Miracle-dz/UniFAR-FTUs huggingface dataset:
The value of the clinical impression in recognizing and treating sepsis patients in the emergency department

Objectives Immediate bedside recognition of sepsis in the emergency department (ED) enables early treatment. This study aims to investigate whether the clinical impression score of different health care providers (a) is a good predictor of the severity of sepsis, (b) is mutually agreed, and (c) correlates with the treatment provided in the ED. Methods We performed a prospective observational study in the ED of a tertiary teaching hospital over a 3-month period. The vital signs of all patients of at least 18 years presenting with suspected infection or sepsis were measured on arrival at the ED. In patients with at least one of the ‘Systemic Inflammatory Response Syndrome’ criteria, the nurse, resident, and attending physician assigned a clinical impression score for the degree of acute illness, ranging from 1 (not ill) to 10 (extremely ill). Additional information collected included demographic and treatment data. Results We included 123 patients with sepsis and 11 patients with a (suspected) infection with one ‘Systemic Inflammatory Response Syndrome’ criterion. The clinical impression scores of all health care providers increased significantly between the infection without sepsis, mild sepsis, and severe sepsis groups. The agreement between the health care providers ranged from moderate to good (weighted &kgr; 0.54–0.62). The clinical impression score correlated with time to antibiotics (R=−0.33, P=0.001), amount of volume therapy (R=0.61–0.64, P⩽0.001), and amount of oxygen therapy (R=0.58–0.63, P⩽0.001). Conclusion The clinical impression score is associated with the severity of sepsis, is mutually agreed between the different health care providers and is correlated with sepsis treatment provided in the ED.
The Effect of Government Expenditures on Economic Growth. the Case of Albania

One of the main issues of economic policy and government is to ensure a sustainable economic growth of a country.Economic growth has been at the center of every government in place since at least year 2000.Though for this teen-year ,growth values were satisfactory in Albania, the macroeconomic situation changed in 2009,when appeared the elements of the global crisis. Economic global crisis has awakened interest in the case of fiscal policy.Fiscal policy and monetary policy as well, are two basci components of state economic policy which are used for macroeconomic purposes:influence of gross domestic product, the level of enmployment, income and price level. The two main instruments of fiscal policy are government expenditures and taxes. Government expenditures are considered as the most powerful weapon available to fiscal policy makers, especially in developing countries such as Albania. During the last century , governments have spent more and more in relation to their national income. This increase in government spending can be explained by the impact that this variable can have on the economic growth of a country? In fact ,about the connection between the government spending and the economic growth of a country various studies seem full of contradictions.This conflict is explained by changes in terms of definitions and from the differencies of the various countries included in these studies. The objective of this study is to give an appropriate answer to the question : Can government spending have the potential to impact and stimulate economic growth? How the changes of the size of the fiscal policy instruments have affected indicators of economic growth in Albania? This article will focus on the role that the fiscal policy has on economic growth , especially in our country, reviewing economic growth theories, debates about the effectiveness of fiscal policy , and active fiscal policy. Finally some suggestions for the future addressing the government expenditures towards priority sectors.
OXIDATION OF CAFFEINE BY CYP1A2: ISOTOPE EFFECTS AND METABOLIC SWITCHING

Caffeine (1,3,7-trimethylxanthine) has previously been shown to undergo metabolic switching in vivo when the N-1 or the N-7 methyl groups were trideuteromethylated [Horning et al. (1976) Proceedings of the Second International Conference on Stable Isotopes, pp 41–54]. We have examined the effect of replacing the N-3 methyl group with a trideuteromethyl group. The corresponding isotope effects can then be used to distinguish the kinetic mechanism by which four primary metabolites can be formed from one substrate by one cytochrome P450 (P450). We have synthesized 3-CD3-caffeine and 3-CD3-7-CD3-caffeine as well as trideuteromethylated analogs of each of the in vitro metabolites formed by cytochrome P4501A2. The observed competitive isotope effects for the metabolites, which do not result from deuterium abstraction (theobromine, theophylline), demonstrate that the nondissociative mechanism applies to caffeine metabolism by cytochrome P4501A2. Thus, there must be equilibration of the kinetically distinguishable activated P450-substrate complexes at rates competitive with hydrogen abstraction. The true isotope effects for the N-3 demethylation of caffeine were derived from the ratios of the amount of paraxanthine relative to the amount of theobromine or theophylline. The resultant ratios indicate that these isotope effects are essentially intrinsic. Observation of the isotope effects on N-3 demethylation was facilitated by branching to the minor in vitro metabolites as well as water formation. Product release is not rate-limiting for this system.
Deep learning lane marker segmentation from automatically generated labels

