bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tropical cloud-radiative changes contribute to robust climate change-induced jet exit strengthening over Europe during boreal winter
Authors: Albern Nicole , Voigt Aiko , Pinto Joaquim G 
Published: July 2021

Abstract
The North Atlantic jet stream is projected to extend eastward towards Europe in boreal winter in response to climate change. We show that this response is robust across a hierarchy of climate models and climate change scenarios. We further show that cloud-radiative changes contribute robustly to the eastward extension of the jet stream in three atmosphere models, but lead to model uncertainties in the jet stream response over the North Atlantic. The magnitude of the cloud contribution depends on the model, consistent with differences in the magnitude of changes in upper-tropospheric cloud-radiative heating. We further study the role of regional cloud changes in one of the three atmosphere models, i.e. the ICON model. Tropical cloud-radiative changes dominate the cloud impact on the eastward extension of the jet stream in ICON. Cloud-radiative changes over the Indian Ocean, western tropical Pacific, and eastern tropical Pacific contribute to this response, while tropical Atlantic cloud changes have a minor impact. Our results highlight the importance of upper-tropospheric tropical clouds for the regional circulation response to climate change over the North Atlantic-European region and uncertainty therein.
Quasi-inversion of quantum and classical channels in finite dimensions
Authors: Shahbeigi Fereshte , Sadri Koorosh , Moradi Morteza , Życzkowski Karol , Karimipour Vahid 
Published: July 2021

Abstract
We introduce the concept of quasi-inverse of quantum and classical channels, prove general properties of these inverses and determine them for a large class of channels acting in an arbitrary finite dimension. Therefore we extend the previous results of Karimipour et al (2020 Phys. Rev. A 101 032109) to arbitrary dimensional channels and to the classical domain. We demonstrate how application of the proposed scheme can increase on the average the fidelity between a given random pure state and its image transformed by the quantum channel followed by its quasi-inversion.
Getting into hot water: Water quality in tropical lakes in relation to their utilisation
Authors: May L , Aura C Mulanda , Becker V , Briddon C L , Carvalho L R , Dobel A J , Jamwal P , Kamphuis B , Marinho M M , McGowan S , Nandini S , Nyamweya C , Ongore C , Sarma S S S , Wishart M J 
Published: July 2021

AbstractOver-exploitation of tropical lakes and reservoirs (‘lakes’) causes water quality problems that occur as a result of competing socio-economic demands and the presence of feedback loops within the system that exacerbate the situation. We review well documented case studies from Brazil, India, Indonesia, Kenya, Malaysia and Mexico to examine the effect that changes in water quality and quantity have had on the utilisation of these tropical lakes. By comparing the different approaches used to improve their sustainable management, we have found that nutrient enrichment is one of the most important and widespread water quality problems, causing adverse effects such as algal blooms, nuisance levels of aquatic plants, low oxygen levels and elevated greenhouse gas emissions. These effects restrict the use of these lakes for water supply, fisheries, recreation, tourism and wildlife. We conclude that tropical lakes require better management, urgently, to restore the ecosystem services that they deliver to man and nature. However, to be effective, the development of sustainable management programmes needs to be underpinned by reliable scientific evidence and the results of extensive stakeholder engagement activities. We note that, currently, there is little information available on how tropical lakes respond to management interventions that can be used to guide these activities. Further research is needed to address this knowledge gap.
Study on Hot Spot Detection Algorithm based on K-Means
Authors: ChenghaoDeng  , YuShen  , KanjianZhang  
Published: July 2021

Abstract
Solar energy is a widely used clean energy at present, and it is inexhaustible. As the main power generation device, photovoltaic modules play an important role in solar power generation. Among the various abnormalities of photovoltaic modules, the hot spot effect will not only reduce the power generation efficiency of photovoltaic modules, but even cause fires due to high temperatures. In this paper, k-means algorithm is adopted for photovoltaic hot spot detection. K-means is an unsupervised machine learning clustering algorithm, which clusters the pixel points of the image, and extracting the connected domain with the points with the shape similar to rectangular rectangle in the clustering, that is, obtaining the hot spot area. At the same time, this paper also uses the traditional computer vision MSER algorithm for experiments, compares the MSER algorithm with the K-means algorithm, and draws the conclusion that the traditional computer vision algorithm has low accuracy but high speed. Machine learning algorithms are accurate but fast.
New EOR Technology: Simultaneous Gas Alternating Gas (SGAG) injection
Authors: Edouard Mvomo N. , Dong Pingchuan , Okere Chinedu J. 
Published: July 2021

