Miracle-dz/UniFAR-FTUs huggingface dataset:
Ventilatory Function in Bronchial Asthma

Ventilation of the lungs is seriously impaired in the asthmatic paroxysm. There is obvious interference with the free exchange of tidal air, but, with considerable effort, the total minute ventilation is often maintained at normal levels. Thus the ventilatory defect cannot be measured in terms of a reduction in minute ventilation or tidal air. Birath (1944) and many other workers have assessed the ventilatory defect in terms of an increase in " physiological dead space " in the lung. This defect, however, may more properly be regarded as due to uneven ventilation of different parts of the lung. A spirometric method recently developed permits the approximate assessment of the degree of uneven ventilation of the lungs in terms of the volume and ventilation of the poorly ventilated space, or spaces, hereafter referred to as P.V. S. (Briscoe, 1952). It is the purpose of this paper to describe some studies on asthmatic subjects using this method.
Using adrenaline during neonatal resuscitation may have an impact on serum cardiac troponin‐T levels

It has been suggested that serum cardiac troponin‐T (cTnT) can predict the severity of neonatal hypoxic–ischaemic encephalopathy. We evaluated whether cTnT was better correlated with adrenaline during cardiopulmonary resuscitation (CPR) than with the severity of the insult itself, based on the Apgar scores.
The Source and Exploitation of the Program Vulnerability

Vulnerabilities with the C and C ++ language programming are the source of information security incidents. The language is an insecure programming language, which allows an attacker to change the behavior of the running program or completely control it through the vulnerabilities in the program. This issue has been known for more than 30 years. During this period, many vulnerability mitigation technologies have been proposed to prevent the exploitation of the vulnerabilities. However, many facts have proven that these mitigation technologies can not completely solve the problem. This paper clearly illustrates that the flaws and errors of C and C ++ language are the fundamental cause of the vulnerability generation. Then, the paper further analyzes the vulnerabilities generated by the flaws and errors as well as the implementation attacks by exploiting the vulnerabilities. Lastly, this paper also points out the key to the successful implementation attacks by exploiting these vulnerabilities. Keywordsvulnerabilities, exploit, attack
Antigen-Reactive T Cell Enrichment for Direct, High-Resolution Analysis of the Human Naive and Memory Th Cell Repertoire

Ag-specific CD4+ T cells orchestrating adaptive immune responses are crucial for the development of protective immunity, but also mediate immunopathologies. To date, technical limitations often prevented their direct analysis. In this study, we report a sensitive flow cytometric assay based on magnetic pre-enrichment of CD154+ T cells to visualize rare Ag-reactive naive and memory Th cells directly from human peripheral blood. The detection limit of ∼1 cell within 105–106 permitted the direct enumeration and characterization of auto-, tumor-, or neo-Ag–reactive T cells within the naive and even memory CD4+ T cell repertoire of healthy donors. Furthermore, the analysis of high target cell numbers after pre-enrichment of rare Ag-specific T cells from large blood samples dramatically improved the identification of small subpopulations. As exemplified in this work, the dissection of the Ag-specific memory responses into small cytokine-producing subsets revealed great heterogeneity between pathogens, but also pathogen-related microsignatures refining Th cell subset classification. The possibility to directly analyze CD4+ T cells reactive against basically any Ag of interest at high resolution within the naive and memory repertoire will open up new avenues to investigate CD4+ T cell–mediated immune reactions and their use for clinical diagnostics.
Asymmetric play in a linear quadratic difierential game with bounded controls

This paper uses computational techniques to identify the Markov perfect equilibria in a two agent linear quadratic difierential game with bounded controls. No evidence is found asymmetric equilibria when the agents are symmetric or of non-linear equilibria when the agents are asymmetric. This suggests that the standard continuum result for identical agents is not robust and that non-linear strategies are not of general interest in the analysis of linear quadratic difierential games. The techniques presented here are applicable to a broader class of difierential games as well.
Grid-connected PV system: Introduction to behavior matching

