object detectiontracking and intrusion detection in the IoT environments is proposed. Esper, an open source complexevent processing engine is used to develop the model. In this model, the cincoming streams of dataare detected by Esper engine according to the predefined EPL rules. And then, trigger correspondinglisteners, the normal events are sent to the higher layer application as an new event through theadapter. In the alert event processor, the abnormal events are divided into the attack events and theother causes of abnormal events, such as sensor fault, transmission delay, etc.
Overview of Left Ventricular Segmentation in Ultrasound Images

Due to its great temporal resolution and quick acquisition periods, two-dimensional echocardiography, or shorter 2D echo, is the most used non-invasive approach for assessing heart disease. It offers a grayscale image that anatomical details can be extracted from to evaluate heart functioning. The initial stage in quantifying cardiac function in 2D echo is the segmentation of the left ventricular (LV) walls. The primary boundary identification methods used for 2D echo at the moment are semi-automatic or manual delineation carried out by professionals. However, manual or semi-automatic approaches take a lot of time and are subjective, which makes them vulnerable to both intra- and inter-observer variability. Many researchers have tried to automate the process of left ventricle segmentation. The extensive use of deep learning algorithms has lately changed medical image analysis. The revolution has primarily been powered by supervised machine learning with convolutional neural networks. In this paper, we will provide a short overview of some of the popular deep-learning techniques for left ventricular segmentation in two-dimensional echocardiography.
Unveiling the Diversity of Hydnum in the Republic of Korea with One New Species, Hydnum paucispinum

Abstract Hydnum is a genus of ectomycorrhizal fungi belonging to the Hydnaceae family. It is widely distributed across different regions of the world, including North America, Europe, and Asia; however, some of them showed disjunct distributions. In recent years, with the integration of molecular techniques, the taxonomy and classification of Hydnum have undergone several revisions and advancements. However, these changes have not yet been applied in the Republic of Korea. In this study, we conducted an integrated analysis combining the morphological and molecular analyses of 30 specimens collected over a period of approximately 10 years in the Republic of Korea. For molecular analysis, the sequence data of the internal transcribed spacer (ITS) region, the large subunit of nuclear ribosomal RNA gene (nrLSU), and a portion of translation elongation factor 1-α (TEF1) were employed as molecular markers. Through this study, we identified eight species that had previously not been reported to occur in the Republic of Korea, including one new species, Hydnum paucispinum. A taxonomic key and detailed descriptions of the eight Hydnum species are provided in this study.
Treatment-Resistant Depression in America Latina study: one-year follow-up of treatment resistant depression patients under standard of care reveals insights on quality of life, disability, work impairment, and depressive symptoms

Introduction Depressive Disorders are on the rise worldwide. This is also the case in Latin America (LatAm). Treatment-Resistant Depressive Disorder (TRD) poses additional burden to patients with depression. Impacts quality of life (QoL) and other dimensions, and standard of care (SOC) is insufficient to achieve the desired clinical outcomes. Evidence from LatAm is, however, lacking. The present study was devised as a 1-year follow-up of the SOC in TRD patients in LatAm to explore the burden of TRD. Methods This was an observational, multinational, longitudinal study. Patients with clinical diagnosis of TRD in LatAm were included in a 1-year follow-up with SOC. Beyond the Sociodemographic characterization, outcome measures were QoL (EQ-5D-5L), disability (Sheehan Disability Scale - SDS), work productivity (Work Productivity and Activity Incapacity Questionnaire: depression - WPAI:D) and depression severity (Patient Health Questionnaire-PHQ9). Patients were assessed every 3-months and comparison was performed based on change from baseline to each visit and end of study (EOS - 12 months). Results Patients averaged 48 (± 13.12) years, mostly female (80.9%) and married/consensual union (42.5%) or single patients (34.4%). Despite the SOC treatment, three-quarters of the patients remained symptomatic at EOS, regardless of the significant longitudinal decrease (p ≤ 0.001). Similar trends were found for disability (p ≤ 0.001) -82.2% of the patients reporting work/school disruption at EOS-, percentage of work (34%) and activity impairment (40%) at EOS (p ≤ 0.001) and only 29.2% of patients with depressive severity “none” at EOS (p ≤ 0.001). The results portray the need to improve clinical outcomes in this complex and burdensome disease in LatAm. Discussion Here we show that the burden of TRD remains significant in essential dimensions of everyday life at EOS underlining the need for better therapeutic solutions. The improvements in most patients do not provide the desired outcome of return to the state before the condition. Further research should focus on identifying which treatments provide better outcomes in a real-world context.
A Review of the Advancements in Targeted Therapies for Breast Cancer

