bluuebunny/crossref_metadata_2025 huggingface dataset:
Metabolic Profiling of Type 2 Diabetes Patients after Bariatric Surgery by Raman Spectroscopy
Authors: Bonizzi Arianna , Sevieri Marta , Sitia Leopoldo , Rizzi Andrea , Conti Lorenzo , Corsi Fabio , Morasso Carlo , Mazzucchelli Serena
Published: November 2021

Background: Bariatric surgery (BS) is an important procedure used for the treatment of morbid obesity and has been proven to improve, or even cure, type 2 diabetes mellitus (T2DM). However, of the patients with T2DM who initially go into remission, a proportion experience a relapse during the follow-up. In this context, Raman spectroscopy (RS) could be a promising technique for monitoring the metabolic profile of patients after surgical treatment with the aim of improving their postsurgical management. Methods: Fourteen obese patients with T2DM were recruited. Clinical parameters, adipokines, ghrelin, Fibroblast growth factor 19 (FGF-19) values, and Raman spectra were collected and analyzed before and after surgery. RS results were compared with profiles obtained from 23 healthy subjects (HC), to observe whether the metabolic fingerprint of bariatric patients normalized during the surgical follow-up. Results: The reduction in anthropometric measures and improved glycemic control and lipid profile after surgical treatment highlighted the benefits of BS. Consequently, adipokines, ghrelin and FGF-19 concentration returned to normal values after surgery. However, RS data highlighted an altered metabolic profile even after BS. Conclusion: RS suggests that BS does not fully restore the metabolic profile of patients in the immediate follow-up after the surgery.
Dilated Filters for Edge-Detection Algorithms
Authors: Orhei Ciprian , Bogdan Victor , Bonchis Cosmin , Vasiu Radu
Published: November 2021

Edges are a basic and fundamental feature in image processing that is used directly or indirectly in huge number of applications. Inspired by the expansion of image resolution and processing power, dilated-convolution techniques appeared. Dilated convolutions have impressive results in machine learning, so naturally we discuss the idea of dilating the standard filters from several edge-detection algorithms. In this work, we investigated the research hypothesis that use dilated filters, rather than the extended or classical ones, and obtained better edge map results. To demonstrate this hypothesis, we compared the results of the edge-detection algorithms using the proposed dilation filters with original filters or custom variants. Experimental results confirm our statement that the dilation of filters have a positive impact for edge-detection algorithms from simple to rather complex algorithms.
Development of a Novel Adsorbent Prepared from Dredging Sediment for Effective Removal of Dye in Aqueous Solutions
Authors: Ouakouak Abdelkader , Abdelhamid Messameh , Thouraya Barhoumi , Chahinez Hadj-Otmane , Hocine Grabi , Hamdi Noureddine , Syafiuddin Achmad , Boopathy Raj
Published: November 2021

This study proposed a novel and low-cost adsorbent prepared from dredging sediment (DSD) for effective removal of dye in aqueous solutions. The adsorption efficiency and behavior of the DSD adsorbent toward the crystal violet (CV), a cationic dye, were investigated via batch experiments. The results showed that DSD samples contain mainly clay minerals (illite and kaolinite) and other mineral phases. In addition, DSD is a mesoporous material (Vmesopore = 94.4%), and it exhibits a relatively high surface area (~39.1 m2/g). Adsorption experiments showed that the solution’s pH slightly affects the adsorption process, and a pH of 11 gave a maximum capacity of 27.2 mg/g. The kinetic data of CV dye adsorption is well described by the pseudo–second-order and the Avrami models. The Langmuir and Liu isotherm models provide the best fit for the adsorption equilibrium data. The monolayer adsorption capacity of Langmuir reached 183.6, 198.0, and 243.6 mg/g at 293, 308, and 323 K, respectively. It was also found that the adsorption process was spontaneous (−ΔG°), exothermic (−∆H°), and increased the randomness (+∆S°) during the adsorption operation. The primary mechanisms in CV dye adsorption were ion exchange and pore filling, whereas electrostatic attraction was a minor contribution. In addition, three steps involving intraparticle diffusion occur at the same time to control the adsorption process. The results of this study highlight the excellent efficiency of DSD material as an ecofriendly sorbent for toxic dyes from water media.
Hierarchical Concept Learning by Fuzzy Semantic Cells
Authors: Zhu Linna , Li Wei , Tang Yongchuan
Published: November 2021