Reliable lane detection is a fundamental necessity for driver assistance, driver safety functions and fully automated vehicles. Based on other detection and classification tasks, deep learning based methods are likely to yield the most accurate outputs for detecting lane markers, but require vast amounts of labeled data. We propose to train a deep neural network for detecting lane markers in camera images without manually labeling any images. To achieve this, we project high definition maps for automated driving into our image and correct for misalignments due to inaccuracies in localization and coordinate frame transformations. The corrections are performed by calculating the offset between features within our map and detected ones in the images. By using detections in the actual image for refining the projections, our labels become close to pixel perfect. After a fast, visual quality check, our projected lane markers can be used for training a fully convolutional network to segment lane markers in images. A single worker can easily generate 20,000 of those labels within a single day. Our fully convolutional network is trained only on automatically generated labels. All of our detections are based solely on gray-scale mono camera inputs without any additional information. The resulting network regularly detects clean lane markers at distances of around 150 meters on a 1 Megapixel camera.
Antidepressant-like and anxiolytic-like effects of hydrogen sulfide in streptozotocin-induced diabetic rats through inhibition of hippocampal oxidative stress

Depression is highly prevalent in individuals with diabetes, and depressive symptoms are less responsive to current antidepressant therapies. Oxidative stress plays a major role both in the pathogenesis of diabetes and in major depression and anxiety disorders. Hydrogen sulfide (H2S), the third gaseous mediator, is a novel signaling molecule in the brain that has both antioxidative activity and antidepressant-like and anxiolytic-like effects. We hypothesized that H2S could produce antidepressant-like and anxiolytic-like effects in diabetic patients through its antioxidative effect. To test this hypothesis, we generated streptozotocin (STZ)-induced diabetic rats. We found that H2S alleviated depressive-like behaviors of STZ-induced diabetic rats in the forced swimming and tail suspension tests and reduced their anxiety-like behaviors in the elevated plus maze test. We also found that H2S significantly reduced levels of malondialdehyde and 4-hydroxynonenal and elevated levels of superoxide dismutase and reduced glutathione in the hippocampus of STZ-induced diabetic rats. The results provide evidence for antidepressant-like and anxiolytic-like effects of H2S in STZ-induced diabetic rats and suggest that the therapeutic effects may result from inhibition of hippocampal oxidative stress. These findings suggest that elevating H2S signaling is a potential target for treatment of depressive and anxiety disorders related to diabetes.
Optimized harmonic current control strategy for nonlinearities compensation in multiphase AC drives

Low-order odd harmonics are particularly problematic in multiphase drives, due to the small impedance in the no-torque subspaces. The harmonics can be compensated by proportional-integral controllers in multiple synchronous reference frames (SRFs). In three-phase systems, the computational burden of such scheme is often avoided by implementing instead resonant controllers (RCs) tuned at the harmonics that are multiples of six in an SRF rotating with the fundamental frequency. This paper extends that harmonic current control strategy to symmetrical machines of any phase number. The optimum frequencies for the SRFs and for the RCs in each plane, so that the total number of RCs is minimized, are assessed. Simulation results validate the theory.
Optimal Design of Superconducting Motor to Improve Power Density Using 3D EMCN and Response Surface Methodology

This paper proposes an effective design process for 1 MW HTS superconducting motor by using 3-dimensional equivalent magnetic circuit network method (3D EMCN) and response surface methodology (RSM). During the process, 3D EMCN is used with a simplified 3D analysis model to get electric parameters in short time. RSM is used for the motor optimal design to improve power density. The usefulness of this method is verified through the comparison of the performances of the optimal geometry and those of the initial geometry
Observed/revealed willingness to pay for QALYs in older adults: Evidence from planned commonly used surgical procedures

ABSTRACT Objectives: Published estimates of willingness to pay (WTP) for quality adjusted life years (QALYs) based on elicited preferences vary widely, especially across health procedures. The study evaluated the revealed WTP for QALYs by older adult patients who paid fully out-of-pocket for common inpatient procedures in the United States. Methods: Patient-level discharge data were from academic medical center members of the University Health System Consortium Clinical Data Base from 2005 to 2015 (now Vizient) for patients who paid ‘cash-in-full. ’ The median, 25th percentile, and 75th percentile of charges, payments, and payment to charge ratio were examined and combined with available measures on QALYs by procedure. Results: Among patients over age 50 from 22 academic medical centers there were 846 self-pay patients, and the majority were international. The mean out-of-pocket payment was $57731 and the payment to charge ratio was 0.53. For the five procedures with available QALYs, the lower bound median payment based estimates of WTP ranged from $2949 for PTCA to $15441 for replacement or repair of aortic valve. Conclusions: The study was designed to provide lower bound estimates of revealed preferences for QALYs. WTP and how it should intersect with payment policy remains an important area for future research.
Inhibition of Listeria monocytogenes by using bacteriocin PA-1 produced by Pediococcus acidilactici PAC 1.0