Breast cancer, the second-most common and lethal disease in women, poses a severe danger to global health. Breast cancer rates continue to climb despite advances in medical technology. Predictions indicate that by 2040, there will be more than three million new cases yearly. Targeted medicines have experienced a profound transformation in treating breast cancer, allowing for individualized strategies that lessen side effects and improve patient outcomes. This thorough analysis gives a rigorous investigation of current developments in breast cancer-targeted treatments. It carefully examines several subtypes, including hormone receptor-positive (HR+), HER2-positive (HER2+), and triple-negative breast cancer (TNBC), recognizing the illness' fundamental variety. It offers specialized treatment plans catered to each subtype's particular traits. The review also examines how precise genetic abnormalities like BRCA1/2 and PIK3CA mutations and molecular profiling facilitate therapy selection. Monoclonal antibodies and small molecule inhibitors are some of the targeted medicines examined in the study. It explains how each of these treatments works and supports its findings with data from clinical trials. It also considers potential new medications and addresses persistent problems, such as resistance mechanisms, chances for combining therapies, and cutting-edge patient classification techniques. This study seeks to give healthcare professionals, researchers, and patients a thorough overview of the recent advancements in breast cancer-targeted therapy by drawing on the opinions of top authorities in the area. The coordinated effort aims to create customized, efficient therapies, eventually bolstering the battle against this powerful illness.
Lessons Learned from Case Histories of Dynamic Compaction at Municipal Solid Waste Sites

AbstractDynamic compaction (DC) has an extensive performance record on municipal solid waste (MSW) sites. A database of 56 test sites has been developed and analyzed to garner lessons on the performance of DC on MSW sites. Analysis of the data indicates that the depth of improvement in MSW is shallower than the depth of improvement in cohesionless soils with values of the empirical parameter, n, for MSW commonly on the order of 0.4±0.05. DC results in a denser waste matrix that increases the stiffness of the waste by a factor of 2.8–24 compared with its unimproved state and results in reduction of waste compression upon load application. The achieved higher density and more stable structure of the MSW result in a lower rate and amount of long-term settlement. Limited studies indicate that DC is an effective technique to reduce settlements. Surface wave seismic methods represent an attractive method to assess the depth of improvement. Vibrations induced by DC are attenuated faster in MSW than in inorganic .
Correlation distance of waveforms for closely located events—I. Implication of the heterogeneous structure around the source region of the 1995 Hyogo-Ken Nanbu, Japan, earthquake (Mw = 6.9)

