Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of blunting astrocyte activity on hippocampal synaptic plasticity in a mouse model of early Alzheimer's disease based on amyloid‐β peptide exposure

Amyloid‐β peptides (Aβ) accumulate in the brain since early Alzheimer's disease (AD) and dysregulate hippocampal synaptic plasticity, the neurophysiological basis of memory. Although the relationship between long‐term potentiation (LTP) and memory processes is well established, there is also evidence that long‐term depression (LTD) may be crucial for learning and memory. Alterations in synaptic plasticity, namely in LTP, can be due to communication failures between astrocytes and neurons; however, little is known about astrocytes' ability to control hippocampal LTD, particularly in AD‐like conditions. We now aimed to test the involvement of astrocytes in changes of hippocampal LTP and LTD triggered by Aβ1–42, taking advantage of L‐α‐aminoadipate (L‐AA), a gliotoxin that blunts astrocytic function. The effects of Aβ1–42 exposure were tested in two different experimental paradigms: ex vivo (hippocampal slices superfusion) and in vivo (intracerebroventricular injection), which were previously validated to impair memory and hippocampal synaptic plasticity, two features of early AD. Blunting astrocytic function with L‐AA reduced LTP and LTD amplitude in hippocampal slices from control mice, but the effect on LTD was less evident, suggesting that astrocytes have a greater influence on LTP than on LTD under non‐pathological conditions. However, under AD conditions, blunting astrocytes did not consistently alter the reduction of LTP magnitude, but reverted the LTD‐to‐LTP shift caused by both ex vivo and in vivo Aβ1–42 exposure. This shows that astrocytes were responsible for the hippocampal LTD‐to‐LTP shift observed in early AD conditions, reinforcing the interest of strategies targeting astrocytes to restore memory and synaptic plasticity deficits present in early AD.
Psoas Cross-Sectional Measurements Using Manual CT Segmentation before and after Endovascular Aortic Repair (EVAR)

Sarcopenia has been associated with an increased incidence of adverse outcomes, including higher mortality, after endovascular aortic repair (EVAR). We aim to use computed tomography (CT) to quantify changes in total psoas muscles area (PMA) and psoas muscle density (PMD) after EVAR, and to evaluate the reproducibility of both measurements. PMA and PMD were assessed via manual segmentation of the psoas muscle on pre- and post-operative CT scans belonging to consecutive patients who underwent EVAR. Wilcoxon test was used to compare PMA and PMD before and after EVAR, and inter- and intra-reader agreements of both methods were evaluated through Bland–Altman analysis. A total of 50 patients, 42 of them males (84%), were included in the study. PMA changes from 1243 mm2 (1006–1445 mm2) to 1102 mm2 (IQR 937–1331 mm2), after EVAR (p < 0.001). PMD did not vary between pre-EVAR (33 HU, IQR 26.5–38.7 HU) and post-EVAR (32 HU, IQR 26–37 HU, p = 0.630). At inter-reader Bland–Altman analysis, PMA showed a bias of 64.0 mm2 and a coefficient of repeatability (CoR) of 359.2 mm2, whereas PMD showed a bias of −2.43 HU and a CoR of 6.19 HU. At intra-reader Bland–Altman analysis, PMA showed a bias of −81.1 mm2 and a CoR of 394.6 mm2, whereas PMD showed a bias of 1.41 HU and a CoR of 6.36 HU. In conclusion, PMA decreases after EVAR. A good intra and inter-reader reproducibility was observed for both PMA and PMD. We thus propose to use PMA during the follow-up of patients who underwent EVAR to monitor muscle depletion after surgery.
Current Error Vector Based Prediction Control of Currents in Segment Winding Permanent Magnet Linear Synchronous Motor

