Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of physicochemical and organoleptic properties of wild tea (Camellia sinensis) compared to selected commercially grown tea cultivars in Sri Lanka

“Ceylon tea”, has a special place as one of the best quality tea among the tea drinkers worldwide. However, Sri Lankan tea industry is facing some challenges associated with lower productivity and increasing cost of production. Therefore, higher price should be gained through value addition and product differentiation. Production of wild tea is one such strategy associated with higher demand in niche markets. An experiment was conducted to evaluate qualities of wild tea with compared to commercially cultivated tea and free growing cultivar in the Low Country region in Sri Lanka. Wild tea, free growing cultivar (TRI 2025), two commercial cultivars from the Tea Research Station in Rathnapura (TRI 4049 and TRI 2023) and one cultivar from a commercial grower (TRI 2023) were used for evaluation. Phytochemical investigation was carried out on methanol crude extracts of the made tea leaves. The made tea samples were subjected to organoleptic evaluation to determine its quality and preference. Significantly highest total phenolic content, total flavonoid content and the highest ABTS+ free radical scavenging activities were recorded in wild tea than other commercial cultivars. Organoleptic qualities such as colour, aroma, taste, strength and overall acceptability were favorably higher in wild tea, over the other commercial cultivars.
ILCR: Item-based Latent Factors for Sparse Collaborative Retrieval

Interactions between search and recommendation have recently attracted significant attention, and several studies have shown that many potential applications involve with a joint problem of producing recommendations to users with respect to a given query, termed $Collaborative$ $Retrieval$ (CR). Successful algorithms designed for CR should be potentially flexible at dealing with the sparsity challenges since the setup of collaborative retrieval associates with a given $query$ $\times$ $user$ $\times$ $item$ tensor instead of traditional $user$ $\times$ $item$ matrix. Recently, several works are proposed to study CR task from users' perspective. In this paper, we aim to sufficiently explore the sophisticated relationship of each $query$ $\times$ $user$ $\times$ $item$ triple from items' perspective. By integrating item-based collaborative information for this joint task, we present an alternative factorized model that could better evaluate the ranks of those items with sparse information for the given query-user pair. In addition, we suggest to employ a recently proposed scalable ranking learning algorithm, namely BPR, to optimize the state-of-the-art approach, $Latent$ $Collaborative$ $Retrieval$ model, instead of the original learning algorithm. The experimental results on two real-world datasets, (i.e. \emph{this http URL}, \emph{Yelp}), demonstrate the efficiency and effectiveness of our proposed approach.
SoundButton: design of a low power wearable audio classification system

The paper deals with the design of a sound recognitionsystem focused on an ultra low power hardware implementationin a button like miniature form factor. We present theresults of the first design phase focused on selection andexperimental evaluation of sound classes and algorithmssuitable for low power realization. We also present theVHDL model of the hardware showing that our method canbe implemented with minimal resources. Our approach isbased on spectrum analysis to distinguish between a subsetof sound sources with a clear audio signature. It alsouses intensity analysis from microphones placed at differentlocations to correlate the sounds with user activity.
ARTOS : System Model and Optimization Algorithm Technical Report

The ARTOS research project at the University of Ulm explores the runtime administration of concurrent soft real-time applications. Available resources need to be assigned to applications, taking into account their priorities and utility. The applications support different modes with associated resource requirements. Higher modes reflect better quality of the outcome. An algorithm using a dynamic programming approach was designed to find the optimal solution to the problem of assigning resources to applications while achieving the highest possible utility. The algorithm was implemented in Java and in C as part of our preliminary work. Its evaluation shows which factors have the most pronounced impact on the performance of the optimization. It is investigated to which extent — regarding varying the numbers of applications and their modes, as well as the available resource limits — the algorithm is suitable for deployment in real-time systems.
A Distributed and Hierarchical Government Organization Model in Inter-organizational Business Integration

Nowadays, while the modeling of business processes and workflows in inter-organizational business integration is well researched, the relationship between the organizational elements and process activities is not clear, which is the essential reason why the current business integration model is not suitable for real complex operation environment. Consequently, organization modeling is very important to the design and application of inter-organizational business integration. In view of the description requirement of organization model in E-Government inter-organizational business integration, a meta- organization model is promoted, which is oriented to the government on the analyzing of the features of government inter-organizational business process integration. Based on the constructed organization meta-model, a distributed and hierarchical government organization model is designed using the technique of LDAP. Inter-organizational communication protocol and standard accessing rules are designed to guarantee flexible collaboration between organizations.
A Laboratory Experimental Study on Enhancing the Oil Recovery Mechanisms of Polymeric Surfactants