This paper presents a PV grid-connected system in centralized configuration and constructed with a three- phase dual-stage inverter. In this topology, usually, a DC- DC converter performs the maximum power point tracking (MPPT) and an inverter is responsible for controlling of the grid-current. For the DC-DC stage the three-phase series resonant converter (SRC3) is chosen thanks to the very advantages that it exhibit. However, it is inadequate for the accomplishment of MPPT, due that its efficiency extremely depends on the implemented deadtime and switching frequency. Then, this paper proposes a conceptual modification, i.e., a dual-stage inverter in which the inverter stage is responsible for the MPPT and the grid-current control. In addition, the DC-DC converter operates with constant duty cycle and frequency. Such configuration requires a new concept, introduced as behavior matching. It serves as fundamental feature for the DC-DC converter to reproduce the PV array I-V characteristic when they are connected, without control action. The maximum power operating point (MPOP) is finding maximizing the direct axis current, obtained by Park's transformation from the inverter, through the perturbation and observation algorithm (P&O). Any specific measurement to MPPT is made. The isolation is performed by a high-frequency transformer becoming the system most compact. The structure is appropriate for high power applications, above 10 kW.
The association of mental health over time with cardiac outcomes in HEMO study patients.

BACKGROUND AND OBJECTIVES Poor mental health over time is significantly associated with cardiovascular morbidity and mortality in the general population, which is the leading cause of death in dialysis patients. Most studies of dialysis patients, however, have investigated the relationship between baseline mental health measurements and all-cause mortality and not mental health measured longitudinally throughout a study and cause-specific mortality. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS This study examined the association of changes in mental health over time with all-cause and cause-specific deaths and cardiac hospitalizations in the Hemodialysis study patients. Mental health was assessed at baseline and annually during the study with short form 36 mental health index scores. Poorer mental health was defined by a mental health index score≤60. RESULTS Patients with poorer mental health at baseline were more likely to have less than a high school education and be unmarried, have significantly higher index of coexistent disease scores, and report taking β-blockers and sleep medications. Low mental health scores over time were independently associated with a decrease in survival time from all-cause mortality by -0.06 (-0.10, -0.03; P<0.001), and they also significantly hastened time to first cardiac hospitalization by -0.08 (-0.13, -0.02; P=0.01) and composite of first cardiac hospitalization or cardiac death by -0.04 (-0.07, -0.02; P<0.001). CONCLUSIONS This study found an independent association between poor mental health over time and all-cause mortality, cardiac hospitalization, and the composite of cardiac death or cardiac hospitalization in hemodialysis patients. The results underscore the importance of attention to mental health related to cardiac complications and even death in dialysis patients.
Large Scale LP Decoding with Low Complexity

Linear program (LP) decoding has become increasingly popular for error-correcting codes due to its simplicity and promising performance. Low-complexity and efficient iterative algorithms for LP decoding are of great importance for practical applications. In this paper we focus on solving the binary LP decoding problem by using the alternating direction method of multipliers (ADMM). Our main contribution is that we propose a linear-complexity algorithm for the projection onto a parity polytope (having a computational complexity of small O(d), where small d is the check-node degree), as compared to recent work , which has a computational complexity of small O(d log d). In particular, we show that the projection onto the parity polytope can be transformed to a projection onto a simplex.
Pharmacoepigenetics: an element of personalized therapy?

