Miracle-dz/UniFAR-FTUs huggingface dataset:
A predictability analysis of network traffic

This paper assesses the predictability of network traffic by considering two metrics: (1) how far into the future a traffic rate process can be predicted for a given error constraint; (2) what the minimum prediction error is over a specified prediction time interval. The assessment is based on two stationary traffic models: the auto-regressive moving average (ARMA) model and the Markov-modulated Poisson process (MMPP) model. Our study in this paper provides an upper bound for the optimal performance of online traffic prediction. The analysis reveals that the application of traffic prediction is limited by the quickly deteriorating prediction accuracy with increasing prediction interval. Furthermore, we show that different traffic properties play different roles in predictability. Traffic smoothing (low-pass filtering) and statistical multiplexing also improves predictability. In particular, experimental results suggest that traffic prediction works better for backbone network traffic, or when short-term traffic variations have been properly filtered out. Moreover, this paper illustrates the various factors affecting the effectiveness of traffic prediction in network control. These factors include the traffic characteristics, the traffic measurement intervals, the network control time-scale, and the utilization target of network resources. Considering all of the factors, we present guidelines for utilizing and evaluating traffic prediction in network control areas.
A comparative study on data mining techniques for rainfall prediction in Subang

Rainfall prediction is a challenging problem in the meteorological department around the world due to the accurateness of prediction. This paper studies on data mining techniques to predict rainfall using meteorological data of Subang Weather Station collected from January 2009 to December 2016. The data preparation process involves five weather factors which are maximum temperature, minimum temperature, evaporation, wind speed and cloud with 2922 observations. Predictive Decision Tree model, Artificial Neural Network model and Naive Bayes model are developed for rainfall prediction and comparison. Surprisingly, results show that the performance of Decision Tree model is better as compared to the other predictive models with the misclassification rate of 0.15 and RMSE=0.35. Given enough set of data, rainfall can be predict using the data mining techniques.Rainfall prediction is a challenging problem in the meteorological department around the world due to the accurateness of prediction. This paper studies on data mining techniques to predict rainfall using meteorological data of Subang Weather Station collected from January 2009 to December 2016. The data preparation process involves five weather factors which are maximum temperature, minimum temperature, evaporation, wind speed and cloud with 2922 observations. Predictive Decision Tree model, Artificial Neural Network model and Naive Bayes model are developed for rainfall prediction and comparison. Surprisingly, results show that the performance of Decision Tree model is better as compared to the other predictive models with the misclassification rate of 0.15 and RMSE=0.35. Given enough set of data, rainfall can be predict using the data mining techniques.
A General Framework for Integrating HCLP and PCSP (Poster Abstract)

We present Gocs, a general framework for reasoning about over-constrained systems. It includes HCLP and PCSP as special cases, but also allows the user to beneet from both at the same time. We discuss functions which calculate scores for diierent relaxations of an over-constrained problem, and also discuss pre-orders over these scores. Our framework is compositional. An example is used to illustrate the three theories Gocs, HCLP, and PCSP.
ROOT CAUSE ANALYSIS OF NON PERFORMING FINANCING ON MURABAHAH FINANCING (STUDY OF COSTUMER AT BPRS ADECO KOTA

Purpose – This study aims to identify and describe the factors behind Islamic Banking students Class of 2018 not using Islamic banks in their transaction activities in daily life. Method - This type of research uses field research which is descriptive qualitative in nature. The study uses two data sources, namely primary data and secondary data, as well as data collection techniques through observation, interviews and documentation. Then according to the data analyzed inductively. This research involved students of the Islamic Banking Study Program class of 2018. The number of students of the Islamic banking study program class of 2018 was 285 students. The subjects in this study were 10% of the total number of students of the Islamic banking study program of 29 students Research Results - Based on the results of the study, it can be concluded that the causative factor for Islamic Banking students class of 2018 has not transformed from conventional banks to Islamic banks, namely because people generally carry out transactions at conventional banks because they know more about the existence of conventional banks than Islamic banks and the existence of conventional branches that are close to them. with homes, family and closest relatives still using conventional banks in conducting transactions and not feeling the need for a sharia bank yet, the location of Islamic banks is still very minimal, ATM facilities and branches are still few, and there is trauma to their own experiences or those closest to them due to lack of service from Islamic banks. Limitations – This study has limitations in terms of the relatively small number of research subjects. Practical
Development of a chemoresistant orthotopic human nonsmall cell lung carcinoma model in nude mice

