Miracle-dz/UniFAR-FTUs huggingface dataset:
Optical coherence tomography and T cell gene expression analysis in patients with benign multiple sclerosis

Benign multiple sclerosis is a retrospective diagnosis based primarily on a lack of motor symptom progression. Recent findings that suggest patients with benign multiple sclerosis experience non-motor symptoms highlight the need for a more prospective means to diagnose benign multiple sclerosis early in order to help direct patient care. In this study, we present optical coherence tomography and T cell neurotrophin gene analysis findings in a small number of patients with benign multiple sclerosis. Our results demonstrated that retinal nerve fiber layer was mildly thinned, and T cells had a distinct gene expression profile that included upregulation of interleukin 10 and leukemia inhibitory factor, downregulation of interleukin 6 and neurotensin high affinity receptor 1 (a novel neurotrophin receptor). These findings add evidence for further investigation into optical coherence tomography and mRNA profiling in larger cohorts as a potential means to diagnose benign multiple sclerosis in a more prospective manner.
The Ability of Cloud Computing Performance Benchmarks to Measure Dependability

Current benchmarks focus on evaluating performance with little efforts made to evaluate the dependability characteristics of the cloud. Cloud computing has several advantages like scalability, elasticity and cost reduction, this led companies to move their applications to the cloud. The availability of applications and consequently businesses are then dependant on the cloud’s efforts to keep its services running. To guarantee reliability and trust, benchmarking dependability is a challenging task because of the cloud layered model which makes it difficult to predict the root of faults as higher layers are dependant of lower layers. By integrating dependability in benchmarks as a metric, we can evaluate how well does the cloud handle itself when faults occur, prevent those faults and check not only raw performance but also trust. In this paper, we study the following cloud benchmarks: Spec IaaS 2016, TPCx-V, YCSB, Perfkit Benchmarker, CloudBench, DS-Bench/D-Cloud, and evaluate if they are suitable for benchmarking dependability.
Capital Expenditures Structure, Cost of Capital and Shareholders' Wealth

Financing with reasonable cost, correct usage of capital and preventing the creation of unused resources are the financial management’s most important tasks. Appropriate financing and correct investment in assets leads to sustainable growth in shareholders’ wealth. This study was carried out to investigate the relationship between the capital expenditures structure (CES) and the cost of capital with shareholders’ wealth. Using systematic sampling in a five years period, 186 companies, including the listed companies in Tehran Stock Exchange were selected. To analyze data, Partial Least Squares method of Structural Equation Modeling was used. The findings indicated that there is a significant positive relationship between the CES and shareholders’ wealth in total, but some components of the CES are not related to shareholders’ wealth and it is necessary to be studied carefully. Because, understanding the relationship between the CES and shareholders’ wealth is very important to maximize shareholders’ wealth and will be most effective in capital expenditures’ budgeting. Also, there is a significant inverse relationship between the cost of capital and shareholders’ wealth.
Single-Conductor Transmission-Line Model of Multiwall Carbon Nanotubes

The equivalent single-conductor model of a multiwall carbon nanotube (MWCNT) interconnect is derived analytically from the rigorous formulation of the complex multiconductor transmission-line propagation equations. The expressions of the per-unit-length (p.u.l.) equivalent quantum capacitance and kinetic inductance are obtained in closed form. A new accurate approximated expression of the equivalent p.u. l. quantum capacitance is proposed. It is demonstrated, through analytical derivations and numerical calculations, that the new expression is valid for the most of MWCNT interconnect configurations, whereas a more simplified formula, obtained on the basis of qualitative considerations, produces high approximation errors. The proposed model is solved in both the frequency and time domains. Transient analyses are performed in order to predict the attenuation and time delay of a pulse signal transmitted along an MWCNT as a function of the tube length and number of shells. Simulation results are also compared with measured data available in literature.
Acute Physiology and Chronic Health Evaluation (APACHE) IV: Hospital mortality assessment for today’s critically ill patients*

