Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of body composition measures on chyle leak after oesophagectomy

Background Chyle leak (CL) is an infrequent but potentially serious complication of oesophagectomy. Sarcopenia is an increasingly recognised prognostic factor in oesophageal cancer surgery. The aim of this study was to identify the influence of body composition measures on CL following oesophagectomy. Methods Patients who developed CL after oesophagectomy between January 2006–December 2020 were identified retrospectively from a prospectively maintained dataset. A control group of patients undergoing oesophagectomy, who did not experience chyle leak during the same time period, was also collected. Relationships between CL and demographics, operative factors and body composition measures were investigated as primary outcomes. Risk factors for severe CL were evaluated as a secondary outcome. Results There were 26 patients who developed a CL following an oesophagectomy. On univariate analysis, preoperative body mass index (BMI) (P=0.001), subcutaneous fat index (P=0.001) and total fat index (P=0.004) were significantly associated with CL. On multivariate analysis, a lower preoperative subcutaneous fat index was a significant independent predictor of CL (P=0.003). Sarcopenia, as an overall measure, was not found to be a significant predictor of developing CLs. No significant predictors of severe CL were identified. Conclusions A reduced preoperative BMI and body fat composition are risk factors for CL after oesophagectomy. Sarcopenia does not predict either the occurrence or severity of CL. This presents potentially modifiable risk factors for CL after oesophagectomy and emphasises the importance of physiological and nutritional optimisation before oesophagectomy.
A micropower analogue front end for wireless ECG system

ABSTRACT Recently, the growing demand of low power, low noise and miniaturised size for biopotential integrated front end have drawn a lot of research interests. This paper proposed an analogue front end for wireless ECG system. It consists of a capacitively coupled chopper instrumentation amplifier (CCIA), chopper spike filter (CSF), band-pass filter and clock generator. 1/f noise and offset of the first stage are filtered by the chopping technology. The spikes generated by the input chopper of CCIA are filtered by the CSF. The band-pass filter sets the bandwidth of the front end. The front end was implemented in a 0.13-m complementary metal-oxide-semiconductor process. It achieves 46.3 dB gain, 100 dB common mode rejection ratio and 5 A current consumption. Meanwhile, other state-of-the-art performances in terms of input common mode, dc-electrode offset and noise were also achieved with a chip area of 0.075 mm2. The results prove that the chip has the possibility to apply into the wireless ECG system for long-term homecare.
Total technology practice : preliminary study for application in New Zealand schools : a thesis presented in partial fulfilment of the requirements for the degree of Master of Philosophy in Technology, at Massey University

The purpose of this research was to identify the important generic elements of total technology practice and to develop a preliminary list of the important techniques, knowledge and actions used by technologists. The research was based on the hypothesis that in technology education in New Zealand schools, the important elements of technology practice could be represented in the form of a model that could be used to organise and communicate the elements and knowledge involved in total technology practice. The research was undertaken with technologists working at Massey University and teachers involved in teaching technology. A product development research methodology was used to test ideas and develop a model of technology practice for use in New Zealand schools. The first phase of the research used the experience and knowledge of product development technologists to identify the important elements of technology practice and develop preliminary lists of techniques and knowledge involved in each element. A group of specialist technologists were used to verify these elements and identify detailed content. This research showed that total technology practice can be structured using seven elements that together provide a simplified description of total technology practice. The elements of practice associated with the human context and goal of technology practice were identified as society, the work environment, and purposeful action. The elements technologists bring to the context were organisation, information, resource use, and an extensive knowledge of techniques and the skill, ingenuity and experience to apply and adapt techniques to specific contexts and problems. Individual technologists were interviewed to identify the important practices and knowledge within their area of expertise. Technological knowledge was structured into a framework that reflected the way technologists broke complex systems into subsystems to solve problems and develop solutions.
Mechanobiology: Exploitation for Medical Benefit

An emerging field at the interface of biology and engineering, mechanobiology explores the mechanisms by which cells sense and respond to mechanical signals—and holds great promise in one day unravelling the mysteries of cellular and extracellular matrix mechanics to cure a broad range of diseases. Mechanobiology: Exploitation for Medical Benefit presents a comprehensive overview of principles of mechanobiology, highlighting the extent to which biological tissues are exposed to the mechanical environment, demonstrating the importance of the mechanical environment in living systems, and critically reviewing the latest experimental procedures in this emerging field.
Docking and Molecular Dynamics Simulations Reveal A Possible Site of Interaction of Olive Leaf Extract Hydroxytyrosol with Polyunsaturated Fatty Acid 5-Lipoxygenase Human Enzyme