SUMMARY The way in which cross-correlation coefficients of seismograms for closely located events change with frequency and event separation was investigated by using records of aftershocks of the 1995 Hyogo-Ken Nanbu, Japan, earthquake (M w = 6.9). For 11 master events (M between 2.9 and 3.5) on the mainshock fault plane and smaller events (M greater than 2.0) within 5 km of the master events, the relative hypocentre was determined with respect to each master event and cross-correlation coefficients of seismograms were calculated for a time window of 2 s including direct P waves for pairs of events in each cluster at two stations with an average hypocentral distance of 36 km and 42 km. Relative hypocentres were located within errors of several hundred metres for most of the earthquakes. Cross-correlation coefficients are high for frequencies below 8 Hz and decrease with increasing frequency above 8 Hz at both stations. It was also found that cross-correlation coefficients decay with increasing event separation. If the source‐time function is assumed to be simple for small earthquakes, it may be said that dependence of cross-correlation coefficients on event separation below 8 Hz is mainly influenced by the heterogeneous structure around the earthquake source. We introduce a correlation distance where cross-correlation coefficients first become lower than 0.6 with increasing event separation. The correlation distance exhibits a clear regional difference: it is less than 4.5 km in the Awaji region and more than 4.5 km in the Kobe region. This result implies that heterogeneity of velocity structure around the earthquake source is stronger in the Awaji region than in the Kobe region. It is notable that both low- and high-frequency seismic waves radiated strongly from the Awaji region at the time of the mainshock. The correlation distance may be an indicator of heterogeneous structure around an earthquake source, which may have a close relationship to the rupture process itself.
The Impact of Informational Intervention on HPV Vaccination Intention among Heterosexual Men

Human papillomavirus (HPV) is one of the most common sexually transmitted infections (STIs). However, despite widespread under-vaccination amongst men and the importance of vaccinating both sexes to curb the spread of HPV, research has focused on promoting HPV vaccination predominantly amongst women. Therefore, the current study examines the effectiveness of different informational interventions in promoting vaccination intentions amongst heterosexual men. In a preregistered study of 583 unvaccinated adult men, we randomly assigned participants to one of four informational interventions aimed at promoting awareness of HPV risks and vaccine uptake: (1) risks to oneself (n = 145), (2) risks to their female partner (n = 144), (3) risks to oneself and their female partner (n = 153), and (4) general vaccine information (n = 153). Amongst participants reporting a sexual history (67%), intentions to get vaccinated significantly increased by 10.75 points on a 100-point scale (p < 0.01) after they received information about the risks of HPV for both themselves and their female partner, compared to receiving information about only their own HPV risk. These findings provide valuable guidance for public health officials and policymakers into the effectiveness of different messaging strategies in promoting HPV vaccination amongst adult male populations to increase vaccination rates.
Assessment of lower food web in Hamilton Harbour, Lake Ontario, 2002 - 2004.

iv RESUME v Assessment of Hamilton Harbour; Background . R. Dermott 1 Water Quality and Phytoplankton Photosynthesis M. Burley 9 An Integrated Assessment of Microbial and Planktonic Communities of Hamilton Harbour M. Munawar, M. Fitzpatrick 43 Zooplankton in Hamilton Harbour: 2002-2004 J. Gerlofsma, K. Bowen, O. Johannsson 65 Benthic Fauna in Hamilton Harbour: 2002 2003 R. Dermott, R. Bonnell 91
Confronting the human papillomavirus–HIV intersection: Cervical cytology implications for Kenyan women living with HIV

Background High-risk human papillomavirus (HR-HPV) is the primary cause of cervical cancer, leading to over 311 000 global deaths, mainly in low- and middle-income countries. Kenyan women living with HIV (WLHIV) face a disproportionate burden of HR-HPV. Objectives We determined the prevalence of HR-HPV infections and their association with cervical cytology findings among Kenyan WLHIV. Method We conducted a cross-sectional study among WLHIV attending the HIV care and treatment clinic at the Kenyatta National Hospital (KNH), Kenya’s national referral hospital. Study nurses collected a cervical sample with a cytobrush for HR-HPV genotyping using Gene Xpert® assays and HPV Genotypes 14 Real-TM Quant V67-100FRT. Bivariate analysis explored the associations. Results We enrolled 647 WLHIV (mean age of 42.8 years), with 97.2% on antiretroviral therapy (ART) and 79% with a suppressed viral load (< 50 copies/mL plasma). The prevalence of any and vaccine-preventable HR-HPV was 34.6% and 29.4%, respectively, with HPV 52 being the most common genotype (13.4%). Among WLHIV with HR-HPV infections, 21.4% had abnormal cervical cytology. Women with multiple HR-HPV infections were more likely to have abnormal cytology compared to those with single HR-HPV infections (34.9 vs 9.3%, adjusted odds ratio [aOR] = 6.2, 95% confidence interval [CI]: 2.7–14.1, P = 0.001). Women with HR-HPV infection (single or multiple) were more likely to be on the second-line ART regimen compared to those without HR-HPV infections (53.1% vs 46.7%, aOR = 2.3, 95% CI: 1.3–4.1, P = 0.005). Conclusion Among WLHIV at KNH, abnormal cytology was common and more frequent among women with multiple HR-HPV infections.
YOLO-SCL: a lightweight detection model for citrus psyllid based on spatial channel interaction