In order to evaluate the physical and chemical properties of polymer surfactants and analyze their oil displacement mechanisms, three types of poly-surfactant used in the Daqing oil field were chosen to be researched, and the oil displacement effects were studied using poly-surfactants of different viscosity, dehydrating rate, and core permeability. The main purpose is to determine the reasonable range of different characteristic indexes of polymeric surfactant flooding. The oil displacement effect of 15 cores was analyzed, and the effects of viscosity, the dehydrating rate of emulsion, and permeability on EOR (Enhanced Oil Recovery) were analyzed. The oil displacement mechanisms of polymeric surfactants were researched using a photolithographic glass core. This paper explores the mechanism underlying production enhancement as an EOR target, while simultaneously conducting laboratory tests to assess the physical and chemical properties of polymeric surfactants. The poly-surfactant agents exhibit a notable increase in viscosity, with the optimal displacement effect observed at a core effective permeability exceeding 400 mD, resulting in a potential EOR of 15% or higher. Moreover, at a viscosity ranging between 40 and 70 mPa·s, the total EOR can reach 73%, with the peak efficiency occurring at a viscosity of 60 mPa·s. The water loss rate of the emulsion, ranging between 30% and 70%, achieves optimal performance at 50%. The poly-surfactants’ higher viscosity extends the oil sweep area, enhancing recovery efficiency, and noticeably reducing residual oil compared to water flooding. During poly-surfactant flooding, a substantial amount of residual oil is extracted and transformed into droplets. The rapid emulsification of the polymeric surfactant solution with crude oil forms a stable emulsion, contributing to its significant oil recovery effect. This research provides valuable technical support for EOR in thin and low-quality reservoirs of onshore multi-layered sandstone reservoirs.
Development of partial-discharge-emulator for smart grid monitoring system

Development of subsystems like PD emulators is an approach to operation optimization and real-time condition monitoring in future smart grid. This paper illustrates the method of PD locating based on the technique of VHF based emulator development. A partial discharge emulator consists of a spark plug and miniature electric fence circuit is developed. The system was tested by using a PD source in air to evaluate the sensitivity and the impulse behavior in correlation to the conventional measurement technique. Here the VHF method can be considered for PD detection which takes advantage of the fact that discharges emanating from the spark plug produce electromagnetic waves with frequencies that extend well into the VHF range (100 to 300 MHz). A simpler and low cost square law detector for partial discharge detection has also been developed and tested. The paper describes a novel method of radio frequency partial discharge detection method by using a simpler and low cost square law detector in radio frequency range.
Mutually reinforcing systems

This paper demonstrates strategies for designing mobile games with by-products in order to allow the acquisition of specific data. A mobile game with by-products called EyeSpy and a photo website called Realise will be used as examples to demonstrate these strategies. The Realise website allows users to browse geographically tagged photos and make specific requests for new ones. In the EyeSpy game, players use mobile phones to tag geographic positions with photos and text. EyeSpy players can earn points from validating each others' tags by visiting tag locations and attempting to 'confirm' them. If players go to the correct location, both the player confirming the tag and the player who created it will gain points. This creates game content for EyeSpy and provides more refined results for the Realise website. In this way, both the systems mutually reinforce each other.
Psychometric properties of the SF-36 in the early post-stroke phase.

BACKGROUND Patients who have had a stroke are a large group in whom long-term disability is common and therefore impaired general health is likely. The Short Form 36 (SF-36) is a popular measure of general health that has been used with this patient group, but not all aspects of its psychometric properties have been established for use in this context, and its use in the early post-stroke phase has been neglected. AIMS To examine the reliability, validity and sensitivity to change of the SF-36 (UK version I) in patients in the early post-stroke period. DESIGN A prospective, observational study of stroke outcomes was carried out. RESEARCH METHODS From May 1996 to April 1997, patients who had had a stroke were identified by 24 general practices in Scotland and were recruited within 1 month of their stroke, whether in hospital or at home. Outcome measures including the SF-36 were administered at one, 3 and 6 months after onset. RESULTS The internal consistency of the eight subscales at all three time-points was good except for 1 month Vitality (alpha = 0.6824) and 3 month General Health (alpha = 0.6650), which were borderline in comparison with the criterion value of 0.7. Construct validity was adequate overall, although correlations between Role Physical and General Health and the Barthel Index and Canadian Neurological Scale were lower than hypothesized. Most SF-36 subscales were sensitive to change between 1 and 3 months post-stroke, but none detected change between 3 and 6 months. CONCLUSIONS There were some practical problems in using the SF-36 in an acutely unwell stroke population. However, analysis of psychometric properties suggested that most of the subscales were adequately reliable and valid. Sensitivity to change was poorer in the later stages of the study.
Inducing Word and Part-of-Speech with Pitman-Yor Hidden Semi-Markov Models