Abstract
A new oil recovery method known as Simultaneous Gas Alternating Gas (SGAG) injection that is based on the principle of the conventional Simultaneous Water Alternating Gas (SWAG) injection has been proposed in this study. The performance was observed via a simulation process based on data from an oil field of a shale oil reservoir. The effectiveness of SGAG was evaluated through a sensitivity analysis, and by observing its effect on oil recovery factor and ultimate oil recovery. The results of the sensitivity analysis show that (1) SGAG technique will improve the ultimate recovery factor compared to continuous gas injection; (2) Based on gravity segregation between two gases, oil recovery is enhanced; and (3) Because the produced CH4 can be reinjected and based on the availability of CO2, the possible SGAG combination of (CH4 + CO2) is more economically and feasible for a tank of Shale Oil reserve. This study provides a reliable basis for minimizing operating costs per unit CO2 injection volume and insight into cost-effectively enhanced oil recovery (EOR) technique.
Simulaneous Determination of Heavey Metals in 6 Kind of Mineral Water by ICP-MS
Authors: Yu Y D , Zhao M S , Li S G , Li Z Y , Zhu Y 
Published: July 2021

Abstract
A method for simultaneous determination of nine kinds of inorganic elements including Be, B, Ti, Co, V, Ni, Mo, Sb, Ba and Tl in mineral of six different mountains was established by inductively coupled plasma mass spectrometry (ICP-MS). The samples were analyzed directly after equilibration treatment. The results showed that the linearity ranged well among 0-200 ug/L with correlation coefficient above 0.9999.and the limit of detection was 0.03, 0.90, 0.40, 0.07, 0.03, 0.07, 0.06, 0.07, 0.30, 0.10 ug/L。 While the recoveries of spiked samples were between 88-110 % and the relative standard deviation (RSD) were 0 to 0.888 %. The method has simple operation, good reproducibility, no complicated pre-treatment steps, high sensitivity and reliable data, and can provide a reference for scientific selection of drinks to the residents.
Simultaneous multi-location wireless monitoring of sweat lactate trends
Authors: Gillan Liam , Teerinen Tuija , Suhonen Mika , Kivimäki Liisa , Alastalo Ari 
Published: July 2021

AbstractWearable device technologies for sweat analytics present a versatile application for monitoring physiological state, which can circumvent the requirement for inconvenient and invasive blood sampling. This paper reports a miniature electrochemical sensor platform for non-invasive and wireless real-time monitoring of lactate in exercise-induced human sweat. The conformal and low profile sensor platform is composed of (a) a flexible electronic readout tag with wireless charging and data acquisition, and (b) a disposable enzymatic amperometric biosensor patch with electrodes fabricated using high throughput roll-to-roll processing. Data were generated in real time from sensor response to lactate in exercise-induced sweat from multiple body regions simultaneously. The biosensor demonstrates current response proportional to lactate at physiological concentration range between 5 and 30 mM. This developed platform can be adapted for sensing of other sweat constituents including ions or metabolites, and therefore advances wearable technology for personalized physiological monitoring
What gets recorded, counts: dementia recording in primary care compared with a specialist database
Authors: Davis Katrina A S , Mueller Christoph , Ashworth Mark , Broadbent Matthew , Jewel Amelia , Molokhia Mariam , Perera Gayan , Stewart Robert J 
Published: July 2021

Abstract

Background
databases of electronic health records are powerful tools for dementia research, but data can be influenced by incomplete recording. We examined whether people with dementia recorded in a specialist database (from a mental health and dementia care service) differ from those recorded in primary care.

Methods
a retrospective cohort study of the population covered by Lambeth DataNet (primary care electronic records) between 2007 and 2019. Documentation of dementia diagnosis in primary care coded data and linked records in a specialist database (Clinical Records Interactive Search) were compared.