To maintain the characteristics such as greater thrust,higher efficiency without reducing the thrust stability,this paper proposes a segment winding permanent magnet linear synchronous motor(SW-PMLSM),whose iron core is continuous,whereas winding is divided.The discrete system model of the motor was derived.With the definition of the current error vector and selection of the value function,the theory of the current error vector based prediction control for the motor currents was explained clearly.According to the winding segment structure,the motion region of the mover was divided into five zones,in which the implementation of the current predictive control method was proposed.The experimental results show that the current control effect has good dynamic response and the mover passes across the winding boundary successfully.
Trajectory Optimization and Channel Allocation for Delay Sensitive Secure Transmission in UAV-Relayed VANETs

This paper investigates the delay sensitive secure transmission problem in unmanned aerial vehicle (UAV)-relayed vehicular ad hoc networks (VANETs). Specifically, we take the security assurance into account and formulate this problem as a total information delay minimization problem by optimizing the UAV relay trajectory and channel allocation. To tackle this optimization problem, we propose an alternating optimization framework, where the UAV relay trajectory is solved by the Newton method, and the channel allocation is obtained by relax-and-round and sequential convex approximation methods. Finally, simulation results show the performance improvement of our algorithm compared with the current works in terms of the total information delay.
Chemical Composition of Pinus nigra Arn. Unripe Seeds from Bulgaria

The present paper aims to investigate the chemical composition of unripe black pine seeds obtained from Bulgaria. The lipid fraction was evaluated in unripe seeds, and the cellulose, total carbohydrates, glucose, fructose, and sucrose were evaluated in seedcakes. The major fatty acid identified in the Pinus nigra seed oil was unsaturated linoleic acid (44.2%), followed by the saturated palmitic acid (31.2%). The amount of unsaturated pinolenic (10.5%) and oleic acids (8.8%) was also rather high. The amino acid composition of the protein fraction of seedcakes was also determined. The amino acid composition was represented mainly by asparagine (3.92 mg/g), serine (3.79 mg/g), alanine (3.65 mg/g), arginine (3.32 mg/g), phenylalanine (2.98 mg/g), lysine (2.85 mg/g), proline (2.69 g/mg), tryptophan (2.44 mg/g), valine (2.33 mg/g), isoleucine (2.28 mg/g), and tyrosine (2.05 mg/g). The mineral content (N, P, K, Mg, Na, and Cu) of the seedcakes was evaluated, as the amount of K (8048.00 mg/kg) and Mg (172.99 mg/kg) were the highest in the samples. These findings emphasized the potential use of the unripe black pine seeds in different areas due to their chemical importance and values.
Determination of some chemical properties of wild pear (Pyrus spinosa Forsk.)

Wild pear plant species Pyrus spinosa Forsk. , naturally grown in woodlands in Turkey, are one of the most important wild fruits consumed by local people as food, as well as used for medical purposes. In this study, some chemical properties were determined such as fruit seed and fruit pulp antioxidant and antimicrobial activities, fruit seed fatty acid components of Pyrus spinosa determined, which grow naturally in Ödemiş, İzmir, in the south of Turkey. The qualitative and quantitative analyses of fatty acid components of fruit seed of P. spinosa were determined by GC/MS analysis. A total of 16 fatty acids in the fruit seed were found in the analysis results and 44.8% linoleic acid (C18:2n6c), 40.5% oleic acid (C18:1n9c), and 7.6% palmitic acid (C16:0) components were found in higher proportions. Free radical removal effects of fruit seed and fruit pulp extracts were determined using the DPPH method. The antimicrobial activity of fruit pulp extract of P. spinosa was determined by the disk diffusion method against E. coli, S. aureus, and C. albicans. This study revealed that the fruit pulp and fruit seed of P. spinosa, which had a significant level of antioxidant activity, antimicrobial activity, and fruit seed had high levels fatty acids components.
Oligoclonal Band Straightening Based on Optimized Hierarchical Warping for Multiple Sclerosis Diagnosis