Nonsmall cell lung carcinomas (NSCLCs) are associated with very dismal prognoses, and adjuvant chemotherapy, including irinotecan, taxanes, platin, and vinca alkaloid derivatives, offer patients only slight clinical benefits. Part of the chemoresistance of NSCLC results from the expression in NSCLC cells of a very large set of endogenous proteins, which antagonize chemotherapy‐mediated attacks on these tumor cells.
Explorer Low-Shear Modelled Microgravity Environment Maintains Morphology and Differentiated Functionality of Primary Porcine Hepatocyte Cultures

ity and differentiated functionality, including expression of hepatic integrin (cid:2) 5 , as markers of functional morphology. We report here that in the absence of exogenous biomatrix scaffolding, hepatocytes cultured in serum-free chemically defined medium in a microgravity environment rapidly ( ! 24 h)
CD8+ T Cells Resistant to Costimulatory Blockade Are Controlled by an Antagonist Interleukin-15/Fc Protein

Background. Although permanent engraftment is often achieved with new therapeutics, chronic rejection and graft failure still occur. As the importance of CD8+ T cells in rejection processes has been underlined in various transplant models, and as interleukin (IL)-15 is involved in the activation of CD8+ T cells, we hypothesize that CD8+ T cell “escape” from costimulation blockade might be a IL-15/IL-15R dependent process. Methods. In a murine islet allograft model employing a fully major histocompatibility complex–mismatched strain combination of Balb/c donors to CD4−/− C57BL/6 recipients, a monotherapy with the IL-15 antagonist, IL-15 mutant/Fcγ2a, or the costimulatory blockade molecule, CTLA4/Fc, was used. In addition to monitoring graft survival, infiltration of alloreactive immune cells was analyzed by histology and immunohistochemistry, and alloimmune response of proliferative CD8+ T cells was measured in vivo. Results. Sixty percent of the recipients treated with CTLA4/Fc acutely rejected their islet allograft, comparable to untreated control animals (50% survival). In contrast, the IL-15 antagonist proved to be highly effective, with 100% of recipients accepting their allograft. Immunohistology study demonstrated a remarkable decrease of CD8+ T-cell intragraft infiltration in IL-15 mutant/Fcγ2a treated animals with well-preserved islet architecture and a reduced frequency of proliferating alloreactive CD8+ T cells in comparison with that of untreated and CTLA4/Fc treated groups. Conclusions. In this study, we determined the efficacy and potential therapeutic benefit of the IL-15 antagonist on CD4-independent CD8+ T-cell responses to alloantigens. Targeting the IL-15/IL-15R pathway represents a potent strategy to prevent rejection driven by CD8+ T cells resistant to costimulation blockade.
Comparative Study of Staphylococcus aureus isolates in Pus and Nasal Swabs among patients in Lahore