Objective:To improve the accuracy of the Acute Physiology and Chronic Health Evaluation (APACHE) method for predicting hospital mortality among critically ill adults and to evaluate changes in the accuracy of earlier APACHE models. Design:Observational cohort study. Setting:A total of 104 intensive care units (ICUs) in 45 U.S. hospitals. Patients:A total of 131,618 consecutive ICU admissions during 2002 and 2003, of which 110,558 met inclusion criteria and had complete data. Interventions:None. Measurements and Main Results:We developed APACHE IV using ICU day 1 information and a multivariate logistic regression procedure to estimate the probability of hospital death for randomly selected patients who comprised 60% of the database. Predictor variables were similar to those in APACHE III, but new variables were added and different statistical modeling used. We assessed the accuracy of APACHE IV predictions by comparing observed and predicted hospital mortality for the excluded patients (validation set). We tested discrimination and used multiple tests of calibration in aggregate and for patient subgroups. APACHE IV had good discrimination (area under the receiver operating characteristic curve = 0.88) and calibration (Hosmer-Lemeshow C statistic = 16.9, p = .08). For 90% of 116 ICU admission diagnoses, the ratio of observed to predicted mortality was not significantly different from 1.0. We also used the validation data set to compare the accuracy of APACHE IV predictions to those using APACHE III versions developed 7 and 14 yrs previously. There was little change in discrimination, but aggregate mortality was systematically overestimated as model age increased. When examined across disease, predictive accuracy was maintained for some diagnoses but for others seemed to reflect changes in practice or therapy. Conclusions:APACHE IV predictions of hospital mortality have good discrimination and calibration and should be useful for benchmarking performance in U.S. ICUs. The accuracy of predictive models is dynamic and should be periodically retested. When accuracy deteriorates they should be revised and updated.
Extension of Bertrand’s theorem and factorization of the radial Schrödinger equation

The Bertrand’s theorem is extended, i.e., closed orbits still may exist for central potentials other than the power law Coulomb potential and isotropic harmonic oscillator. It is shown that for the combined potential V(r)=W(r)+b/r2(W(r)=arν), when (and only when) W(r) is the Coulomb potential or isotropic harmonic oscillator, closed orbits still exist for suitable angular momentum. The correspondence between the closeness of classical orbits and the existence of raising and lowering operators derived from the factorization of the radial Schrodinger equation is investigated.
Balanced scorecard method for healthcare quality improvement: A critical analysis

Throughout the world there is an on-going effort to determine quality in healthcare settings. The very definition of “quality”, particularly in healthcare, is rather elusive. The aim of this critique is to analyze the Balance Scorecard method to measure quality as it relates to patient safety in healthcare organisations. Analysis of the Balanced Scorecard in this context determined that the objectivity, both in its measurements and its ability to link together the organization’s quality and financial goals, is indeed beneficial. However, this methodology was also found to be unduly focused on systems and administration rather than on the actual health and safety of patients. The result is a tool that measures “quality” in financial and organizational terms, as sought by healthcare management, and this will continue to be the case until there is a fundamental shift towards defining quality of healthcare in terms of the patients that utilize healthcare services.
Biochemical characterisation of a glucoamylase from Aspergillus niger produced by solid-state fermentation

In this work, glucoamylase was produced by Aspergillus niger in solid-state fermentation. The enzyme was partially purified by ammonium sulphate precipitation and ion exchange and gel filtration chromatographies. Its molecular mass was estimated as 118.17 kDa by electrophoresis. The partially purified enzyme had an optimum pH range of 4.5-5.0 and an optimum temperature of 60 °C, with average activity 152.85 U mL-1. Thermal and pH stability assays with the crude extract showed that more than 60 % of the activity remained at pH 4.6 and 60 °C, even after an exposition to these conditions longer than 24 h. Yet, after purification, the enzyme was stable at these for at least 4 h, which indicated that its purification for use in starch saccharification was inadvisable. KM and Vmax were 0.34 mg mL-1 and 160.22 U mL-1, respectively.
Multilinear Parameter Estimation and Applications Based on Tensor Decomposition

Parameter estimation has always played a key role in signal processing. The conventional methods are based on vector or matrix modeling since the completeness of matrix theory. However, the real-world signal often has the higherorder tensor structure. For instance, the color image can be described as a third-order tensor data including RGB color and coordinate information; similarly, a MIMO channel transfer function can be formulated as a higher-order harmonic signal. Such tensor signal maintains certain structural information among each mode, which would inevitably lost by dimension reduction process. In order to utilize the structural information, tensor decomposition framework has been introduced into signal processing in recent years [1]. Tensor modeling possesses many benefits, e.g., Tucker decomposition (TKD) can achieve a high efficiency in data compression [2]; the uniqueness of canonical polyadic decomposition (CPD) will facilitate the signal identification [3]. In this research, two kinds of parameter estimation problems have been investigated: 1. Arrival angles estimation in array signal processing; 2. SAR imaging for block sparse scattering targets.
ENV-612: A NOVEL SLUDGE-BED ANAEROBIC MEMBRANE BIOREACTOR FOR SUSTAINABLE TREATMENT OF INDUSTRIAL WASTEWATER