The detection of immunoglobulin G (IgG) oligoclonal bands (OCB) in cerebrospinal fluid (CSF) by isoelectric focusing (IEF) is a valuable tool for the diagnosis of multiple sclerosis. Over the last decade, the results of our clinical research have suggested that tears are a non-invasive alternative to CSF. However, since tear samples have a lower IgG concentration than CSF, a sensitive OCB detection is therefore required. We are developing the first automatic tool for IEF analysis, with a view to speeding up the current visual inspection method, removing user variability, reducing misinterpretation, and facilitating OCB quantification and follow-up studies. The removal of band distortion is a key image enhancement step in increasing the reliability of automatic OCB detection. Here, we describe a novel, fully automatic band-straightening algorithm. The algorithm is based on a correlation directional warping function, estimated using an energy minimization procedure. The approach was optimized via an innovative coupling of a hierarchy of image resolutions to a hierarchy of transformation, in which band misalignment is corrected at successively finer scales. The algorithm’s performance was assessed in terms of the bands’ standard deviation before and after straightening, using a synthetic dataset and a set of 200 lanes of CSF, tear, serum and control samples on which experts had manually delineated the bands. The number of distorted bands was divided by almost 16 for the synthetic lanes and by 7 for the test dataset of real lanes. This method can be applied effectively to different sample types. It can realign minimal contrast bands and is robust for non-uniform deformations.
A Framework for Governance Capacity: A Broad Perspective on Steering Efforts in Society

In the network society, the capacity to deal with societal issues is spread among interacting actors in governance networks. Knowledge about this capacity, often called “governance capacity,” is still fragmented and quite incoherent. The aim of this study is therefore to gain an integrated understanding of governance capacity. To do this, we conducted a literature review and organized focus groups. This resulted in the selection of five elements of governance capacity: (1) collective action, (2) coordination, (3) resilience, (4) learning, and (5) resources. We used these elements to form the first contours of a governance capacity framework.
Temporal Scaling of Streamflow Elasticity to Precipitation: A Global Analysis

Streamflow elasticity to precipitation, defined as the percent change of streamflow resulting from a 1% change in precipitation, is sometimes used as an alternative to rainfall‐runoff models in climate impact analyses. Elasticity is usually estimated from long streamflow and precipitation series aggregated at annual time steps while the climate impact analyses are usually geared toward changes at decadal scales. The purpose of this paper is therefore to understand how the elasticity depends on the aggregation time scale and the process controls of such a dependence. We analyze streamflow records of 7,053 catchments around the world over the period 1950–2016, and select 5,327 with reliable elasticity estimates for aggregation time ranging from 13 to 60 months. We find a significant scaling of streamflow elasticity to precipitation with aggregation time in 66% of the catchments which is much larger than expected by chance. Positive scaling occurs much more frequently than negative scaling. More arid/less rainy catchments, less forested catchments and catchments with a large base flow contribution to streamflow are more frequently characterized by a positive scaling. A random forest classification model identifies aridity index, latitude, mean annual precipitation, the potential evapotranspiration seasonality, the base flow index and the precipitation seasonality as relevant explanatory variables of the scaling. We interpret the sign of the scaling by non‐linear runoff generation in arid regions, by the effect of climate modes and snow processes, and by the regulation capacity of vegetation to transpire more water if the past years were wet. It is suggested to use decadal elasticities instead of annual elasticities in climate impact analyses in order to account for their scaling behavior.
Methods for Financial Assessment of Renewable Energy Projects: A Review

The financial evaluation of renewable energy sources (RES) projects is well explored in the literature, but many different methods have been followed by different authors. Then, it is important to understand if and how these methods have been changing and what factors may have driven new approaches. Therefore, this article aims to explore the publications on the financial evaluation of RES projects from 2011 to 2020 and to present a critical analysis of the reviewed literature. The methods for evaluating RES projects were grouped into four categories: (i) traditional metrics based on net present value, internal rate of return, and payback period; (ii) levelized cost of electricity; (iii) return on investment approach; and (iv) real options analysis. A quantitative analysis was carried out considering aspects related to the relevance of the authors, productivity by country, and the most relevant journals for each of these groups. Then, a qualitative analysis of the main characteristics of the five most cited articles in each group was conducted. The results show that the more traditional methods are still widely used for the financial evaluation of RES projects. However, approaches based on the levelized cost and real options have been growing in importance to tackle the complex features of financial evaluation and comparison of RES projects.
Real-World Cost-Effectiveness of First-Line Gemcitabine Plus Nab-Paclitaxel vs FOLFIRINOX in Patients With Advanced Pancreatic Cancer