ABSTRACT Introduction: Epigenetics is a rapidly growing field describing heritable alterations in gene expression that do not involve DNA sequence variations. Advances in epigenetics and epigenomics have influenced pharmacology, leading to the development of a new specialty, pharmacoepigenetics, the study of the epigenetic basis for the individual variation in drug response. Areas covered: We present an overview of the major epigenetic mechanisms and their effects on the expression of drug metabolizing enzymes and drug transporters, as well as the epigenetic status of drug protein targets affecting therapy response. Recent advances in the development of pharmacoepigenetic biomarkers and epidrugs are also discussed. Expert opinion: There is growing evidence that pharmacoepigenetics has the potential to become an important element of personalized medicine. Epigenetic modifications influence drug response, but they can also be modulated by drugs. Moreover, they can be monitored not only in the affected tissue, but also in body fluids. Nevertheless, there are very few examples of epigenetic biomarkers implemented in the clinical setting. Explanation of the interplay between genomic and epigenomic changes will contribute to the personalized medicine approach. Ultimately, both genetic biomarkers and epigenetic mechanisms should be taken into consideration in predicting drug response in the course of successful personalized therapy.
Impulsive Synchronization of Reaction–Diffusion Neural Networks With Mixed Delays and Its Application to Image Encryption

This paper presents a new impulsive synchronization criterion of two identical reaction-diffusion neural networks with discrete and unbounded distributed delays. The new criterion is established by applying an impulse-time-dependent Lyapunov functional combined with the use of a new type of integral inequality for treating the reaction-diffusion terms. The impulse-time-dependent feature of the proposed Lyapunov functional can capture more hybrid dynamical behaviors of the impulsive reaction-diffusion neural networks than the conventional impulse-time-independent Lyapunov functions/functionals, while the new integral inequality, which is derived from Wirtinger's inequality, overcomes the conservatism introduced by the integral inequality used in the previous results. Numerical examples demonstrate the effectiveness of the proposed method. Later, the developed impulsive synchronization method is applied to build a spatiotemporal chaotic cryptosystem that can transmit an encrypted image. The experimental results verify that the proposed image-encrypting cryptosystem has the advantages of large key space and high security against some traditional attacks.
Water/air performance analysis of a fluidic muscle

This paper deals with a comparative study on using water and air as actuation means for the control of a fluidic muscle (designed for air) and assesses the performance, particularly from a dynamic and energetic point of view. A medium with higher bulk modulus such as oil/water is believed to increase pressure and force bandwidths and reduce sensitivity to load variations, as is the case with conventional hydraulic stiff actuation systems. However in this application the inherent flexibility of the muscle plays a major role. Water has been chosen because of its non-flammability, environmental friendliness and the low solubility of air in it. The operating pressure range of the pneumatic muscle is 0-6 bar (typical range of a pneumatic system) that is well below typical operating pressures of hydraulic systems (typically over 100 bar). At such low pressures the dynamic behaviour of water is less predictable because of the higher likelihood of entrapped air in the water which physically occurs when operating at low pressures. This can majorly affect water bulk modulus and hence its dynamic performance. Therefore, the behaviour of the system in this unconventional pressure range for a liquid must be more thoroughly investigated. Theoretical and experimental analyses on a dedicated test rig have been carried out to assess these assumptions.
Role of medial cortical networks for anticipatory processing in obsessive‐compulsive disorder

Recurrent anticipation of ominous events is central to obsessions, the core symptom of obsessive‐compulsive disorder (OCD), yet the neural basis of intrinsic anticipatory processing in OCD is unknown. We studied nonmedicated adults with OCD and case matched healthy controls in a visual‐spatial working memory task with distractor. Magnetoencephalography was used to examine the medial cortex activity during anticipation of to‐be‐inhibited distractors and to‐be‐facilitated retrieval stimuli. In OCD anticipatory activation to distractors was abnormally reduced within the posterior cingulate and fusiform gyrus compared to prominent activation in controls. Conversely, OCD subjects displayed significantly increased activation to retrieval stimuli within the anterior cingulate and supplementary motor cortex. This previously unreported discordant pattern of medial anticipatory activation in OCD was accompanied by normal performance accuracy. While increased anterior cortex activation in OCD is commonly viewed as failure of inhibition, the current pattern of data implicates the operation of an anterior compensatory mechanism amending the posterior medial self‐regulatory networks disrupted in OCD. Hum Brain Mapp 33:2125–2134, 2012. © 2011 Wiley Periodicals, Inc.
Visualizing Bitcoin Flows of Ransomware: WannaCry One Week Later