Staphylococcus aureus predominately found in nasal and pus samples is one of the major causes of skin infections and invasive diseases like endocarditis, pneumonia, and osteomyelitis. The current study was performed over the 3 months period, from April 2022 to June 2022. A total of 368 participants’ nasal and pus swab specimens were included in this study and were collected from the different hospitals in Lahore. The objective of the study was to discern the relative prevalence of Staphylococcus aureus isolates in pus and nasal swabs among patients in Lahore. All the collected samples were cultured in sterile conditions on Blood agar, Chocolate agar, Mannitol salt agar, and MacConkey agar according to the standard laboratory guidelines. S. aureus culture plates were identified based on the colonial morphology after 48hrs. Furthermore, isolated bacteria were characterized based on Gram stain, and differential biochemical analyses like the Catalase test, Coagulase test, Indole test, Motility agar test, Oxidase test, Triple sugar iron and Urease test that was performed to reconfirm S. aureus presence in the given pus and nasal specimens. The modified Kirby Bauer disc diffusion method is a widely used technique for testing the susceptibility of microorganisms to antimicrobial agents. In this method, the zone sizes around the antibiotic
Attitudes of Virginia Dental Hygienists Toward Dental Therapists

ATTITUDES OF VIRGINIA DENTAL HYGIENISTS TOWARD DENTAL THERAPISTS Helene Mesina Burns Old Dominion University, 2020 Director: Prof. Susan Lynn Tolle Problem: The purpose of this study was to determine the opinions and attitudes of Virginia dental hygienists toward dental therapists (DTs) and to determine if current education level and years of practice affected opinions regarding education requirements for DTs. Methods: After IRB approval, a 22-item questionnaire was distributed online to a convenience sample of 910 Virginia dental hygienists. Questions assessed attitudes of participants toward the DT using a seven-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). Additionally, participants were asked to respond to demographic questions and openended questions about potential advantages and/or disadvantages to DTs. Independent sample ttests and chi-square analysis was used to analyze results. Results: An overall response rate of 22% was obtained (n=200). Most respondents agreed a DT was needed in Virginia (M=5.78, P<0.001) and supported that dental therapy could be a solution to the problem of access to care issues in Virginia (M=5.97, P<0.001). Similarly, most respondents agreed they had an understanding of the services performed by DTs (M=5.90, P<0.001) and agreed there was evidence DTs could perform high-quality work (M=5.75, P<0.001). While most hygienists agreed it was important for Virginia to adopt legislation for a dental therapy model (M=5.89, P<0.001), most disagreed that DTs’ practice should be restricted to acknowledged underserved areas in Virginia (M=3.19, P<0.001). No significant association was found between years of practice and opinions toward education requirements for DTs; however, a significant association was found between current education level and opinions toward education requirements for DTs (Fisher’s Exact Test=34.17, df=9, P=.000, Cramer’s V=.28). Thirty-three percent of respondents with associate degrees supported an associate degree as the appropriate degree requirement for DTs, compared to only 3% of all other degree holders. Conclusions: Results revealed Virginia dental hygienists had overwhelmingly positive attitudes toward DTs. Research with a larger sample could provide more insight into opinions of the Virginia dental hygienist population.
Decreased α-Methylacyl CoA Racemase Expression in Localized Prostate Cancer is Associated with an Increased Rate of Biochemical Recurrence and Cancer-Specific Death

α-Methylacyl CoA racemase (AMACR) is overexpressed in prostate cancer relative to benign prostatic tissue. AMACR expression is highest in localized prostate cancer and decreases in metastatic prostate cancer. Herein, we explored the use of AMACR as a biomarker for aggressive prostate cancer. AMACR protein expression was determined by immunohistochemistry using an image analysis system on two localized prostate cancer cohorts consisting of 204 men treated by radical prostatectomy and 188 men followed expectantly. The end points for the cohorts were time to prostate-specific antigen (PSA) failure (i.e., elevation >0.2 ng/mL) and time to prostate cancer death in the watchful waiting cohort. Using a regression tree method, optimal AMACR protein expression cutpoints were determined to best differentiate prostate cancer outcome in each of the cohorts separately. Cox proportional hazard models were then employed to examine the effect of the AMACR cutpoint on prostate cancer outcome, and adjusted for clinical variables. Lower AMACR tissue expression was associated with worse prostate cancer outcome, independent of clinical variables (hazard ratio, 3.7 for PSA failure; P = 0.018; hazard ratio, 4.1 for prostate cancer death, P = 0.0006). Among those with both low AMACR expression and high Gleason score, the risk of prostate cancer death was 18-fold higher (P = 0.006). The AMACR cutpoint developed using prostate cancer–specific death as the end point predicted PSA failures independent of Gleason score, PSA, and margin status. This is the first study to show that AMACR expression is significantly associated with prostate cancer progression and suggests that not all surrogate end points may be optimal to define biomarkers of aggressive prostate cancer.
Capturing Intracellular pH Dynamics by Coupling Its Molecular Mechanisms within a Fully Tractable Mathematical Model