Abstract Background There are no randomized control trials (RCTs) comparing gemcitabine and nab-paclitaxel (Gem-Nab) and fluorouracil, folinic acid, irinotecan, oxaliplatin (FOLFIRINOX) for advanced pancreatic cancer (APC). Although it is well known that RCT-based efficacy often does not translate to real-world effectiveness, there is limited literature investigating comparative cost-effectiveness of Gem-Nab vs FOLFIRINOX for APC. We aimed to examine the real-world cost-effectiveness of Gem-Nab vs FOLFIRINOX for APC in Ontario, Canada. Methods This study compared patients treated with first-line Gem-Nab or FOLFIRINOX for APC in Ontario from April 2015 to March 2019. Patients were linked to administrative databases. Using propensity scores and a stabilizing weights method, an inverse probability of treatment weighted cohort was developed. Mean survival and total costs were calculated over a 5-year time horizon, adjusted for censoring, and discounted at 1.5%. Incremental cost-effectiveness ratio and net monetary benefit were computed to estimate cost-effectiveness from the public health-care payer’s perspective. Sensitivity analysis was conducted using the propensity score matching method. Results A total of 1988 patients were identified (Gem-Nab: n = 928; FOLFIRINOX: n = 1060). Mean survival was lower for patients in the Gem-Nab than the FOLFIRINOX group (0.98 vs 1.26 life-years; incremental effectiveness = −0.28 life-years [95% confidence interval = −0.47 to −0.13]). Patients in the Gem-Nab group incurred greater mean 5-year total costs (Gem-Nab: $103 884; FOLFIRINOX: $101 518). Key cost contributors include ambulatory cancer care, acute inpatient hospitalization, and systemic therapy drug acquisition. Gem-Nab was dominated by FOLFIRINOX, as it was less effective and more costly. Results from the sensitivity analysis were similar. Conclusions Gem-Nab is likely more costly and less effective than FOLFIRINOX and therefore not considered cost-effective at commonly accepted willingness-to-pay thresholds.
Between traditional lifestyle and late modern leisure: young second-home dwellers’ perspectives on Finnish cottage culture

ABSTRACT Young people have rarely been studied in the field of second-home research as active subjects, although they play an influential part in contemporary second-home tourism. Based on semi-structured interviews, this study seeks to address the scholarly gap in the existing literature by analysing the experiences of, and attitudes towards, second-home living among 12- to 17-year-old second-home dwellers vacationing in Mäntyharju, Finland. The study focuses on the second-home environment as a hybrid space enabling young cottagers to combine elements of a traditionalist lifestyle, outdoor recreation, and late modern technoscape in pursuit of pleasurable and restorative leisure. The findings suggest that young second-home dwellers see outdoor activities and rich natural surroundings, as well as intense familial communality and selected aspects of simple living, as the basis of an enjoyable second-home experience. At the same time, they complement these elements with the active use of mobile and entertainment technology, seeking a satisfying balance between the exotic and the ordinary. The results show that studying young second-home dwellers offers fresh new perspectives not only on second-home tourism and its ongoing changes but also on the leisure preferences of late modern youth in general.
Heart Attack Prediction System using Cascaded Neural Network