Because of its pseudo-anonimity and decentralisation characteristics, bitcoin payments are often a tool utilised by ransomware: this kind of malware infects a victim computer by encrypting some/all its data and/or denying the access to it. Then, the victim has to pay a given amount of bitcoins to see all the blocked functionalities restored. The goal of this paper is to visualise these bitcoin transactions, and in particular we focus on the e(cid:11)ects of one of such ransomware, i.e., WannaCry , one/two weeks after its di(cid:11)usion. We exploit BlockChainVis , a tool for visualising (cid:13)ows of bitcoins through the use of Visual Analytics.
Inferring fundamental value and crash nonlinearity from bubble calibration

Identifying unambiguously the presence of a bubble in an asset price remains an unsolved problem in standard econometric and financial economic approaches. A large part of the problem is that the fundamental value of an asset is, in general, not directly observable and it is poorly constrained to calculate. Further, it is not possible to distinguish between an exponentially growing fundamental price and an exponentially growing bubble price. In this paper, we present a series of new models based on the Johansen–Ledoit–Sornette (JLS) model, which is a flexible tool to detect bubbles and predict changes of regime in financial markets. Our new models identify the fundamental value of an asset price and a crash nonlinearity from a bubble calibration. In addition to forecasting the time of the end of a bubble, the new models can also estimate the fundamental value and the crash nonlinearity, meaning that identifying the presence of a bubble is enabled by these models. In addition, the crash nonlinearity obtained in the new models presents a new approach to possibly identify the dynamics of a crash after a bubble. We test the models using data from three historical bubbles ending in crashes from different markets. They are the Hong Kong Hang Seng index 1997 crash, the S&P 500 index 1987 crash (Black Monday) and the Shanghai Composite index 2009 crash. All results suggest that the new models perform very well in describing bubbles, forecasting their ending times and estimating fundamental value and the crash nonlinearity. The performance of the new models is tested under both the Gaussian residual assumption and non-Gaussian residual assumption. Under the Gaussian residual assumption, nested hypotheses with the Wilks' statistics are used and the p-values suggest that models with more parameters are necessary. Under the non-Gaussian residual assumption, we use a bootstrap method to obtain type I and II errors of the hypotheses. All tests confirm that the generalized JLS models provide useful improvements over the standard JLS model.
Do Anesthesiologists Know What They Are Doing? Mining a Surgical Time-Series Database to Correlate Expert Assessment with Outcomes

Anesthesiologists are taught to carefully manage patient vital signs during surgery. Unfortunately, there is little empirical evidence that vital sign management, as currently practiced, is correlated with patient outcomes. We seek to validate or repudiate current clinical practice and determine whether or not clinician evaluation of surgical vital signs correlate with outcomes. Using a database of over 90,000 cases, we attempt to determine whether those cases that anesthesiologists would subjectively decide are “low quality” are more likely to result in negative outcomes. The problem reduces to one of multi-dimensional time-series classification. Our approach is to have a set of expert anesthesiologists independently label a small number of training cases, from which we build classifiers and label all 90,000 cases. We then use the labeling to search for correlation with outcomes and compare the prevalence of important 30-day outcomes between providers. To mimic the providers’ quality labels, we consider several standard classification methods, such as dynamic time warping in conjunction with a kNN classifier, as well as complexity invariant distance, and a regression based upon the feature extraction methods outlined by Mao et al. 2012 (using features such as time-series mean, standard deviation, skew, etc.). We also propose a new feature selection mechanism that learns a hidden Markov model to segment the time series; the fraction of time that each series spends in each state is used to label the series using a regression-based classifier. In the end, we obtain strong, empirical evidence that current best practice is correlated with reduced negative patient outcomes. We also learn that all of the experts were able to significantly separate cases by outcome, with higher prevalence of negative 30-day outcomes in the cases labeled as “low quality” for almost all of the outcomes investigated.
Adaptive Sliding Motion Tracking Control of Piezo-Driven Flexure-Based Mechanism