We describe the construction of a fully tractable mathematical model for intracellular pH. This work is based on coupling the kinetic equations depicting the molecular mechanisms for pumps, transporters and chemical reactions, which determine this parameter in eukaryotic cells. Thus, our system also calculates the membrane potential and the cytosolic ionic composition. Such a model required the development of a novel algebraic method that couples differential equations for slow relaxation processes to steady-state equations for fast chemical reactions. Compared to classical heuristic approaches based on fitted curves and ad hoc constants, this yields significant improvements. This model is mathematically self-consistent and allows for the first time to establish analytical solutions for steady-state pH and a reduced differential equation for pH regulation. Because of its modular structure, it can integrate any additional mechanism that will directly or indirectly affect pH. In addition, it provides mathematical clarifications for widely observed biological phenomena such as overshooting in regulatory loops. Finally, instead of including a limited set of experimental results to fit our model, we show examples of numerical calculations that are extremely consistent with the wide body of intracellular pH experimental measurements gathered by different groups in many different cellular systems.
Noise, Information and the Favorite-Longshot Bias

According to the favorite-longshot bias, longshots are overbet relative to favorites. We propose an explanation for this bias (and its reverse) based on an equilibrium model of informed betting in parimutuel markets. The bias arises because bettors take positions without knowing the positions simultaneously taken by other privately informed bettors. The direction and the extent of the bias depend on the amount of private information relative to noise present in the market. With realistic ex-post noise and ex-ante asymmetries, our model replicates the main qualitative features of expected returns observed in horse races.
Cannabinoid WIN-55,212-2 mesylate inhibits ADAMTS-4 activity in human osteoarthritic articular chondrocytes by inhibiting expression of syndecan-1

A central feature of osteoarthritis (OA) is the loss of articular cartilage, which is primarily attributed to cartilage breakdown. A group of metalloproteinases termed the A disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS) family are reported to be important in cartilage breakdown. Recent studies have suggested that ADAMTS-4 is a major contributor to the pathogenesis of OA and that syndecan-1 is closely associated with activation of ADAMTS-4 in human chondrocytes. Accumulating evidence also suggests that cannabinoids have chondroprotective effects. The current study explored the effects of synthetic cannabinoid WIN-55,212-2 mesylate (WIN-55) on the expression of syndecan-1 and ADAMTS-4, as well as ADAMTS-4 activity, in unstimulated and interleukin (IL)-1β-stimulated OA chondrocytes. Primary human OA articular chondrocytes were treated with WIN-55 in the presence or absence of IL-1β and cannabinoid receptor antagonists. The results of the present study demonstrated that WIN-55 inhibited ADAMTS-4 activity in unstimulated and IL-1β-stimulated primary human OA articular chondrocytes in a concentration-dependent manner. Cannabinoid receptor type 1 (CB1) and 2 (CB2) were constitutively expressed in human OA articular chondrocytes. Furthermore, selective CB2 antagonist, JTE907, but not selective CB1 antagonist, MJ15, abolished the inhibitory effect of WIN-55 on ADAMTS-4 activity. WIN55 inhibited the expression of syndecan-1 but not ADAMTS-4, and overexpression of syndecan-1 reversed the inhibitory effect of WIN-55 on the ADAMTS-4 activity in unstimulated and IL-1β-stimulated human OA articular chondrocytes. Despite having no significant effect on syndecan-1 gene promoter activity, WIN-55 markedly decreased the stability of syndecan-1 mRNA via CB2. In conclusion, to the best of our knowledge, the present study provides the first in vitro evidence supporting that the synthetic cannabinoid WIN-55 inhibits ADAMTS-4 activity in unstimulated and IL-1β-stimulated human OA articular chondrocytes by decreasing the mRNA stability/expression of syndecan-1 via CB2. This suggests a novel mechanism by which cannabinoids may prevent cartilage breakdown in OA. In addition, it also provides novel insights into the pharmacological effects of synthetic cannabinoids on OA.
Achieving Real-Time Target Tracking UsingWireless Sensor Networks