The polyphenol hydroxytyrosol (HT), a molecule easily extracted from olive oil production waste, has well known antioxidant and anti-inflammatory properties. In literature various bioassays points to a clear inhibitory effects on the polyunsaturated fatty acid 5-lipoxygenase enzyme (LOX5) which is a current target for pharmaceutical intervention for various inflammatory diseases. We have investigated the hypothesis of direct interaction of HT with LOX5 through blind docking and a 200 nanoseconds long molecular dynamics. Analysis of the results highlights the stability of the interaction of HT in the putative binding site with LOX5. This is in accord with the hypothesis of an allosteric way of action of HT to inhibit the activity of the LOX5 also suggesting the use of HT structure as a scaffold to design LOX5 inhibitors with improved activity and specificity.
Development of Parametric Power Generation and Distribution Subsystem Models at the Conceptual Aircraft Design Stage

The ongoing eﬀorts to reduce aviation related greenhouse gas emissions and fuel burn have led to advancements in power generation and distribution (PG&D) subsystem technology. Due to the absence of historical data, PG&D subsystem models must be created from ﬁrst-order analysis without compromising crucial information on their characteristics. This paper demonstrates the development of parametric, physics-based subsystem models such as battery, electric motor, power distribution and management system, and propeller speed reduction unit for rapid and low-cost sizing, simulation and analysis at early design stages. A special focus was put on rechargeable battery technology and implementing a dynamic (rather than steady-state) discharge behavior into the propulsion architecture. A methodology to integrate the developed subsystem models was presented. A sample application was also provided to demonstrate the combined capabilities of the models. To this end, the models were applied within a sample parallel hybrid electric architecture using Dornier 328 as a test bed. The subsystem behaviors under varying power requirements were then analyzed. Finally, the importance of having more dimensionality at the subsystem level at early design stages was highlighted by comparing the results of two diﬀerent architectural choices.
Light weight gypsum-based material manufactured by expanding process with aluminum powder

The paper presents the preparing method of a light weight gypsum-based material. The raw material foaming principle is applied to the manufacture of aerated autoclavized concrete by hydrogen release in the material mass by the corrosion reaction of aluminum powder in aqueous solution of Ca(OH) 2 . The work originality is the generation method of powder aluminum by microwave melting of metal waste and melt atomization by concentrated nitrogen jets. The product has density between 530-600 kg/m 3 and compressive strength between 1.2-2.2 MPa, being similar to aerated autoclaved concrete, with identical application fields, but low energy costs.
Research Needs for and Barriers to Use of Treadmill Workstations

Although laboratory studies demonstrate increases in energy expenditure with the use of treadmill workstations, effectiveness and efficiency studies demonstrating improved energy expenditure in real workplaces have yet to build the evidence to support use of such workstations. Psychosocial barriers to using treadmill workstations are related to communication (noise and hierarchy), need for motivation, peer pressure, and adaptation that might affect performance. Answers to questions such as whether the institution is willing to pay more to acquire very-low-noise devices, whether it is able to tolerate low use of treadmills, and whether vendors exist with no-hassle return policies may help in properly implementing treadmill workstations.
One-step single-tube accelerated quantitative nucleoprotein gene-specific reverse transcription loop-mediated isothermal gene amplification (RT-LAMP) assay for rapid, real-time & reliable clinical detection of Ebola virus.

Background & objectives : Due to the absence of specific drugs or vaccines for Ebola virus disease, rapid, sensitive and reliable diagnostic methods are required to control the transmission chain of the disease and for better patient management. Isothermal amplification of nucleic acids has emerged as a promising alternative in which rapid and efficient amplification is achieved at a constant temperature without the thermal cycling required in PCR. Methods : A one-step single-tube accelerated quantitative reverse trascription loop-mediated isothermal amplification (RT-LAMP) assay was developed by targeting the NP gene of 2014 Zaire Ebola virus (ZEBOV). The RT-LAMP assay was found to be specific for ZEBOV, without having any cross-reactivity with related haemorrhagic fever viral agents. Results : The comparative evaluation of Ebola virus NP gene-specific RT-LAMP assay with reverse transcription (RT) - PCR and TaqMan real-time RT-PCR demonstrated that RT-LAMP was 10-1000 folds more sensitive than TaqMan real-time RT-PCR and conventional RT-PCR, respectively, with a detection limit of 1 copy number. In the absence of real-world clinical samples, the feasibility of Ebola virus RT-LAMP assay for clinical diagnosis was evaluated with different body fluids including serum, urine, saliva, semen and stool samples from healthy human volunteers spiked with gamma-irradiated ZEBOV 2014 obtained from Robert Koch Institute, Berlin, Germany, through the European Network for Diagnostics of Imported Viral Diseases. The Ebola virus RT-LAMP assay could correctly be picked up the spiked samples up to 1 copy of viral RNA without having any matrix interference. The monitoring of gene amplification can also be visualized with the naked eye by using SYBR Green I fluorescent dye. Interpretation & conclusions : Thus, due to easy operation without a requirement of sophisticated equipment and skilled personnel, the RT-LAMP assay reported here is a valuable tool as a point-of-care diagnosis for the rapid and real-time detection of Ebola virus in resource-limited healthcare settings of developing countries.
Meeting the housing needs of military veterans: exploring collaboration and governance