The bacteriocin produced by Pediococcus acidilactici PAC 1.0, previously designated PA-1 bacteriocin, was found to be inhibitory and bactericidal for Listeria monocytogenes. A dried powder prepared from PAC 1.0 culture supernatant fortified with 10% milk powder was found to contain bacteriocin activity. An MIC against L. monocytogenes and lytic effects in broth cultures were determined. Inhibition by PA-1 powder occurred over the pH range 5.5 to 7.0 and at both 4 and 32 degrees C. In addition, inhibition of L. monocytogenes was demonstrated in several food systems including dressed cottage cheese, half-and-half cream, and cheese sauce.
Surviving Parents’ Influence on Adult Children’s Depressive Symptoms Following the Death of a First Parent

Parents and children are linked across the life course, and they share common experiences. This article focuses on the bereavement experience of adult children’s loss of a first parent during adulthood and examines the downward influence of emotional closeness with a surviving parent on adult children’s depressive symptoms following loss. Analyses are based on adult children who experienced the death of a first parent (N = 227), drawn from the Longitudinal Study of Generations, a study of three-and four-generation families from Southern California. Multilevel lagged dependent variable models indicate that an emotionally close relationship with a surviving parent is related with fewer post-bereavement depressive symptoms when a mother survives a father, but not vice versa. This analysis extends the theory of linked lives and highlights the mutual influence parents and children exert, as well as the complex role of gender in shaping family relationships.
Subunit structure of islet-activating protein, pertussis toxin, in conformity with the A-B model.

The subunit structure of islet-activating protein (IAP), pertussis toxin, has been analyzed to study a possibility that this protein is one of the A-B toxins [Gill, D. M. (1978) in Bacterial Toxins and Cell Membranes (Jeljaszewicz, J., & Wadstrom, T., Eds.) pp 291-332, Academic Press, New York]. Heating IAP with 1% sodium dodecyl sulfate caused its dissociation into five dissimilar subunits named S-1 (with a molecular weight of 28 000), S-2 (23 000), S-3 (22 000), S-4 (11 700), and S-5 (9300), as revealed by polyacrylamide gel electrophoresis; their molar ratio in the native IAP was 1:1:1:2:1. The molecular weight of IAP estimated by equilibrium ultracentrifugation was 117 000 which was not at variance with the value obtained by summing up molecular weights of the constituent subunits. The preparative separation of these IAP subunits was next undertaken; exposure of IAP to 5 M ice-cold urea for 4 days followed by column chromatography with carboxymethyl-Sepharose caused sharp separation of S-1 and S-5, leaving the other subunits as two dimers. These dimers were then dissociated into their constituent subunits, i.e., S-2 and S-4 for one dimer and S-3 and S-4 for the other, after 16-h exposure to 8 M urea; these subunits were obtained individually upon further chromatography on a diethylaminoethyl-Sepharose column. Subunits other than S-1 were adsorbed as a pentamer by a column using haptoglobin as an affinity adsorbent. The same pentamer was obtained by adding S-5 to the mixture of two dimers. Neither this pentamer nor other oligomers (or protomers) exhibited biological activity in vivo. Recombination of S-1 with the pentamer at the 1:1 molar ratio yielded a hexamer which was identical with the native IAP in electrophoretic mobility and biological activity to enhance glucose-induced insulin secretion when injected into rats. In the broken-cell preparation, S-1 was biologically as effective as the native IAP; both catalyzed ADP-ribosylation of a protein in membrane preparations from rat C6 glioma cells. In conclusion, IAP is an oligomeric protein consisting of an A (active) protomer (the biggest subunit) and a B (binding) oligomer which is produced by connecting two dimers by the smallest subunit in a noncovalent manner. Rationale for this terminology is discussed based on the A-B model.
Natural Language Processing and Graph Theory: Making Sense of Imaging Records in a Novel Representation Frame