We propose a nonparametric Bayesian model for joint unsupervised word segmentation and part-of-speech tagging from raw strings. Extending a previous model for word segmentation, our model is called a Pitman-Yor Hidden SemiMarkov Model (PYHSMM) and considered as a method to build a class n-gram language model directly from strings, while integrating character and word level information. Experimental results on standard datasets on Japanese, Chinese and Thai revealed it outperforms previous results to yield the state-of-the-art accuracies. This model will also serve to analyze a structure of a language whose words are not identified a priori.
Sensitivity of output performance measures to input distribution shape in modeling queues.3. Real data scenario

This paper follows-on papers presented at the two previous WSC conferences on sensitivity of output measures to input distribution selection in queueing modeling. Here, a real situation is studied, where data on input distributions are utilized and distributions selected by two fitting packages, Arena Input Analyzer and ExpertFit. Empirical distributions made from histograms of the raw data itself, as well as the first two choices from Arena and ExpertFit are compared for this small bank queueing network model, showing that an output measure such as mean wait in queue is quite sensitive to input distribution choice.
Structured Self-Monitoring of Blood Glucose Significantly Reduces A1C Levels in Poorly Controlled, Noninsulin-Treated Type 2 Diabetes

OBJECTIVE To assess the effectiveness of structured blood glucose testing in poorly controlled, noninsulin-treated type 2 diabetes. RESEARCH DESIGN AND METHODS This 12-month, prospective, cluster-randomized, multicenter study recruited 483 poorly controlled (A1C ≥7.5%), insulin-naïve type 2 diabetic subjects from 34 primary care practices in the U.S. Practices were randomized to an active control group (ACG) with enhanced usual care or a structured testing group (STG) with enhanced usual care and at least quarterly use of structured self-monitoring of blood glucose (SMBG). STG patients and physicians were trained to use a paper tool to collect/interpret 7-point glucose profiles over 3 consecutive days. The primary end point was A1C level measured at 12 months. RESULTS The 12-month intent-to-treat analysis (ACG, n = 227; STG, n = 256) showed significantly greater reductions in mean (SE) A1C in the STG compared with the ACG: −1.2% (0.09) vs. −0.9% (0.10); Δ = −0.3%; P = 0.04. Per protocol analysis (ACG, n = 161; STG, n = 130) showed even greater mean (SE) A1C reductions in the STG compared with the ACG: −1.3% (0.11) vs. −0.8% (0.11); Δ = −0.5%; P < 0.003. Significantly more STG patients received a treatment change recommendation at the month 1 visit compared with ACG patients, regardless of the patient’s initial baseline A1C level: 179 (75.5%) vs. 61 (28.0%); <0.0001. Both STG and ACG patients displayed significant (P < 0.0001) improvements in general well-being (GWB). CONCLUSIONS Appropriate use of structured SMBG significantly improves glycemic control and facilitates more timely/aggressive treatment changes in noninsulin-treated type 2 diabetes without decreasing GWB.
Economic Evaluation of Active Implementation versus Guideline Dissemination for Evidence-Based Care of Acute Low-Back Pain in a General Practice Setting

Introduction The development and publication of clinical practice guidelines for acute low-back pain has resulted in evidence-based recommendations that have the potential to improve the quality and safety of care for acute low-back pain. Development and dissemination of guidelines may not, however, be sufficient to produce improvements in clinical practice; further investment in active implementation of guideline recommendations may be required. Further research is required to quantify the trade-off between the additional upfront cost of active implementation of guideline recommendations for low-back pain and any resulting improvements in clinical practice. Methods Cost-effectiveness analysis alongside the IMPLEMENT trial from a health sector perspective to compare active implementation of guideline recommendations via the IMPLEMENT intervention (plus standard dissemination) against standard dissemination alone. Results The base-case analysis suggests that delivery of the IMPLEMENT intervention dominates standard dissemination (less costly and more effective), yielding savings of $135 per x-ray referral avoided (-$462.93/3.43). However, confidence intervals around point estimates for the primary outcome suggest that – irrespective of willingness to pay (WTP) – we cannot be at least 95% confident that the IMPLEMENT intervention differs in value from standard dissemination. Conclusions Our findings demonstrate that moving beyond development and dissemination to active implementation entails a significant additional upfront investment that may not be offset by health gains and/or reductions in health service utilization of sufficient magnitude to render active implementation cost-effective.
An Exploration of Determinants of Anemia in Pregnant Women at Buakayu Community Health Center Tana Toraja Regency

