Miracle-dz/UniFAR-FTUs huggingface dataset:
Microbend sensor structure for use in distributed and quasi-distributed sensor systems based on selective launching and filtering of the modes in graded index multimode fiber

This paper describes a novel optical fiber microbend sensor architecture which my be utilized in distributed and quasi-distributed measurement. The actual sensor element is graded index multimode fiber coupled to the measurand field through the usual microbend inducing structures. However, the feed to the sensing section is through a single-mode fiber spliced to the multimode fiber to ensure that only the lowest order spatial mode is launched. Similarly the receiver is also coupled to the sensing element through a single mode fiber. The single mode within multimode fiber propagates with minimal mode coupling with source to receiver losses of typically 0.7 dB for short sensors ranging to approximately 0.3 dB per each additional kilometer of sensing fiber. The sensitivity of this structure to microbend induced losses has been thoroughly characterized. Typically the optical power loss for a given microbend structure and force is about three to six times higher in this architecture than for conventional fully mode filled microbend sensor. The structure is also almost totally insensitive to macrobend induced losses and allows a variety of novel designs in microbend inducing structures. Additionally, spatial mode filters allow effective control over concatenation effects that are common in microbend sensors.
A new approach for estimating indoor radio propagation characteristics

Presents a new approach for estimating the propagation characteristics of indoor radio channels. The technique is based on the use of principal component analysis and the information theoretic criterion. It is shown, based on the simulation results, that the new technique can be used to overcome difficulties experienced by conventional methods and, as a result, is able to produce greater accuracy in its estimates of the channel parameters. The authors demonstrate the use of this technique by carrying out data analysis using measured indoor radio channel data. >
Signal conditioning and quality estimation method of Overhauser magnetometer

Overhauser magnetometer reaches an ultra-high accuracy benefit from the outputted frequency of free induction decay transversal signal is proportional to the magnetization on measuring the real scalar geomagnetic field. Nevertheless, the magnitude of the accuracy is an important factor that severely affects the validity of geomagnetic field data. Since the real value of the geomagnetic field is unknown, we propose a measurement quality estimation method through analyzing the envelope of the free induction decay transversal signal from the Overhauser magnetometer. The estimation model includes the SNR and the decay slope characteristics of the signal is indicated in an two-digit number changes from 00~99. The results demonstrated that the proposed estimation method can effective performance the reliability of magnetometer measurement data in our experiments.
Open Innovation with Customers: Crowdsourcing and Co-Creation at Threadless

Threadless’ product is rather simple: A graphic t-shirt. But the company has become one of textbook examples and pioneers of customer co-creation – open innovation with customers. The Chicago-based start-up, founded in 2001, created a unique infrastructure for deep involvement of customers and external experts in the new product development process. It has become the role-model for many entrepreneurs in the field. This paper describes how Threadless “crowdsourcing” approach works and what the factors of its success are. The paper also comments briefly on idea to transfer the Threadless model onto other industries.
A Gene Prognosis Profile using Partial Least Square (PLS)

In a typical clinical study based on a microarray gene expression experiment, there are often more genes than subject samples, and many genes are correlated. Partial least square regression, though not originally designed for classification purposes, can be used to build a classifier to predict outcomes based on the high dimensional correlated gene expression data. In this article, using a publicly available breast cancer study data, we show the process of using PROC PLS in SAS to construct a metastasis risk classifier from a training dataset. The classifier is further used to assign patients from an independent validation set into high- and low- risk groups based on their gene expressions. The result confirms that patients in the two predicted risk groups show significant difference in their survival outcome.
Moderate-intensity interval training (MIT) can protect rats against Methamphetamine –induced injuries