Background A concise visualization framework of related reports would increase readability and improve patient management. To this end, temporal referrals to prior comparative exams are an essential connection to previous exams in written reports. Due to unstructured narrative texts' variable structure and content, their extraction is hampered by poor computer readability. Natural language processing (NLP) permits the extraction of structured information from unstructured texts automatically and can serve as an essential input for such a novel visualization framework. Objective This study proposes and evaluates an NLP-based algorithm capable of extracting the temporal referrals in written radiology reports, applies it to all the radiology reports generated for 10 years, introduces a graphical representation of imaging reports, and investigates its benefits for clinical and research purposes. Methods In this single-center, university hospital, retrospective study, we developed a convolutional neural network capable of extracting the date of referrals from imaging reports. The model's performance was assessed by calculating precision, recall, and F1-score using an independent test set of 149 reports. Next, the algorithm was applied to our department's radiology reports generated from 2011 to 2021. Finally, the reports and their metadata were represented in a modulable graph. Results For extracting the date of referrals, the named-entity recognition (NER) model had a high precision of 0.93, a recall of 0.95, and an F1-score of 0.94. A total of 1,684,635 reports were included in the analysis. Temporal reference was mentioned in 53.3% (656,852/1,684,635), explicitly stated as not available in 21.0% (258,386/1,684,635), and omitted in 25.7% (317,059/1,684,635) of the reports. Imaging records can be visualized in a directed and modulable graph, in which the referring links represent the connecting arrows. Conclusions Automatically extracting the date of referrals from unstructured radiology reports using deep learning NLP algorithms is feasible. Graphs refined the selection of distinct pathology pathways, facilitated the revelation of missing comparisons, and enabled the query of specific referring exam sequences. Further work is needed to evaluate its benefits in clinics, research, and resource planning.
Cellular automata simulation on FPGA for training neural networks with virtual world imagery

We present ongoing work on a tool that consists of two parts: (i) A raw micro-level abstract world simulator with an interface to (ii) a 3D game engine, translator of raw abstract simulator data to photorealistic graphics. Part (i) implements a dedicated cellular automata (CA) on reconfigurable hardware (FPGA) and part (ii) interfaces with a deep learning framework for training neural networks. The bottleneck of such an architecture usually lies in the fact that transferring the state of the whole CA significantly slows down the simulation. We bypass this by sending only a small subset of the general state, which we call a 'locus of visibility', akin to a torchlight in a darkened 3D space, into the simulation. The torchlight concept exists in many games but these games generally only simulate what is in or near the locus. Our chosen architecture will enable us to simulate on a micro level outside the locus. This will give us the advantage of being able to create a larger and more fine-grained simulation which can be used to train neural networks for use in games.
AIS Electronic Library (AISeL)

(REQUIRED) Consumer health information portals (HIP) are a popular means to provide quality health information via the Web. However complex usage problems in HIPs are still a major barrier to their success. A usage-driven approach, which places emphasis on improving online services based on learnings from the data of the interactions between users and the system, is crucial to ensuring sustainable and user-centred online health provision. Inspired by this idea, we present a taxonomy of usage problems that encompasses the dimensions of the content, the systems and users, focusing on a holistic understanding of usage problems. Our taxonomy is grounded on a literature analysis empirically validated through an analysis of usage-data captured from a consumer health information portal, operational for the past five years. By exploring how usage data highlights user problems, we also present strategies for health portal improvements based on better understandings of usage data. Benefits of usage-driven health portals in terms of smart learning capabilities to improve content and user satisfaction are discussed.
Do I Switch? Understanding Users' Intention to Switch between Social Network Sites

With the growing popularity of online social network sites (SNSs) and increasing competition among the leading players, users' switching behavior between different SNSs becomes an issue of great interest to information systems researchers and practitioners, as user retention is the key to the success of SNSs. In this paper, we draw from the push-pull-mooring model and the uses and gratification theory to investigate factors influencing SNS users' switching behavior. The results of a survey on current Facebook users show that both dissatisfaction with the original SNS and relative attractiveness of the competitive SNS exert strong positive impact on users' decision to switch to the competitive SNS. Moreover, switching costs not only reduce users' switching intention directly but also mitigate the impact of dissatisfaction and relative attractiveness on users' switching intention. This study has important contributions both to research and to practice.
Altered neurochemical markers in Rett's syndrome

Rett's syndrome (RS) is a neurologic disorder associated with severe mental deficiency and neurologic manifestations of cortical and extrapyramidal origin. The present report is a preliminary postmortem brain study that compares the levels of endogenous biogenic amines and selected neurotransmitter receptors in five cases with RS and six normal controls of similar age. The level of choline acetyltransferase activity was reduced in several cortical and subcortical regions. Endogenous levels of dopamine in the superior frontal and superior temporal gyri, occipital cortex, and putamen were reduced. The changes in specific neurotransmitter markers, particularly those associated with the basal ganglia and cortex, may underlie the progressive deterioration in motor and cognitive function characteristic of this progressive disorder.