Abstract Veterans in the UK seek help from numerous, diverse organisations to navigate the housing system, in contrast to countries such as the US and Australia, which operate dedicated Veterans Administrations. Collaboration between organisations to support veterans is non-mandatory, yet influential on housing outcomes. This study utilised network governance theory to examine how local partnerships affect veterans’ housing pathways. The research approach involved five in-depth, area-based case studies across different housing contexts. The research contributes new findings on the positive impact of local partnerships and develops a conceptual model of veterans’ housing pathways, focused on collaboration. The study revealed a step change in partnership-working since the introduction of the UK Armed Forces Covenant in 2011, with the absence of mandatory collaboration requirements having nurtured trust-based network governance. The findings suggest this has been effective for veterans in housing need, but there are potential risks in terms of sustainability of voluntary partnerships and the temptation for central government of more hierarchical approaches.
Using extreme learning machines for short-term urban water demand forecasting

Abstract This study explores the ability of various machine learning methods to improve the accuracy of urban water demand forecasting for the city of Montreal (Canada). Artificial Neural Network (ANN), Support Vector Regression (SVR) and Extreme Learning Machine (ELM) models, in addition to a traditional model (Multiple linear regression, MLR) were developed to forecast urban water demand at lead times of 1 and 3 days. The use of models based on ELM in water demand forecasting has not previously been explored in much detail. Models were based on different combinations of the main input variables (e.g., daily maximum temperature, daily total precipitation and daily water demand), for which data were available for Montreal, Canada between 1999 and 2010. Based on the squared coefficient of determination, the root mean square error and an examination of the residuals, ELM models provided greater accuracy than MLR, ANN or SVR models in forecasting Montreal urban water demand for 1 day and 3 days ahead, and can be considered a promising method for short-term urban water demand forecasting.
Magnetic Disturbance Detection for Smartphone-Based Indoor Positioning Systems With Unsupervised Learning

The smartphone magnetometer has been used in many indoor positioning systems to provide location information, such as orientation, user trajectory construction, and magnetic-field-based fingerprint. However, suffering from magnetic disturbance, magnetometer measurements are vulnerable to interference from metal infrastructures, electrical equipment, and other electronic devices in complex indoor environments. This article extracts and explores the statistical features of the smartphone magnetometer measurements. Extensive experiments in various conditions show that the covariance and the magnitude difference can help detect the magnetic disturbance. Based on this, two unsupervised learning-based methods using Gaussian mixture model and k-means are developed to explore the two features mentioned above in magnetic disturbance detection. Experimental results demonstrate that the two proposed approaches have superior detection accuracy, which is 5%–20% higher than the widely adopted vector selection methods in the literature.
Priority Strategy of Financial Institution Pension Funds (FIPF) for Islamic Scheme in Indonesia: Internal, Market, and Regulation Approach

According to a survey conducted by Otoritas Jasa Keuangan (OJK), 74.8% of workers and 85.7% of employers are attracted to Islamic pension funds. However, its market share is still relatively low compared to other Islamic financial product. The purpose of this study is to identify the internal, market and regulation issues that affect the development of FIPF (financial institution pension funds) and construct the strategy to develop FIPF for Islamic scheme. This study applies the analytical hierarchy process (AHP) to determine the strategy based on the priority scale assessed by several experts. The internal issues of FIPF are the priority of both problems and solutions in the development of FIPF for Islamic schemes. Furthermore, from the identification of problems and solutions, the strategy for optimizing FIPF scheme performance and services are the main strategies in expanding the FIPF’s market, followed by FIPF's socialization and literacy strategy, and strategies for strengthening relationships and synergy between the authority and FIPF management.
Investigating the effects of different force fields on spring-based normal mode analysis

Classical normal mode analysis (CNMA) has been widely acknowledged as one of the most useful simulation tools for studying protein dynamics. CNMA uses a fine-grained all-atom model of proteins and a complex empirical potential. In addition, CNMA requires a structure that must be energetically minimized, which makes the method cumbersome to use, especially for large proteins. In contrast, elastic network models (ENM) use coarse-grained protein models and adopt a simplified potential function. ENM is much faster than CNMA but is less accurate. To take the advantages of both CNMA and ENM, the spring-based normal mode analysis (sbNMA) was developed. It uses a fine-grained all-atom model for proteins and an all-atom empirical force field to maintain accuracy while reducing the computing complexity by eliminating the minimization step. In the previous work on sbNMA, only the CHARMM force field was explored. In this work, we extend the analyses to AMBER, another widely-used force field. We investigate the dependence of sbNMA’s performance on force fields. This work provides also insightful understandings of the differences between CHARMM and AMBER.
SWEEP ALGORITHM IN CVRP TO OPTIMIZE DELIVERY AUTOMOTIVE SPARE PART