Methamphetamine (METH) can cause neurotoxicity and increase the risk of neurodegenerative disorders such as Alzheimer disease and Parkinson disease. This study aimed to investigate the effect of moderate-intensity interval training (MIT) on gene expression and antioxidant status of the hippocampus of METH-dependent rats. Twenty-eight male Wistar rats were randomly divided into four equal groups (n=7): saline, METH, MIT, and METH+MIT. METH was injected intraperitoneally at 5 mg/kg for 21 days. The MIT (intermittent running) was performed on the treadmill 5 days a week for 8 weeks. Morris Water Maze test was performed to measure learning and memory. Then, the hippocampal tissue was extracted to evaluate changes in gene expression and biochemical enzymes. The data were analyzed using one-way and two-way ANOVA methods at P<0.05. The results showed that METH injection significantly reduced spatial memory and antioxidant enzymes and increased the expression of α-synuclein (α-syn), cyclin-dependent kinase 5 (CDK5), tau and phosphorylated tau (p-Tau) genes compared to the saline group. MIT significantly increased spatial memory and antioxidant enzymes. However, it reduced α-syn, CDK5, tau and p-tau expression. Thus, METH caused neural damage, and MIT could protect the neural system against METH-induced insults in male rats.
Unsteady and three-dimensional flow phenomena in a transonic centrifugal compressor impeller at rotating stall

This paper presents a combined experimental and numerical analysis of rotating stall in a transonic centrifugal compressor impeller for automotive turbochargers. Stall characteristics of the compressor were examined by two high-response pressure transducers mounted on the casing wall near the impeller inlet. The pressure traces were analyzed by wavelet transforms to estimate the disturbance waves quantitatively. Three-dimensional unsteady internal flow fields were simulated numerically by Detached Eddy Simulation (DES) coupled LES-RANS approach. The analysis results show good agreements on both compressor performance characteristics and the unsteady flow features at the rotating stall. At stall inception, spiral-type breakdown of the full-blade tip leakage vortex was found out at some passages and the brokendown regions propagated against the impeller rotation. This phenomenon changed with throttling, and tornado-type separation vortex caused by the full-blade leading edge separation dominated the flow field at developed stall condition. It is similar to the flow model of short-length scale rotating stall established in an axial compressor rotor.Copyright © 2009 by ASME
Removal of Malachite Green and cadmium ions using nifty combination of metal functionalized graphene based composites from refuse dry cell batteries

The persistent use of toxic chemicals, that is, azo dyes and heavy metals in various sectors like industries, agriculture and research laboratories have resulted in polluting different compartments of the environment with the residues. The present communication specifically aims to synthesize a nifty combination of graphene oxide (GO) functionalized with metal particles, that is, silver (Ag) and copper (Cu) to remediate the pollutants from the wastewater using the adsorption process. GO functionalized with a silver (AgGO) and copper metal (CuGO) were synthesized respectively and characterized as adsorbents for the removal of Malachite green, cadmium ions (Cd2+) and as a microbial entity, that is, Staphylococcus aureus. Results of Fourier-transform infrared spectroscopy and X-ray fluorescence techniques have confirmed the synthesis of GO and its functionalization. A close batch system of 60 min was designed to study the adsorption process under various parameters (concentration, contact time) using ultraviolet-visible spectroscopy and flame atomic absorption spectroscopy. Comparison of percentage removal of heavy metal between composites revealed a better adsorption trend by AgGO (94%) as compared with the prepared CuGO (84%) from wastewater. Contrary to that the percentage removal of azo dyes is 98% by CuGO. Kinetic studies favored pseudo-second-order and intraparticle diffusion models whereas adsorption studies favored Langmuir and Freundlich isotherms. The proposed composite comprises of graphene which is labeled as a bactericidal agent and after its metal functionalization enhances the antibacterial activity marvelously.
Intrinsic neural control of propulsion, storage and slow transit in the large intestine