Results
3,859 people had dementia documented in primary care codes and 4,266 in the specialist database, with 2,886/5,239 (55%) documented in both sources. Overall, 55% were labelled as having Alzheimer’s dementia and 29% were prescribed dementia medication, but these proportions were significantly higher in those documented in both sources. The cohort identified from the specialist database were less likely to live in a care home (prevalence ratio 0.73, 95% confidence interval 0.63–0.85), have multimorbidity (0.87, 0.77–0.98) or consult frequently (0.91, 0.88–0.95) than those identified through primary care codes, although mortality did not differ (0.98, 0.91–1.06).

Discussion
there is under-recording of dementia diagnoses in both primary care and specialist databases. This has implications for clinical care and for generalizability of research. Our results suggest that using a mental health database may under-represent those patients who have more frailty, reflecting differential referral to mental health services, and demonstrating how the patient pathways are an important consideration when undertaking database studies.
The duties of impartiality, disclosure, and confidentiality: lessons from a London-seated arbitration
Authors: Leung Samuel Yee Ching , Chan Alex Chun Hei 
Published: July 2021

Abstract
Halliburton Company v Chubb Bermuda Insurance Ltd (formerly known as Ace Bermuda Insurance Ltd [2020] UKSC 48 is an important case not only to the UK but also to the international arbitration community for several reasons: first, it examines indispensable duties in international arbitration and for the first time recognises and explicates upon the duty of disclosure at the highest court of the United Kingdom; secondly, it addresses and clarifies key concepts in international arbitration; thirdly, it confirms the objective nature of the test of justifiable doubts which has wider implications for other arbitral forums; fourthly, it illustrates how the duties of impartiality, disclosure, and confidentiality interact with and affect each other and how the key concepts should be applied to this interaction; and finally, it lays down useful guidance for arbitrators. For these reasons, this case deserves close and careful examination. This article aims to explain the significance of the aforesaid and suggests that, in addition to what has been addressed, further judicial explanations are warranted in what other aspects.
Selecting gene features for unsupervised analysis of single-cell gene expression data
Authors: Sheng Jie , Li Wei Vivian 
Published: July 2021

AbstractSingle-cell RNA sequencing (scRNA-seq) technologies facilitate the characterization of transcriptomic landscapes in diverse species, tissues, and cell types with unprecedented molecular resolution. In order to evaluate various biological hypotheses using high-dimensional single-cell gene expression data, most computational and statistical methods depend on a gene feature selection step to identify genes with high biological variability and reduce computational complexity. Even though many gene selection methods have been developed for scRNA-seq analysis, there lacks a systematic comparison of the assumptions, statistical models, and selection criteria used by these methods. In this article, we summarize and discuss 17 computational methods for selecting gene features in unsupervised analysis of single-cell gene expression data, with unified notations and statistical frameworks. Our discussion provides a useful summary to help practitioners select appropriate methods based on their assumptions and applicability, and to assist method developers in designing new computational tools for unsupervised learning of scRNA-seq data.
The role of mTORC1 activation in seizure-induced exacerbation of Alzheimer's disease
Authors: Gourmaud Sarah , Stewart David A , Irwin David J , Roberts Nicholas , Barbour Aaron J , Eberwine Grace , O’Brien William T , Vassar Robert , Talos Delia M , Jensen Frances E 
Published: July 2021