Concept modeling and learning have been important research topics in artificial intelligence and knowledge discovery. This paper studies a hierarchical concept learning method that requires a small amount of data to achieve competitive performances. The method starts from a set of fuzzy prototypes called Fuzzy Semantic Cells (FSCs). As a result of FSC parameter optimization, it creates a hierarchical structure of data–prototype–concept. Experiments are conducted to demonstrate the effectiveness of our approach in a classification problem. In particular, when faced with limited training data, our proposed method is comparable with traditional techniques in terms of robustness and generalization ability.
Cultivation of Solanum lycopersicum under Glass Coated with Nanosized Upconversion Luminophore
Authors: Burmistrov Dmitry E. , Yanykin Denis V. , Simakin Alexander V. , Paskhin Mark O. , Ivanyuk Veronika V. , Kuznetsov Sergey V. , Ermakova Julia A. , Alexandrov Alexander A. , Gudkov Sergey V.
Published: November 2021

The effect of upconverting luminescent nanoparticles coated on glass on the productivity of Solanum lycopersicum was studied. The cultivation of tomatoes under photoconversion glass led to an increase in plant productivity and an acceleration of plant adaptation to ultraviolet radiation. An increase in the total leaf area and chlorophyll content in the leaves was revealed in plants growing under the photoconversion glass. Plants growing under the photoconversion glass were able to more effectively utilize the absorbed light energy. The results of this study suggest that the spectral changes induced by photoconversion glass can accelerate the adaptation of plants to the appearance of ultraviolet radiation.
Assessment of the Antimicrobial and Antiproliferative Activities of Chloropyrazine-Tethered Pyrimidine Derivatives: In Vitro, Molecular Docking, and In-Silico Drug-Likeness Studies
Authors: Bhandare Richie R. , Shaik Afzal Basha
Published: November 2021

Molecular hybridization (MH) of heterocyclic rings has enabled scientists to design and develop novel drugs and drug-like candidates. In our previous work, considering the importance of MH, we synthesized different kinds of chloropyrazine-tethered pyrimidine derivatives (22–40) containing either substituted phenyl or heteroaryl rings at position-6 of the pyrimidine ring and evaluated their antitubercular activity. Herein, we report the antimicrobial and antiproliferative activities of 22–40. The antiproliferative activity of the target hybrids was superior to the antimicrobial activity. However, some compounds showed greater antimicrobial activity than the standard drugs. For instance, among the nineteen derivatives, compound 31 containing a 2″,4″-dichlorophenyl ring, showed the most potent antibacterial and antifungal activities (MIC 45.37 µM), followed by compounds 25 and 30 bearing 4″-nitrophenyl and 2″,4″-difluorophenyl scaffolds with minimum inhibitory concentrations (MIC) values of 48.67 µM and 50.04 µM, respectively. Compound 35, containing a bioisosteric 2″-pyridinyl ring, showed the most potent antiproliferative activity against the prostate cancer cell line (DU-145) with an IC50 value of 5 ± 1 µg/mL. Additional testing of compounds 22–40 on human normal liver cells (LO2) indicated that the compounds were more selective to cancer cell lines over normal cells. Further, molecular docking of the most potent compound 35 against dihydrofolate reductase (DHFR) (PDB ID: 1U72) had a good binding affinity with a docking score of −6.834. The SwissADME program estimated the drug-likeness properties of compound 35. Hybrid 35 is a potential lead molecule for the development of new anticancer drugs, whereas 31 is a promising antimicrobial lead candidate.
Efficiently Supporting Online Privacy-Preserving Data Publishing in a Distributed Computing Environment
Authors: Kim Jong Wook
Published: November 2021