This paper presents an adaptive sliding motion tracking control methodology for a flexure-based micro/nano manipulator driven by a piezoelectric actuator. This control methodology is proposed for tracking desired motion trajectories in view of the problems of unknown or uncertain system parameters, non-linearities including the hysteresis effect, and external disturbances in the system. In this paper, a lumped parameter dynamic model is established for the formulation of the proposed control methodology. The convergence of the position and velocity tracking errors to zero is assured by the approach in the presence of the aforementioned conditions. The stability of the closed-loop system is proven theoretically, and a precise tracking performance in following a desired motion trajectory is demonstrated in the experimental study.
Opinion within opinion: segmentation approach for urdu sentiment analysis

In computational linguistics, sentiment analysis facilitates classification of opinion as a positive or a negative class. Urdu is a widely used language in different parts of the world and classification of the opinions given in Urdu language is as important as for any other language. The literature contains very restricted research for sentiment analysis of Urdu language and mainly Bag-of-Word model dominates the research methods used for this purpose. The Bag-of-Word based models fail to classify a subset of the complex sentiments; the sentiments with more than one opinion. However, no known literature is available which identifies and utilizes sub-opinion level information. In this paper, we proposed a method based on subopinions within the text to determine the overall polarity of the sentiment in Urdu language text. The proposed method classifies a sentiment in three steps, First it segments the sentiment into two fragments using a set of hypotheses. Next it calculates the orientation scores of these fragments independently and finally estimates the polarity of the sentiment using scores of the fragments. We developed a computational model that empirically evaluated the proposed method. The proposed method increases the precision by 8.46%, recall by 37.25% and accuracy by 24.75%, which is a significant improvement over the existing techniques based on Bag-of-Word model.
Determining what is important for sustainability: scoping processes of sustainability assessments

ABSTRACT Over recent decades, there has been a significant proliferation of types of impact assessments. While some argue that this is threatening future use of impact assessments, sustainability assessments have emerged as a potential approach to bridge these diverse approaches. This research focuses on examining sustainability assessments at the project level, looking specifically at scoping practices key to integration. Nine multinational enterprises operating within Indonesia are studied, utilising a case study methodology with semi-structured interviews with 32 respondents. Findings emphasise that while these multinationals sought to address key regulatory requirements through their scoping practices, international standards and global sustainability platforms were critical in informing the practices of these organisations. The recognition of these standards and guidelines saw them addressing a broad range of key sustainability issues; also using prescribed techniques to engage with stakeholders and identify the most critical sustainability issues to focus on in assessment. There was integration of scoping processes through different levels and across the organisations, which were generally managed by teams providing sustainability expertise, including through affiliate personnel for local contextualisation. Abbreviation AMDAL - Analisis Mengenai Dampak Lingkungan (EIA); BAPEDALDA - provincial/regional-level of the Environmental Impact Management Agency; CAQDAS – computer assisted data analysis software; CSR – corporate social responsibility; EIA – environmental impact assessment; EU – European Union; FDI – foreign direct investment; GRI – Global Reporting Initiative; ILO – International Labour Organization; MCA – multicriteria analysis; MNE – multinational enterprise; MOE - Ministry of Environment (now Ministry of Environment and Forestry); NGO – non-government organisation; OECD – Organisation for Economic Cooperation and Development; OH&S – occupational health and safety; SPPL - Letter of Statement on Environmental Management Effort; UKL – Environmental Management Effort; UN – United Nations; UNGC – United Nations Global Compact; UPL - Environmental Controlling Effort.