---Cardiovascular disease remains the biggest cause of deaths worldwide. The percentage v of premature death from this disease ranges from 4% in high income countries and 42 % in low income countries. This shows the importance of predicting heart disease at the early stage. In this paper, a new classification system is adopted for heart attack prediction at the early stage using the patient’s medical record. The information in the patient record are preprocessed initially using data mining techniques and then the attributes are classified using a cascaded neural network classifier. In the classification stage 13 attributes are given as input to the CNN classifier to determine the risk of heart attack. The proposed system will provide an aid for the physicians to diagnosis the disease in a more efficient way. The efficiency of the classifier is tested using the records collected from 270 patients. The results shows the proposed system can predict the likelihood of patients getting a heart attack in a more efficient and cost effective way.
Trajectory analysis for parking lot vacancy detection system

Taking a vacant parking lot in crowded metropolitan areas is a major problem especially with the huge number of vehicles. In this study, the authors provide a vision-based system for real-time management of parking spaces in the case of outdoor parking. Different real-world challenges may face these systems such as weather conditions, luminance variation, perspective distortion and inter-spaces occlusion. In this study, they propose a decisional module based on a tracking approach that determines in real time the state of the parking lots and localises the vacant parking spaces according to several extracted attributes. This decision is based on local characteristics of the parking spaces as well as the performed vehicles' events.
Sharp Zero-Queueing Bounds for Multi-Server Jobs

Multi-server jobs, which are jobs that occupy multiple servers simultaneously during service, are prevalent in today's computing clusters. But little is known about the delay performance of systems with multi-server jobs. In this paper, we consider queueing models for multi-server jobs in a scaling regime where the number of servers in the system becomes large. Prior work has derived upper bounds on the queueing probability in this scaling regime. But without proper lower bounds, the results cannot be used to differentiate between policies. We focus on the mean queueing time of multi-server jobs, and establish both upper and lower bounds under various scheduling policies. Our results show that a Priority policy achieves order optimality for minimizing mean queueing time, and the Priority policy is strictly better than the First-Come-First-Serve policy.
Reliability Prediction of Electronic Direct Current Transformer in HDVC System

Direct current on the transmission lines of the high-voltage direct current(HVDC)project is one of the most critical technical data for supervising the operating conditions and system control.Thus,Direct current transformer is the significant equipment of HDVC system.It should provide output signal to protect devices reliably,correctly and quickly.To estimate its reliability,this paper first presents the system structure of electronic direct current transformer briefly.Electronic direct current transformer is composed of the direct current shunt,optical links equipped with composite insulator,high-voltage processing unit and earth-potential processing unit,any faults of elements and devices in these parts can cause the direct current transformer in failure.Thus a serial reliability model is used to establish its reliability block diagram.Based on this reliability block diagram,the reliability mathematic model is deduced and detailed mathematics expression of failure rate and mean time between failures is presented.Using two methods-"part stress analysis method" and "part count method" proposed by America military handbook MIL-HDBK-217F notice 2 and China military standard GJB/Z 299B-1998,the failure rate of electronic direct current transformer can be predicted.The failure rate of electronic direct current transformer is about 15.51×10-6/h and mean time between failure is about 64474 hours.Otherwise,two critical points are found by reliability prediction :(1)the failure rate of the large power laser using for optical-powered is the uppermost influential factors of reliability of electronic direct current transformer;(2)the failure rate of composite insulator is secondary influential factors.
Shrinking Logs by Safely Discarding Commands

Logs are crucial to the development of dependable distributed applications. By logging entries on a sequential global log, systems can synchronize updates over distributed replicas and provide a consistent state recovery in the presence of faults. However, logs account for a signiﬁcant overhead on fault-tolerant applications' performance, and many studies present alternatives to alleviate servers from such costs. This paper proposes an approach to reduce log footprint by safely and efﬁciently discarding entries from logs. The expected beneﬁts are twofold: minimize durability costs and speed up recovery. Besides shrinking logging information, the proposed technique splits the log into several ﬁles and incorporates strategies to reduce logging overhead, such as batching and parallel I/O. The proposed approach was compared to a standard logging scheme using realistic workloads. Results demonstrate that our logging approach is capable to generate compressed logs and reduce recovery time, imposing half the throughput overhead of a standard logging scheme.