There has recently been an increasing need for the collection and sharing of microdata containing information regarding an individual entity. Because microdata typically contain sensitive information on an individual, releasing it directly for public use may violate existing privacy requirements. Thus, extensive studies have been conducted on privacy-preserving data publishing (PPDP), which ensures that any microdata released satisfy the privacy policy requirements. Most existing privacy-preserving data publishing algorithms consider a scenario in which a data publisher, receiving a request for the release of data containing personal information, anonymizes the data prior to publishing—a process that is usually conducted offline. However, with the increasing demand for the sharing of data among various parties, it is more desirable to integrate the data anonymization functionality into existing systems that are capable of supporting online query processing. Thus, we developed a novel scheme that is able to efficiently anonymize the query results on the fly, and thus support efficient online privacy-preserving data publishing. In particular, given a user’s query, the proposed approach effectively estimates the generalization level of each quasi-identifier attribute, thereby achieving the k-anonymity property in the query result datasets based on the statistical information without applying k-anonymity on all actual datasets, which is a costly procedure. The experiment results show that, through the proposed method, significant gains in processing time can be achieved.
Techno-Economics Optimization of H2 and CO2 Compression for Renewable Energy Storage and Power-to-Gas Applications
Authors: Esteban Mario , Romeo Luis M.
Published: November 2021

The decarbonization of the industrial sector is imperative to achieve a sustainable future. Carbon capture and storage technologies are the leading options, but lately the use of CO2 is also being considered as a very attractive alternative that approaches a circular economy. In this regard, power to gas is a promising option to take advantage of renewable H2 by converting it, together with the captured CO2, into renewable gases, in particular renewable methane. As renewable energy production, or the mismatch between renewable production and consumption, is not constant, it is essential to store renewable H2 or CO2 to properly run a methanation installation and produce renewable gas. This work analyses and optimizes the system layout and storage pressure and presents an annual cost (including CAPEX and OPEX) minimization. Results show the proper compression stages need to achieve the storage pressure that minimizes the system cost. This pressure is just below the supercritical pressure for CO2 and at lower pressures for H2, around 67 bar. This last quantity is in agreement with the usual pressures to store and distribute natural gas. Moreover, the H2 storage costs are higher than that of CO2, even with lower mass quantities; this is due to the lower H2 density compared with CO2. Finally, it is concluded that the compressor costs are the most relevant costs for CO2 compression, but the storage tank costs are the most relevant in the case of H2.
Comparison of PM2.5 in Seoul, Korea Estimated from the Various Ground-Based and Satellite AOD
Authors: Kim Sang-Min , Koo Ja-Ho , Lee Hana , Mok Jungbin , Choi Myungje , Go Sujung , Lee Seoyoung , Cho Yeseul , Hong Jaemin , Seo Sora , Lee Junhong , Hong Je-Woo , Kim Jhoon
Published: November 2021

Based on multiple linear regression (MLR) models, we estimated the PM2.5 at Seoul using a number of aerosol optical depth (AOD) values obtained from ground-based and satellite remote sensing observations. To construct the MLR model, we consider various parameters related to the ambient meteorology and air quality. In general, all AOD values resulted in the high quality of PM2.5 estimation through the MLR method: mostly correlation coefficients >~0.8. Among various polar-orbit satellite AODs, AOD values from the MODIS measurement contribute to better PM2.5 estimation. We also found that the quality of estimated PM2.5 shows some seasonal variation; the estimated PM2.5 values consistently have the highest correlation with in situ PM2.5 in autumn, but are not well established in winter, probably due to the difficulty of AOD retrieval in the winter condition. MLR modeling using spectral AOD values from the ground-based measurements revealed that the accuracy of PM2.5 estimation does not depend on the selected wavelength. Although all AOD values used in this study resulted in a reasonable accuracy range of PM2.5 estimation, our analyses of the difference in estimated PM2.5 reveal the importance of utilizing the proper AOD for the best quality of PM2.5 estimation.
Special Issue “Data Processing and Modeling on Volcanic and Seismic Areas”
Authors: Bonforte Alessandro , Cannavò Flavio
Published: November 2021

Volcanology, seismology and Earth Sciences in general, like all quantitative sciences, are increasingly dependent on the quantity and quality of data acquired [...]
An Efficient RRT Algorithm for Motion Planning of Live-Line Maintenance Robots
Authors: Feng Jiabo , Zhang Weijun
Published: November 2021