Introduction: Anemia on pregnant women is a global health problem that has serious impacts on the mother and fetus. The objective of the study was to explore the determinants of anemia on pregnant women at Buakayu Community Health Center, Tana Toraja Regency. Methods: The study used an observational study with a cross-sectional design. The sample was pregnant women who visited the Buakayu Community Health Center for antenatal examination using an accidental sampling technique for 11 days. The data was collected through structured interviews and laboratory examinations. Data analysis was carried out using descriptive statistical methods (univariate), bivariate, and regression analysis to determine the variables most related to independent variables and anemia in pregnant women. Results: The results of the study showed that diet (p=0.001), dietary restrictions (p=0.005), consumption of Fe tablets (p=0.000), and provision of additional food (p=0.000) were related to anemia incidence on pregnant women. Conclusion: It can be concluded that diet, dietary restrictions, consumption of Fe tablets, and provision of additional food are factors that contribute to anemia incidence on pregnant women at the Buakayu Community Health Center area. It is hoped that the implications of the study can be used as a basis for designing appropriate interventions in dealing with anemia on pregnant women at the Health Center level.
Multi-Task Learning: Multiple Kernels for Multiple Tasks

Many kernel based methods for multi-task learning have been proposed, which leverage relations among tasks to enhance the overall learning accuracies. Most of the methods assume that the learning tasks share the same kernel [e.g., 13], which could limit their applications because in practice different tasks may need different kernels. In this paper, we consider utilizing multiple kernels for multiple tasks. The main challenge of introducing multiple kernels into multiple tasks is that functions from different Reproducing Kernel Hilbert Spaces (RKHSs) are not comparable, making it difficult to exploit relations among tasks. This paper addresses the challenge by defining the problem in the Square Integrable Space (SIS). Specially, it proposes a kernel based method which makes use of a regularization term defined in the SIS to represent task relations. We prove a new representer theorem for the proposed approach in SIS. We further derive a practical method for solving the learning problem and conduct consistency analysis of the method. We discuss the relations between our method and the existing method by showing the inequality relation between the two regularization terms in the two methods. We also give an SVM based implementation of our method for multi-label classification. Experiments on an artificial example and three real-world data sets show significant improvements of the proposed method over existing methods.
Comparison of effects of 3 and 7% hypertonic saline nebulization on lung function in children with cystic fibrosis: a double-blind randomized, controlled trial.

BACKGROUND Beneficial effects of hypertonic saline on lung function in cystic fibrosis patients are well documented. However, the effects of various concentrations of hypertonic saline are not well studied. We, therefore, compared the effects of 3 and 7% hypertonic saline administered by nebulization on lung function in children with cystic fibrosis. METHOD In a double-blind randomized controlled trial, 31 children with cystic fibrosis were randomized to receive either 3% saline or 7% saline nebulization twice daily for 28 days. Spirometry was performed and functional status was measured on Day 14 and 28. RESULTS Of 31 children enrolled in the study, 30 completed the 28 days follow up (15 in each group). Percentage change in Forced Expiratory Volume during first second (FEV(1)) from baseline to Day 14 and on Day 28 was significantly higher in the group receiving 3% saline as compared with those receiving 7% saline inhalation. There was some decrease in FEV(1) (percentage predicted) immediately after 7% saline inhalation unlike 3% saline. The functional status remained comparable between the two groups. CONCLUSION The results suggest that 3% hypertonic saline nebulization was better than 7% saline inhalation. There is a need for studies with larger sample size and longer duration to confirm our results.
Vector and parallel algorithms for Cholesky factorization on IBM 3090

In many engineering applications, a solution of Fx = b is required, where F is a positive definite symmetric matrix. This is usually done by the Cholesky factorization, F = RRT, where R is the lower triangular Cholesky factor. This is a compute intensive problem. However, in order to achieve the best possible performance on IBM 3090 Vector Facility, the problem requires blocking at various levels to match 3090 memory hierarchy. A large problem which does not fit in a particular level of memory is blocked so that each block fits in memory. This minimizes data transfers between various levels of memory. In this paper, various blocking schemes are described for vector and parallel implementation on 3090 VF. Some of these algorithms have been included in the Engineering and Scientific Subroutine Library (ESSL). Performance numbers are also included. These algorithms achieve close to the peak performance of the 3090 uniprocessor and multiprocessors.
Network Kriging

Network service providers and customers are often concerned with aggregate performance measures that span multiple network paths. Unfortunately, forming such network-wide measures can be difficult, due to the issues of scale involved. In particular, the number of paths grows too rapidly with the number of endpoints to make exhaustive measurement practical. As a result, it is of interest to explore the feasibility of methods that dramatically reduce the number of paths measured in such situations, while maintaining acceptable accuracy. We cast the problem as one of statistical prediction-in the spirit of the so-called "kriging" problem in spatial statistics-and show that end-to-end network properties may be accurately predicted in many cases using a surprisingly small set of carefully chosen paths. More precisely, we formulate a general framework for the prediction problem, propose a class of linear predictors for standard quantities of interest (e.g., averages, totals, and differences) and show that linear algebraic methods of subset selection may be used to effectively choose which paths to measure. We characterize the performance of the resulting methods, both analytically and numerically. The success of our methods derives from the low effective rank of routing matrices as encountered in practice, which appears to be a new observation in its own right with potentially broad implications on network measurement generally