Target tracking systems, consisting of thousands of low-cost sensor nodes, have been used in many application domains such as battlefield surveillance, wildlife monitoring and border security. These applications need to meet certain real-time constraints in response to transient events, such as fast-moving targets. While the real-time performance is a major concern in these applications, it should be compatible with other important system properties such as energy consumption and accuracy. Hence, it is desirable to have the ability to exploit the tradeoffs among them. This work presents the real-time design and analysis of VigilNet, a large-scale sensor network system which tracks, detects and classifies targets in a timely and energy efficient manner. Based on a deadline partition method and theoretical derivations of each sub-deadline, we are able to make guided engineering decisions to meet the end-to-end tracking deadline. To confirm our design and obtain an empirical understanding of these tradeoffs, we invest significant efforts to perform large-scale simulations with 10,000 nodes as well as a field test with 200 XSM motes, running VigilNet. The results from both analysis and evaluation can serve as general design guidelines to build similar real-time systems.
Um arcabouc¸o de Selec¸˜ao de Bandas Landsat-8 baseado em UMDA para Detecc¸˜ao de Desmatamento

—The conservation of tropical forests is a current subject of social and ecological relevance due to their crucial role in the global ecosystem. Unfortunately, millions of hectares are deforested and degraded each year. Therefore, government or private initiatives are needed for monitoring tropical forests. In this sense, this work proposes a novel framework, which uses of distribution estimation algorithm (UMDA) to select spectral bands from Landsat-8 that yield a better representation of deforestation areas to guide a semantic segmentation architecture called DeepLabv3+. In performed experiments, it was possible to find several compositions that reach balanced accuracy superior to 90% in segment classification tasks. Furthermore, the best composition ( 651 ) found by UMDA algorithm fed the DeepLabv3+ architecture and surpassed in efficiency and effectiveness all compositions compared in this work.
Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm

Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). The major function of the IBA is to optimize the estimated value of the three-parameters associated with the Muskingum model. The IBA acts based on the chaos search tool, which mainly enhances the uniformity and erogidicty of the population. In addition, the current research, unlike the other existing models which consider flood routing, is based on dividing one reach to a few intervals to increase the accuracy of flood routing models. Three case studies with lateral flow were considered for this study, including the Wilson flood, Karahan flood, and Myanmar flood. Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. The results for the Wilson flood showed that the proposed model could reduce the Sum of Squared Deviations (SSD) value by 89%, 51%, 93%, 69%, and 88%, compared to the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Pattern Search (PS) algorithm, Harmony Search (HS) algorithm, and Honey Bee Mating Optimization (HBMO), respectively. In addition, increasing the number of intervals for flood routing significantly improved the accuracy of the results. The results indicated that the Sum of Absolute Deviations (SAD) using IBA for the Karahan flood was 117, which had reduced by 83%, 88%, 94%, and 12%, compared to the PSO, GA, HS, and BA, respectively. Furthermore, the achieved results for the Myanmar flood showed that SSD for IBA relative to GA, BA, and PSO was reduced by 32%, 11%, and 42%, respectively. In conclusion, the proposed Muskingum Model integrated with IBA considering the existence of lateral flow, outperformed the existing applied simple Muskingum models in previous studies. In addition, the more the number of intervals used in the model, the better the accuracy of flood routing prediction achieved.