The application of robots to replace manual work in live-line working scenes can effectively guarantee the safety of personnel. To improve the operation efficiency and reduce the difficulties in operating a live-line working robot, this paper proposes a multi-DOF robot motion planning method based on RRT and extended algorithms. The planning results of traditional RRT and extended algorithms are random, and obtaining sub-optimal results requires a lot of calculations. In this study, a sparse offline tree filling the planning space are generated offline through the growing–withering method. In the process of expanding the tree, by removing small branches, the tree can fully wiring in the planning space with a small number of nodes. Optimize wiring through a large number of offline calculations, which can improve the progressive optimality of the algorithm. Through dynamic sampling and pruning, the growth of trees in undesired areas is reduced and undesired planning results are avoided. Based on the offline tree, this article introduces the method of online motion planning. Experiments show that this method can quickly complete the robot motion planning and obtain efficient and low-uncertainty paths.
Weibo Text Sentiment Analysis Based on BERT and Deep Learning
Authors: Li Hongchan , Ma Yu , Ma Zishuai , Zhu Haodong
Published: November 2021

With the rapid increase of public opinion data, the technology of Weibo text sentiment analysis plays a more and more significant role in monitoring network public opinion. Due to the sparseness and high-dimensionality of text data and the complex semantics of natural language, sentiment analysis tasks face tremendous challenges. To solve the above problems, this paper proposes a new model based on BERT and deep learning for Weibo text sentiment analysis. Specifically, first using BERT to represent the text with dynamic word vectors and using the processed sentiment dictionary to enhance the sentiment features of the vectors; then adopting the BiLSTM to extract the contextual features of the text, the processed vector representation is weighted by the attention mechanism. After weighting, using the CNN to extract the important local sentiment features in the text, finally the processed sentiment feature representation is classified. A comparative experiment was conducted on the Weibo text dataset collected during the COVID-19 epidemic; the results showed that the performance of the proposed model was significantly improved compared with other similar models.
Development of Knowledge-Based Engineering System for Structural Size Optimization of External Fixation Device
Authors: Mešić Elmedin , Pervan Nedim , Muminović Adis J. , Muminović Adil , Čolić Mirsad
Published: November 2021

The development process of the knowledge-based engineering (KBE) system for the structural size optimization of external fixation device is presented in this paper. The system is based on algorithms for generative modeling, finite element model (FEM) analysis, and size optimization. All these algorithms are integrated into the CAD/CAM/CAE system CATIA. The initial CAD/FEM model of external fixation device is verified using experimental verification on the real design. Experimental testing is done for axial pressure. Axial stress and displacements are measured using tensometric analysis equipment. The proximal bone segment displacements were monitored by a displacement transducer, while the loading was controlled by a force transducer. Iterative hybrid optimization algorithm is developed by integration of global algorithm, based on the simulated annealing (SA) method and a local algorithm based on the conjugate gradient (CG) method. The cost function of size optimization is the minimization of the design volume. Constrains are given in a form of clinical interfragmentary displacement constrains, at the point of fracture and maximum allowed stresses for the material of the external fixation device. Optimization variables are chosen as design parameters of the external fixation device. The optimized model of external fixation device has smaller mass, better stress distribution, and smaller interfragmentary displacement, in correlation with the initial model.
Spatio-Temporal Characteristics of Dry-Wet Conditions and Boundaries in Five Provinces of Northwest China from 1960 to 2020
Authors: Wang Miao , Liu Puxing , Qiao Xuemei , Si Wenyang , Liu Lu
Published: November 2021

The study of dry-wet climate boundaries in the context of climate warming is of great practical significance for improving the environment of ecologically fragile zones and promoting economic and natural sustainable development. In this study, based on the daily meteorological data of 110 stations, using the wetness index, empirical orthogonal function decomposition, regime shift detection test, Fourier power spectrum, and Kriging interpolation, the researchers analyzed the spatiotemporal characteristics of dry-wet conditions and boundaries in five provinces of Northwest China from 1960 to 2020. The results showed that the overall wetness index increased in the past 61 years, but with significant internal differences, among which the western and central climate tended to be warm and wet, and the eastern tended to be warm and dry. The annual wetness index changed abruptly in 1986 with cycles of 3.61 a, 7.11 a and 8.83 a. The mutations occurred correspondingly in spring, summer, autumn, and winter in 1972, 1976, 1983, and 1988, with periods of 3.88 a and 4.92 a, 2.18 a and 2.81 a, 2.15 a, and 2.10 a, respectively. The dry-wet climate boundary has fluctuated markedly since 1960. The extreme arid and arid regions boundary shifted southward and shrank in size until the extreme arid region disappeared in the 2010s. The arid along with semi-arid regions and semi-arid in addition to semi-humid regions boundaries both have two boundary lines, and show the shift of the northwestern boundary to the southeast and the southeastern boundary to the northwest, with the area of the arid together with semi-arid regions shrinking significantly by 5.64%, simultaneously, the area of the semi-humid region area expanding significantly by 84.11%. The boundary of semi-humid and relatively humid regions, and the boundary of relatively humid and humid regions all shifted to the southeast, moreover, the area of the relatively humid region and humid region shrank significantly by 12.08%. The expansion of semi-humid region and the contraction of other climate regions are characteristics of the dry-wet climate variability in five provinces of Northwest China. The area of the three arid climate zones dwindled by 9.61%, and the area of the three humid zones extended by 39.01%. Obviously, the climate inclined to be warm and humid in general.
Implications of COVID-19 Restriction Measures in Urban Air Quality of Thessaloniki, Greece: A Machine Learning Approach
Authors: Akritidis Dimitris , Zanis Prodromos , Georgoulias Aristeidis K. , Papakosta Eleni , Tzoumaka Paraskevi , Kelessis Apostolos
Published: November 2021