Efficient and accurate detection and providing early warning for citrus psyllids is crucial as they are the primary vector of citrus huanglongbing. In this study, we created a dataset comprising images of citrus psyllids in natural environments and proposed a lightweight detection model based on the spatial channel interaction. First, the YOLO-SCL model was based on the YOLOv5s architecture, which uses an efficient channel attention module to perform local channel attention on the inputs in the recursive gated convolutional modules to achieve a combination of global spatial and local channel interactions, improving the model’s ability to express the features of the critical regions of small targets. Second, the lightweight design of the 21st layer C3 module in the neck network of the YOLO-SCL model and the small target feature information were retained to the maximum extent by deleting the two convolutional layers, whereas the number of parameters was reduced to improve the detection accuracy of the model. Third, with the detection accuracy of the YOLO-SCL model as the objective function, the black widow optimization algorithm was used to optimize the hyperparameters of the YOLO-SCL model, and the iterative mechanism of swarm intelligence was used to further improve the model performance. The experimental results showed that the YOLO-SCL model achieved a mAP@0.5 of 97.07% for citrus psyllids, which was 1.18% higher than that achieved using conventional YOLOv5s model. Meanwhile, the number of parameters and computation amount of the YOLO-SCL model are 6.92 M and 15.5 GFlops, respectively, which are 14.25% and 2.52% lower than those of the conventional YOLOv5s model. In addition, after using the black widow optimization algorithm to optimize the hyperparameters, the mAP@0.5 of the YOLO-SCL model for citrus psyllid improved to 97.18%, making it more suitable for the natural environments in which citrus psyllids are to be detected. The experimental results showed that the YOLO-SCL model has good detection accuracy for citrus psyllids, and the model was ported to the Jetson AGX Xavier edge computing platform, with an average processing time of 38.8 ms for a single-frame image and a power consumption of 16.85 W. This study provides a new technological solution for the safety of citrus production.
Analisis dan Perbaikan Sistem Kompensasi Pada UKM ABC dengan Metode Adhered dan Overlapping

Sistem kompensasi memiliki peran penting dalam manajemen sumber daya manusia. Penelitian ini bertujuan untuk menilai sistem kompensasi pada UKM ABC yang bergerak di sektor pertanian modern dan memberikan rekomendasi perbaikan sistem kompensasi. Metode yang digunakan dalam penelitian meliputi penentuan job value berdasarkan faktor kompensasi dengan metode Hay, penentuan job grading dengan metode given grade dan min max, dan pemetaan gaji dengan metode adhered dan overlapping. Hasil yang diperoleh dari penelitian ini adalah gaji pokok yang diterima seluruh karyawan masih kurang ideal apabila dibandingkan dengan upah minimum dan belum ada penentuan job grading. Perbaikan dilakukan dengan menghitung job value dan membagi job title ke dalam tiga grade. Berdasarkan pemetaan gaji untuk sistem kompensasi yang lebih ideal, diperoleh hasil bahwa pemetaan gaji menggunakan metode overlapping dapat dipertimbangkan oleh perusahaan untuk diterapkan
Hepatitis B Virus Genotype Influence on Virological and Enzymatic Measures over Time—A Retrospective Longitudinal Cohort Study