Dissolving pulp mill wastewater called prehydrolysis liquor (PHL) obtained from steam (at 150-170C) treatment of wood had a total chemical oxygen demand (COD) of approximately 100 g/L contains mainly sugars, furfural, lignin, and acetic acid, poses a considerable wastewater disposal problem. Replacement of the current energy intensive disposal method (evaporation and use of recovery boiler) is a requirement of dissolving pulp industry. The bioreactors were fed with PHL at organic loading rates (OLR) ranging from 0.8 to 5 kg-COD/m-d to study the performance with respect to the COD removal, methane (bio-energy) production, effluent characteristics, and membrane fouling. Average COD removal of 91% and specific methane yield of 0.36 m/kg-CODremoved/day were achieved during the pseudo-steady period of the continuous mesophilic operation at each loading rate. Whereas, in thermophilic conditions, a methane yield of 0.38 m/kg-CODremoved/day was observed. There was no sugar and furfural found in the effluent of the SB-AnMBR at both temperatures (35C and 55C) during the pseudo-steady period. High effluent COD can be attributed to lignin in the effluent (0.2 to 1.6 g/L). Flat-sheet membranes used in the SB-AnMBRs did not show significant fouling based on monitoring of temporal variations in the trans-membrane pressure at a sustained flux of 0.1 m/m/d during the 550 days of the continuous operation.
Systemic Treatment in Unresectable Metastatic Well-Differentiated Carcinoid Tumors: Consensus Results From a Modified Delphi Process

Objectives This study aimed to develop expert consensus for the use of systemic treatments for unresectable metastatic well-differentiated (grade 1–2) carcinoid tumors using the RAND/UCLA modified Delphi process. Methods After a comprehensive literature review, 404 patient scenarios addressing the use of systemic treatments for carcinoid tumors were constructed. A multidisciplinary panel of 10 physicians assessed the scenarios as appropriate, inappropriate, or uncertain (on a 1–9 scale) or as an area of disagreement before and after an extended discussion of the evidence. Results Experts were medical and surgical oncologists, interventional radiologists, and gastroenterologists. Among rated scenarios, disagreement decreased from 14% before the meeting to 4% after. Consensus statements about midgut carcinoids included the following: (1) Somatostatin analogs are appropriate as first-line therapy for all patients; (2) In patients with uncontrolled secretory symptoms, it is appropriate to increase the dose/frequency of octreotide long-acting repeatable up to 60 mg every 4 weeks or up to 40 mg every 3 weeks as second-line therapy for refractory carcinoid syndrome. Other options may also be appropriate. Consensus was similar for non–midgut carcinoids. Conclusions The Delphi process provided a structured methodological approach to assist clinician experts in reaching consensus on the appropriateness of specific medical therapies for the treatment of advanced carcinoid tumors.
Parallel social network mining for interesting ‘following’ patterns

Social networking sites (e.g., Facebook, Google+, and Twitter) have become popular for sharing valuable knowledge and information among social entities (e.g., individual users and organizations), who are often linked by some interdependency such as friendship. As social networking sites keep growing, there are situations in which a user wants to find those frequently followed groups of social entities so that he can follow the same groups. In this article, we present (i) a space‐efficient bitwise data structure for capturing interdependency among social entities; (ii) a time‐efficient data mining algorithm that makes the best use of our proposed data structure for serial discovery of groups of frequently followed social entities; and (iii) another time‐efficient data mining algorithm for concurrent computation and discovery of groups of frequently followed social entities in parallel so as to handle high volumes of social network data. Evaluation results show the efficiency and practicality of our data structure and social network data mining algorithms. Copyright © 2016 John Wiley & Sons, Ltd.
Ultrastructural cytochemical prospective study of adult acute lymphoblastic leukemia: Detection of peroxidase activity in patients failing to respond to treatment

Ultrastructural cytochemical studies revealed peroxidase activity in five of 25 adult patients with apparent null lymphoblastic leukemia (ALL) in whom the peroxidase reaction studied with light microcopy was negative. None of these 5 patients responded to a chemotherapy regimen used for adult ALL. The importance of ultrastructural cytochemistry which allows the recognition of myeloblastic differentiation in undifferentiated blast cells is also demonstrated. The correct classification of such cases may be important for prognosis because they appear to be resistant to the chemotherapy used in treating ALL.
WebSifter II: A Personalizable Meta-Search Agent Based on Weighted Semantic Taxonomy Tree

This paper addresses the problem of specifying, retrieving, filtering and rating Web searches so as to improve the relevance and quality of hits, based on the user’s search intent and preferences. We present a methodology and architecture for an agent-based system, called WebSifter II, that captures the semantics of a user’s decision-oriented search intent, transforms the semantic query into target queries for existing search engines, and then ranks the resulting page hits according to a user-specified weighted-rating scheme. Users create personalized search taxonomies via our Weighted Semantic-Taxonomy Tree. The terms in the tree can be refined by consulting a web taxonomy agent such as Wordnet. The concepts represented in the tree are then transformed into a collection of queries processed by existing search engines. Each returned page is rated according to user-specified preferences such as semantic relevance, syntactic relevance, categorical match, page popularity and authority/hub rating.
Intermodal mobility in cities and its contribution to accessibility