The CVRP to solve many optimization and application problems distribution especially of the automotive spare parts industry, West Java, Indonesia is presented has 120 customers who aim to optimize and maximize the capacity and cost of vehicles owned, namely 10 colts 6 diesel type vehicles. Vehicle routes are compared against the existing daily distribution routes showing that significant savings can be gained on the daily cost of transportation-related expenses. The objective of this research is to find a set of optimal routes that minimize the number of vehicles required and total distance traveled for all vehicles to serve customers with a result from 10 to 9 using vehicles with a total distance increase from the Sweep method of 253.8347 km and cost benefits or cost savings with a total usage cost of Rp 17.800. 000 to be Rp 17,709,503 in cost efficiency of 4.47% or Rp 90,496.58 a day.
Operating lease or purchase - analysis, Case: An acquisition of Airbus A330-300 for Finnair

Objectives of the study The purpose of this thesis is to present different lease valuation techniques from the existing literature that can be used when assessing a financing decision of an aircraft and then test these methods in practice with the actual data provided by Finnair. The case framework used is an acquisition of a new Airbus A330-300 widebody airliner. The main question is should the aircraft be purchased or leased under an operating lease. This leads to actual hypotheses which question whether operating lease is more cost-effective than purchasing in less than 10 year period or in the long run. Eventually the analysis provides a financing decision model for Finnair. Research method and data The research method of this thesis is a single-company case study. My analysis will be based on cash flow-based valuation techniques such as Net Present Value (NPV) and its more advanced derivative adjusted present value (APV). The results of the model are examined with a sensitivity analysis and further enhanced with a risk analysis tool utilizing Monte Carlo simulation. There a thousand simulations are made to find the deviation of present values. The data includes current and estimated market values and lease rates of A330-300 provided by an independent valuation company. Findings of the study My first hypothesis, “operating lease is more cost-effective than purchasing in less than 10 years' time”, was clearly accepted as the results from both NPV and APV were indisputable. The second hypothesis, that the above holds also if the time period is extended, remains unanswered or can even be rejected. Although APV still very strongly suggests leasing over purchasing, NPV starts to draw nearer to purchasing. Still statistically leasing is the preferable choice but it is apparent that when the time period is lengthened, the purchase becomes more tempting. As a conclusion, according to my analysis in current market environment Finnair should lease the A330 under an operating lease agreement rather than buy it. This is true especially if the considered utilisation of the aircraft is rather short.
PENGARUH MOTIVASI DAN DISIPLIN KERJA TERHADAP KINERJAPEGAWAI PADA DINAS PERTANIAN KABUPATEN SUPIORI

This study aims to identify and analyze whether there is influence of motivation and discipline ito the performance of employees in the Agriculture Office of Supiori District, Papua Province. This research is classified as causal research associative quantitative approach to the instrument in the form of a questionnaire. The population in this study were all employees of the District Agriculture Office Supiori as many as 80 people. The sampling technique by means of saturated or census sampling technique. The sample in this research is to take the population, or as many as 80 samples. The data used in this study are primary data obtained through questionnaires and secondary data related agencies and journals to support this research. Test the validity of the instrument using bivariate Correclation formula, while the reliability test using Cronbach Alpha. Measuring instrument proved valid and reliable for research instruments. Multiple regression analysis used to test hypotheses of this study. The results showed that: motivation (X1) positive and significant impact on employee performance of Agriculture Office in Supiori District () 0.413 with significantly 0,01. Labor discipline (X2) positive and significant impact on employee performance Supiori of Agriculture Office () 0.741 with significantly by 0,00. And based on the test results both independent variables were tested individually dominant in influencing the performance of employees in Supiori District Agriculture Office is working discipline (with a coefficient of 0.489). It can be concluded that in this study the discipline of work (X2) partially are factors that significantly affect performance (Y).
Multilingual Podcast Summarization using Longformers

—Most literature on automated summarization, including podcast summarization, has been restricted to the English language. At the same time, podcasts are now an important form of media in many countries and in many languages and therefore, it is crucial that we expand the problem of podcast summarization to a wider range of languages. In this work, we explore the application of multilingual models to the task of summarizing podcasts in English and Portuguese. We compare various training scenarios including adapting a Longformer encoder, cross-lingual and cross-task transfer learning and we demonstrate that a uniﬁed model ﬁne-tuned to multilingual data can perform on par with dedicated models that are ﬁne-tuned monolingually. As a result, our models signiﬁcantly outperform the TREC baseline based on the ﬁrst minute of each episode.