The experiments described in this dissertation have examined how the enteric nervous system regulates specific aspects of gastrointestinal motility. We have identified, despite over 100 years of gastrointestinal research, a new intrinsic neural reflex that appears to underlie slow transit and accommodation in the large bowel. Using electrophysiological techniques we demonstrate that circumferential stretch generates ongoing oral excitatory and anal inhibitory junction potentials in the circular muscle (CM) of both the guinea pig distal and primate sigmoid colons. This activity has been referred to as ongoing peristaltic reflex activity. The sensory elements underlying the repetitive firing of ascending excitatory and descending inhibitory neuronal pathways lie in the CM, in close opposition to the myenteric plexus. Mechanosensitive ion channels present on the sensory elements are likely to be responsible for the transduction of the circumferential stretch. In the guinea pig distal and primate sigmoid colons, application of longitudinal stretch inhibited all junction potentials in both species. Inhibiting nitric oxide (NO) synthesis with N-nitro-L-arginine (100 μmol/L) completely reversed the inhibitory effects of longitudinal stretch suggesting that nitric oxide (NO) inhibited interneurons controlling peristaltic circuits. Ca 2+ imaging in preparations that were stretched in both axes revealed ongoing firing in nNOS +ve descending neurons, even when synaptic transmission was blocked. Inhibitory postsynaptic potentials could be evoked in mechanosensitive interneurons and subsequentially blocked by N-nitro-L-arginine (100 μmol/L).
Climate Consequences of Rebalancing Official Climate Finance: Analyzing Multilateral Development Banks’ Allocation Practices

The transition towards a low-carbon economy requires the fundamental reallocation of financial capital from current technologies towards green innovation. The role of public financing of green technological innovation by Multilateral Development Banks (MDB) is a largely unexplored area. In this paper, we provide novel evidence on the climate financing practices of MDBs and their long-term climate consequences. The majority of MDB climate finance is for mitigation projects and is concentrated in a small number of relatively wealthy countries. We show that MDBs’ climate financing is positively correlated with countries' greenhouse gas emissions but not with their vulnerability to climate risks. Our numerical simulations show that moving towards more equal funding of innovative mitigation-adaptation projects can substantially lower global climate vulnerability. We also show that rebalancing MDB funding towards adaptation projects and technologies can reduce vulnerability significantly for an additional 2.5 billion people, without a significant change in the annualized growth rate of emissions. MDB four different scenarios Next, of CO 2 we mitigation finance ADB, AfDB, EBRD, EIB and IDB and the aggregate CO 2 (and GDP) of their covered from 2014 to 2018. We regress the aggregate CO 2 emissions on mitigation finance, and GDP with an MDB fixed effect. We then predict the future total CO 2 emissions of MDBs’ covered countries and the mitigation finance under the four scenarios. We use an estimate of the future GDP growth of countries from the OECD(2018). The average annual GDP growth estimates are 4% until 2030, 3% between 2030 and 2040, and 2.3% between 2040 and 2050.
Real-World Evidence of COVID-19 Patients’ Data Quality in the Electronic Health Records

Despite the importance of electronic health records data, less attention has been given to data quality. This study aimed to evaluate the quality of COVID-19 patients’ records and their readiness for secondary use. We conducted a retrospective chart review study of all COVID-19 inpatients in an academic healthcare hospital for the year 2020, which were identified using ICD-10 codes and case definition guidelines. COVID-19 signs and symptoms were higher in unstructured clinical notes than in structured coded data. COVID-19 cases were categorized as 218 (66.46%) “confirmed cases”, 10 (3.05%) “probable cases”, 9 (2.74%) “suspected cases”, and 91 (27.74%) “no sufficient evidence”. The identification of “probable cases” and “suspected cases” was more challenging than “confirmed cases” where laboratory confirmation was sufficient. The accuracy of the COVID-19 case identification was higher in laboratory tests than in ICD-10 codes. When validating using laboratory results, we found that ICD-10 codes were inaccurately assigned to 238 (72.56%) patients’ records. “No sufficient evidence” records might indicate inaccurate and incomplete EHR data. Data quality evaluation should be incorporated to ensure patient safety and data readiness for secondary use research and predictive analytics. We encourage educational and training efforts to motivate healthcare providers regarding the importance of accurate documentation at the point-of-care.
Information Technology in English Language Learning: Towards a Plan in Teacher Professional Development and Growth