Abstract
The risk of seizures is 10-fold higher in patients with Alzheimer’s disease than the general population, yet the mechanisms underlying this susceptibility and the effects of these seizures are poorly understood. To elucidate the proposed bidirectional relationship between Alzheimer’s disease and seizures, we studied human brain samples (n = 34) from patients with Alzheimer’s disease and found that those with a history of seizures (n = 14) had increased amyloid-β and tau pathology, with upregulation of the mechanistic target of rapamycin (mTOR) pathway, compared with patients without a known history of seizures (n = 20).
To establish whether seizures accelerate the progression of Alzheimer’s disease, we induced chronic hyperexcitability in the five times familial Alzheimer’s disease mouse model by kindling with the chemoconvulsant pentylenetetrazol and observed that the mouse model exhibited more severe seizures than the wild-type. Furthermore, kindled seizures exacerbated later cognitive impairment, Alzheimer’s disease neuropathology and mTOR complex 1 activation. Finally, we demonstrated that the administration of the mTOR inhibitor rapamycin following kindled seizures rescued enhanced remote and long-term memory deficits associated with earlier kindling and prevented seizure-induced increases in Alzheimer’s disease neuropathology.
These data demonstrated an important link between chronic hyperexcitability and progressive Alzheimer’s disease pathology and suggest a mechanism whereby rapamycin may serve as an adjunct therapy to attenuate progression of the disease.
Network-constrained technique to characterize pathology progression rate in Alzheimer’s disease
Authors: Powell Fon , Tosun Duygu , Raj Ashish ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: July 2021

AbstractCurrent methods for measuring the chronic rates of cognitive decline and degeneration in Alzheimer’s disease rely on the sensitivity of longitudinal neuropsychological batteries and clinical neuroimaging, particularly structural magnetic resonance imaging of brain atrophy, either at a global or regional scale. There is particular interest in approaches predictive of future disease progression and clinical outcomes using a single time point. If successful, such approaches could have great impact on differential diagnosis, therapeutic treatment and clinical trial inclusion. Unfortunately, it has proven quite challenging to accurately predict clinical and degeneration progression rates from baseline data. Specifically, a key limitation of the previously proposed approaches for disease progression based on the brain atrophy measures has been the limited incorporation of the knowledge from disease pathology progression models, which suggest a prion-like spread of disease pathology and hence the neurodegeneration. Here, we present a new metric for disease progression rate in Alzheimer that uses only MRI-derived atrophy data yet is able to infer the underlying rate of pathology transmission. This is enabled by imposing a spread process driven by the brain networks using a Network Diffusion Model. We first fit this model to each patient’s longitudinal brain atrophy data defined on a brain network structure to estimate a patient-specific rate of pathology diffusion, called the pathology progression rate. Using machine learning algorithms, we then build a baseline data model and tested this rate metric on data from longitudinal Alzheimer’s Disease Neuroimaging Initiative study including 810 subjects. Our measure of disease progression differed significantly across diagnostic groups as well as between groups with different genetic risk factors. Remarkably, hierarchical clustering revealed 3 distinct clusters based on CSF profiles with &gt;90% accuracy. These pathological clusters exhibit progressive atrophy and clinical impairments that correspond to the proposed rate measure. We demonstrate that a subject’s degeneration speed can be best predicted from baseline neuroimaging volumetrics and fluid biomarkers for subjects in the middle of their degenerative course, which may be a practical, inexpensive screening tool for future prognostic applications.
Presence of dysfunction and myocardial remodeling in patients with premature ventricular complex-induced cardiomyopathy - a cardiovascular MR study
Authors: Kirchgaessner N , Salatzki J , Lugenbiel P , Ochs A , Hund H , Katus HA , Frey N , Giannitsis E , Friedrich MG , Andre F , Scholz E , Ochs MM 
Published: July 2021

Abstract

Funding Acknowledgements
Type of funding sources: None.

Background
Premature ventricular complexes (PVCs) in the absence of underlying structural heart disease are considered to be benign. However, cardiac dysfunction has been observed in patients with a high PVC burden. The characterization of a PVC-induced cardiomyopathy with structural remodeling including myocardial fibrosis and the determination of a specific PVC burden leading to subclinical cardiac dysfunction remains to be determined.

Objectives
We aimed to evaluate cardiac function, remodeling and myocardial fibrosis patterns in patients with PVCs using cardiac magnetic resonance imaging (CMR). Additionally, we aimed to determine a PVC cut-off value leading to subclinical cardiac dysfunction.