ABSTRACT Cities offer a wide range of different mobility options, including a dense public transport network and good conditions for walking and cycling. They provide good basic requirements for using and combining different modes of transport in people’s everyday mobility in a flexible, individual and situational way. In larger cities in particular, intermodal mobility plays a significant role and is being discussed as crucial to minimizing traffic congestion, emissions and the demand for parking space. Although a common practice, intermodal mobility has so far received little attention in empirical and theoretic mobility research. This contribution addresses this gap. It compares unimodal and intermodal travel modes, and discusses their effects on accessibility in cities. Using the city of Berlin, Germany, as example, it explores intermodal mobility practice and the extent to which this relates to accessibility in cities compared to unimodal modes. Based on empirical survey data and calculations of spatial accessibility indicators, we present the performance of unimodal and intermodal travel modes using accessible locations and distance over time, and set them against the frequency of using the various modes of unimodal and intermodal travel. The combination of empirical and modeling data provides new insights into how accessibility measures based on structural data fit together from a user’s perspective and can complement each other. Based on this, we discuss further aspects of accessibility relevant for intermodality.
Predictable multithread scheduling with cycle-accurate thread progress monitor

One of the key challenges to develop applications for multicore-based embedded systems is enduring software complexity and performance requirements raised by parallel programming. Adaptive, self-aware or deterministic computing has been proposed as one method to help application developer cope with these problems. To provide these advanced features, the developer should monitor their application to know the current state of the application for optimizing or adapting to meet their goals. One solution is to make thread progress index of a program for tracking their current state. To guarantee accuracy of the tracking method, we find that the process of a thread should be repeatable and accurate. If the progress does not have the properties, it is impossible to guarantee the accuracy and determinism of the method for tracking progress of thread. Additionally, we minimize the overhead to measure and manage the progress even though providing the cycle-accurate progress tracking with inevitable runtime overhead. In this paper, we propose an efficient method to monitoring thread progress with a cycle-accurate deterministic progress counter and an efficient management technique for adaptive scheduling algorithm. As a case study, we implement 24 video decoders on a quad core system using the proposed runtime system and show the experimental result which yields a geometric mean overhead of about 2.1% to monitor each thread and these applications yield a mean performance improvement of 6% relative to normal execution when running on 4 cores.
Virtual Resource Allocation in Software-Defined Information-Centric Cellular Networks With Device-to-Device Communications and Imperfect CSI

In this paper, we propose an architecture of software-defined information-centric network virtualization with device-to-device (D2D) communications, which facilitates dynamic virtual resource allocation and content caching via a software-defined networking (SDN) controller with a global view of the system. In our proposed framework, substrate physical resources can be virtualized and shared among multiple mobile virtual network operators (MVNOs). Meanwhile, by means of integrating D2D communications into information-centric wireless networks, content caching is enabled not only in the air but in mobile devices as well. In addition, taking into consideration inaccurate channel estimation and measurement, we formulate the virtual resource allocation and caching optimization as a discrete stochastic optimization problem in which imperfect channel state information is incorporated. Because the formulated virtual resource allocation problem is a large-scale combinational optimization problem, we exploit discrete stochastic approximation approaches to cope with it. Finally, extensive simulations are conducted to demonstrate the effectiveness of the proposed scheme with different system parameters. Simulation results show that MVNOs can benefit from not only the sharing of physical infrastructure but from the caching functionality that exists in both the air and mobile devices as well.
Responsible innovation: from concept to application:cases of energy technology adoption in Indonesia

The adoption of solar PV in telecom towers is considered as a sustainable innovation in powering the towers. Such adoption involves different actors who hold different tasks and responsibilities. However, the indication that comes up among the actors involved is that if and when a disaster occurs (e.g. telecom systems collapse) due to the failure in the operation and management of solar PV after its installation, they will most likely be prone to finger-pointing at each other. In such situation, the questions arise: how to locate the accountability, who should be accountable to whom and for what and how to proportionally distribute the accountability? Through a case study in Indonesia, this paper discusses and analyses how to address such issue by undertaking Stakeholder and Impact Analyses and analysis of five dimensions of Responsible Innovation namely: anticipation, reflexivity, deliberation, responsiveness and participation. Our analysis suggests that there is a need of an innovative way or technology that can proportionally distribute the accountability of actors involved. The paper also concludes that innovation without responsibility faces dangers of rejection or less acceptability of even greener and sustainable technology.