HBV is a hepatotropic virus with multiple genotypes. It is uncertain if specific genotype(s) influence virological measures and/or liver markers over time. It is unclear whether nucleos(t)ide analogue therapy response is influenced by genotype. In this retrospective longitudinal study, we utilized data from The Ottawa Hospital Viral Hepatitis Program (TOHVHP) to evaluate the role of HBV genotype on viral load, liver enzymatic levels, fibrosis progression, and parenchymal inflammation and steatosis over time. HBV DNA, ALT, and AST levels, as well as transient elastography scores for fibrosis (E) and inflammation/steatosis (CAP), were modeled using mixed-effects linear regression. Interaction terms between HBV genotype and time were included to investigate if there was a difference in trends between genotypes. A total of 393 HBV patients infected with genotypes A-E were included. The mean age was 44.4 years, and 56% were male. Asian (50.5%), Black (29.1%), and White (6.4%) patients were well-represented. By multivariate analysis, we found no evidence that the trajectories of these commonly measured viral or liver measures varied over time by HBV genotype in those receiving HBV nucleos(t)ides and in those not on antiviral therapy.
On Lists of Words and Lists of Names

The President : I am sure we all agree that we have listened to a most in? teresting and, indeed, fascinating lecture from Dr. St. Joseph. It opens up all sorts of vistas for the future. One can see aerial photography extending far beyond these islands, far beyond our own Continent. I can see it over the vast forests of Brazil and all that country of which we know nothing but about which much will be revealed to us. In the same way as the barrows and camps in our small field have been revealed, so the ancient buildings and remains will be revealed, I am convinced, by aerial photography of the forests that lies below the Andes. However that is a development for the future. Meanwhile, I am confident that the Air Ministry is as conscious as we are of this for the moment secondary product of its activities, and I have every confidence that when the war is over we shall be able to call on that Ministry for help in preserving and developing those features which we have had so pleasantly and instructively put before us. I am sure that I speak for you all when I convey our very best thanks to Dr. St. Joseph for his lecture.
Advanced Design Optimization of Switched Reluctance Motors for Torque Improvement Using Supervised Learning Algorithm

Existing research on geometry optimization of switched reluctance motor (SRM) using machine learning algorithms has focused only on the machine’s static characteristics. The dynamic characteristics, however, are critical to improve the SRM performance, particularly at high speeds. This paper introduces an advanced optimization method utilizing a supervised learning algorithm to act as a surrogate model for both static and dynamic characteristics of the SRM. In this work, back-propagation neural network (BPNN) is applied to map out the SRM geometrical parameters, stator and rotor pole arc angles and their dynamic performance metrics such as average torque and torque ripples. To capture the training data, finite element analysis (FEA) and MATLAB Simulink models are implemented to study the static and dynamic characteristics of the considered 6/14 SRM. Levenberg-Marquardt is applied to train the BPNN. The results of the proposed optimal design candidates are verified using FEA and MATLAB simulations, confirming the effectiveness of the optimal design. The optimal design improves the average torque by around 2% and reduces the torque ripples by around 24%. Moreover, the proposed method significantly decreases the computational overhead.
Variation of Wetland Landscape Pattern and Its Ecological Effects in the Green Corridor of the Arid Inland in Northwest China:a Case Study of the Lower Reaches of the Qarqan River

Using "3S" technology,the authors carried out research on the changes of the wetland landscape pattern of the green corridor in the lower reaches of the Qarqan River based on the diversity index,dominance index,fragment index and patch shaped index from 1975 to 2007.Some conclusions have been reached: the wetland area and patch amount increased a little from 1975 to 2000 and decreased greatly from 2000 to 2007.In the past 32 years,the average area of the patch and the patch density have been reduced continuously,and the patch shape turned to complex;the diversity of the landscape pattern decreased,but the dominance and the fragmentation increased;in all the wetland types,the change range of the river wetland area was small,the lake wetland area increased greatly,and the marsh wetland area decreased considerably.The variation of the wetland landscape aggravated the sandy desertification and led to the reduction of biodiversity,but it guaranteed agricultural water demands and ecological water demands,which would be favorable to the stability of the Qarqan River green corridor ecosystem.