The use of Information Technology (IT) in English language learning has grown over the past 50 years in response to learners’ needs and developments in theories relating to the nature of language and language learning. But technological advancement is not neutral. Educational practitioners require ways of determining what IT has to offer and justifying their decisions to utilise it. Using an original lesson outline and instructional aids produced for a primary level (age 9 and above) class in Singapore, this paper illustrates how IT has the potential to create learning opportunities, increase the quality of learning experiences and provide a basis for input variation. The article concludes with four ideas for starting and maintaining a programme of language teacher professional development and growth with IT. Considered individually, each of these items can bring small rewards. But when combined they have the potential to generate more ambitious and transformative action plans.
Selecting trainees: Too much focus on predictive metrics, not enough on holistic review

As we near the end of the calendar year, undergraduate and graduate medical education programmes set out on another round of highstakes decisions about which trainees will make up their cohorts. They do so in a time of flux, amidst a period of renewed focus on diversity and equity and on the heels of an admissions season whose format was subjected to considerable experimentation in response to the COVID-19 pandemic. Given this context, the effort by Lievens et al. to provide programmes a straightforward means to help ensure their cohorts are diverse and positioned for success is timely. Using Pareto optimization, a mathematical modelling approach developed initially in economics, the authors propose a tool for weighing the attributes of medical school and residency applicants to achieve an optimal balance of diversity and ‘predictiveness’ in selection.
Building Connections through Sport and Physical Activity for Ill and Injured Military Members and Veterans: Determining the Optimal Time for Program Involvement

Abstract Research has shown that physical fitness can benefit individuals with an injury or illness, enhancing their psycho-social health and well-being. The Soldier On program supports Canadian Armed Forces personnel and veterans in overcoming their physical and mental health injuries through promotion of physical activity and sport. Using a qualitative research design, a key question was investigated: are there optimal time points during which ill/injured military members and veterans have higher levels of readiness that would facilitate maximum benefit from program involvement? Semi-structured, in-person interviews were conducted with participants (n = 75) at Soldier On events across Canada. Results suggest there may be critical points following the onset of a significant injury/illness where event participation has the potential to enhance the positive impacts. For service members, this was identified to be following the official medical release decision and duration leading up to their transition out of the military. For veterans, it was found to be only after there was sufficient time post-release to allow for the full reintegration into civilian life. Findings suggest that when considering enrollment of military members and veterans into physical and sport therapy programs, it is important to tailor programs to these critical time periods for each individual.
BUSINESS INTELLIGENCE AND E-GOVERNANCE

As a majority of the population lives in rural areas and are illiterates how to bring them into the new system will be a big challenge to the government. Further, still there are some villages which are not accessible and do not have electricity. To train the entire population on how to use, how to communicate with the officials in case of any issue, one has to have a detailed working strategy for its better utilization. In the e-governance environment, the cost of providing infrastructure would be a big challenge. The costs of new technologies get distributed and in comparison to the value generated, it is worthwhile to invest in such infrastructure only when all the three participants effectively put it into use.
The Adoption of Geographic Information Systems in the Public Sector of Saudi Arabia: A Conceptual Model

The development of fuzzy sets in geographic information systems (GIS) arose out of the need to handle uncertainty and the ability of soft computing technology to support fuzzy information processing. Fuzzy logic is an alternative logical foundation coming from artificial intelligence (AI) technology with several useful implications for spatial data handling. GIS has been found to have a crucial role in the performance of public sector organizations (PSO). However, the literature shows no universal model to support and shed light on GIS adoption, which lessens the chances for effective GIS adoption and usage. Therefore, a new model is needed for successful adoption and eventual enhanced organization’s performance. Thus, there is a need to investigate the factors that can bring about GIS adoption. Models for GIS adoption in literature are few and far between, and the few that exist are not applicable as they do not cover all the significant factors that can contribute to adoption success. Hence, this paper brought a GIS adoption model for PSOs to promote their performance. The model was developed through the extension of the Technology Acceptance Model (TAM) in addition to the DeLone and McLean’s Success Model. The study involved interviews with ten experts in ranking the extracted factors, and data was analyzed through thematic analysis. On the basis of the obtained analysis findings, the fundamental factors were found to be significant in their effects, and GIS adoption sufficiently related to the overall performance. Thus, the study contributes to the body of knowledge by filling the gap in the literature.
Nonlinear piezoelectric vibration absorbers