Methods
Patients who underwent CMR and 24-hour, 12-lead ECG monitoring (Holter ECG) within six months were retrospectively studied. Patients with evidence of structural heart disease were excluded. The cohort was subdivided based on the number of PVCs in Holter ECG; Group-1 = 0-100, Group-2 = 100-5000 and Group-3 &gt; 5000 PVCs. CMR parameters were extracted from our local databank. Myocardial strain was measured using feature tracking. For quantification of myocardial fibrosis, T1 mapping and late gadolinium enhancement (LGE) were investigated. Z-scores were calculated in order to combine T1 values from a 1.5 and 3Tesla CMR vendor.

Results
443 patients (52 ± 20 years, 45% females) were included in the study. Compared to Group-1, Group-3 revealed a significantly reduced LV-EF, an increased indexed LV-EDV and increased indexed LV-ESV, indicating cardiac dysfunction and LV enlargement. PVCs frequency was inversely correlated with LV-EF (r=-0.23, p &lt; 0.001) and positively correlated with indexed LV-EDV (r = 0.13; p &lt; 0.01). Feature tracking showed significantly higher global circumferential strain (GCS) indicating subclinical dysfunction. Global T1 times were significantly prolonged in Group-3. Elevated global T1 Z-scores were found in Group-2 and Group-3 compared to Group-1. Significantly more intramural LGE was present in Group-2. The PVC cut-off value characterized by reduced GCS was defined by 216 PVCs (AUC = 0.61, p = 0.02).

Conclusion
CMR revealed cardiac dysfunction, left ventricular enlargement and diffuse myocardial fibrosis in patients with PVC in the absence of structural heart disease. These changes indicate the development of a PVC-induced cardiomyopathy depending on the PVC burden. Interestingly, subclinical myocardial dysfunction was determined at already low PVC frequencies. Further investigations are necessary in order to examine the influence of different origins of PVCs and the development of structural remodeling.
Variant anatomy of the renal arteries with anastomosis variants in kidney transplantation
Authors: Kolsanov A , Nazaryan A , Khakimiy T , Kopaeva N , Kosolapov A 
Published: July 2021

Abstract

Funding Acknowledgements
Type of funding sources: None.
One of the most important tasks of morphology as an integral part of practical medicine is comprehensive development of theoretical knowledge pertaining to the variants and anomalies of the renal arteries anatomy.
One of the main conditions required for the normal functioning and viability of the renal transplant is its adequate perfusion. Due to the variant anatomy of the renal arteries and the presence of several adjacent vessels with which anastomosis can be performed, there are many strategies for arterial allograft anastomosis.
The goal of the study was to identify patterns of variant topography and anatomy of the human renal arteries according to CT angiography with three-dimensional modeling which would be further used to optimize the technique of forming vascular anastomosis during kidney transplantation.
Materials and methods. The study included an assessment of computed tomograms of the abdominal organs of 130 patients, which were used to build three-dimensional models. Morphometry was carried out using the Autoplan and Luch-S programs. Based on the results of the CT scans of the kidneys and renal arteries in patients who underwent kidney transplantation, computer 3D models of the renal artery and arterial renal bed were constructed when anastomoses of the renal artery were performed with: the external iliac (group I), the internal iliac (group II) and common iliac (group III) arteries, and in the cases of multiple arteries - during the formation of a common trunk (IIa subgroup) or separate anastomosis with the common iliac artery (IIb). Afterwards, using the Abaqus program, analysis of hemodynamic parameters of intravascular blood flow was conducted, namely: volumetric blood flow rate, partial renal blood flow (the ratio of volumetric blood flow rate to graft weight), visual assessment of the blood flow turbulence.

Results
volumetric renal blood flow in group II (594 cm3/min) and group III (610 cm3/min) was greater than in group I (550 cm3/min); specific renal blood flow in group III exceeded groups I and II by 0.34 cm3/min/g; high turbulence was observed in the anastomosis angle region in groups I and III. The volumetric renal blood flow in subgroups IIa and IIb was 615 and 585 cm3/min respectively, and in the presence of an extra artery extending from the lower pole, a decrease in the linear blood flow velocity in the inferior polar segmental artery was visually assessed. Based on the results of the study, we can conclude that in the presence of a single renal artery, the best perfusion outcome is achieved when performing anastomosis with the common and internal iliac arteries. With multiple kidney arteries, the best perfusion option is obtained when a single renal artery fistula is formed.