The effect of quadratic nonlinear electrical shunts on the performance of piezoelectric vibration absorbers is presented. The equations of motion are derived in a format suitable for perturbation analysis. An electrical shunt containing cubic and quadratic elements is coupled to the structure via the piezoelectric effect. Nonlinearities are introduced as a combination of the square and/or cube of the charge flowing in the linear inductive-resistive (LR) shunt. Tuning the shunt near a structural mode causes mechanical energy to be transformed to electrical energy and dissipated by the resistive element in the shunt in a manner analogous to a damped vibration absorber. Analysis is carried out using the method of multiple scales. Simulation results are also presented.
Hollow-core photonic bandgap fiber Mach-Zehnder interferometer based on a long period grating and an offset-splice joint

We report a compact in-fiber Mach-Zehnder interferometer (MZI) made along a hollow-core photonic bandgap fiber (HC-PBF). The MZI uses a long period grating (LPG) and an offset-splice joint (OSJ) which act as beam splitter and combiner respectively. The LPG was produced by use of a high frequency pulsed CO2 laser, and the OSJ was made in serial with the LPG by using a commercial fusion splicer. The interference is between the fundamental core mode (FCM) and a high-order core mode (HOCM). The proposed interferometer was experimentally tested for temperature and strain measurements, and the sensitivities of the interference fringe dip wavelength to temperature and strain are 107.5 pm/ (°C-m) and -1.24 pm/με, respectively.
Incremental fuzzy expert PID control

An approach to intelligent PID (proportional integral derivative) control of industrial systems which is based on the application of fuzzy logic is presented. This approach assumes that one has available nominal controller parameter settings through some classical tuning technique (Ziegler-Nichols, Kalman, etc.). By using an appropriate fuzzy matrix (similar to Macvicar-Whelan matrix), it is possible to determine small changes on these values during the system operation, and these lead to improved performance of the transient and steady behavior of the closed-loop system. This is achieved at the expense of some small extra computational effort, which can be very easily undertaken by a microprocessor. Several experimental results illustrate the improvements achieved. >
A Rapid and Easy-to-Perform Method of Nucleic-Acid Based Dengue Virus Diagnosis Using Fluorescence-Based Molecular Beacons

Detecting dengue virus (DENV) infection in patients as early as possible makes the disease management convenient. Conventionally, DENV infection is diagnosed by ELISA-based methods, but sensitivity and specificity are major concerns. Reverse-transcription-PCR (RT-PCR)-based detection confirms the presence of DENV RNA; however, it is expensive, time-consuming, and skilled personnel are required. A fluorescence-based detection system that detects DENV RNA in patient’s serum directly, without any nucleic acid amplification step, has been developed. The method uses target-specific complementary sequence in the molecular beacon, which would specifically bind to the DENV RNA. The molecular beacons are approximately 40 bases long hairpin structures, with a fluorophore-quencher system attached at the terminal ends of the stem. These probes are biotinylated in the stem region, so that they can be immobilized on the streptavidin-tagged magnetic beads. These magnetic beads, coupled with biotinylated molecular beacons, are used for the detection of the target RNA in the serum by incubating the mixture. After incubation, beads are separated and re-suspended in a buffer. The measurement of fluorescence is taken in fluorometer after 15 min incubation at 50 °C. The whole work is carried out in a single tube. This rapid method can precisely detect dengue RNA within two hours, confirming ongoing DENV replication in the patient.