Following the rapid spread of COVID-19, a lockdown was imposed in Thessaloniki, Greece, resulting in an abrupt reduction of human activities. To unravel the impact of restrictions on the urban air quality of Thessaloniki, NO2 and O3 observations are compared against the business-as-usual (BAU) concentrations for the lockdown period. BAU conditions are modeled, applying the XGBoost (eXtreme Gradient Boosting) machine learning algorithm on air quality and meteorological surface measurements, and reanalysis data. A reduction in NO2 concentrations is found during the lockdown period due to the restriction policies at both AGSOFIA and EGNATIA stations of −24.9 [−26.6, −23.2]% and −18.4 [−19.6, −17.1]%, respectively. A reverse effect is revealed for O3 concentrations at AGSOFIA with an increase of 12.7 [10.8, 14.8]%, reflecting the reduced O3 titration by NOx. The implications of COVID-19 lockdowns in the urban air quality of Thessaloniki are in line with the results of several recent studies for other urban areas around the world, highlighting the necessity of more sophisticated emission control strategies for urban air quality management.
Effect of Humidity on the Reactive Uptake of Ammonia and Dimethylamine by Nitrogen-Containing Secondary Organic Aerosol
Authors: Smith Natalie R. , Montoya-Aguilera Julia , Dabdub Donald , Nizkorodov Sergey A.
Published: November 2021

This study investigated the uptake of ammonia (NH3) by secondary organic aerosol (SOA) particles generated via limonene photooxidation or ozonolysis as well as the uptake of dimethylamine (DMA) by limonene ozonolysis, α-cedrene photooxidation, or toluene photooxidation SOA in an environmental chamber between 0–50% relative humidity. In addition to the acid-base equilibrium uptake, NH3 and DMA can react with SOA carbonyl compounds converting them into nitrogen-containing organic compounds (NOCs). The effective reactive uptake coefficients for the formation of NOCs from ammonia were measured on the order of 10−5. The observed DMA reactive uptake coefficients ranged from 10−5 to 10−4. Typically, the reactive uptake coefficient decreased with increasing relative humidity. This is consistent with NOC formation by a condensation reaction between NH3 or DMA with SOA, which produces water as a product. Ammonia is more abundant in the atmosphere than amines. However, the larger observed reactive uptake coefficient suggests that amine uptake may also be a potential source of organic nitrogen in particulate matter.
Climate Change Perception and Uptake of Climate-Smart Agriculture in Rice Production in Ebonyi State, Nigeria
Authors: Onyeneke Robert Ugochukwu , Amadi Mark Umunna , Njoku Chukwudi Loveday , Osuji Emeka Emmanuel
Published: November 2021

Rice production in Nigeria is vulnerable to climate risks and rice farmers over time have experienced the risks and their respective impacts on rice farming. Rice farmers have also responded to perceived climate risks with strategies believed to be climate-smart. Farmers’ perception of climate risks is an important first step of determining any action to be taken to counteract the negative effects of climate change on agriculture. Studies on the link between perceived climate risks and farmers’ response strategies are increasing. However, there are limited studies on the determinants of rice farmers’ perception of climate events. The paper therefore examined climate change perception and uptake of climate-smart agriculture in rice production in Ebonyi State, Nigeria using cross-sectional data from 347 rice farmers in an important rice-producing area in Nigeria. Principal component analysis, multivariate probit regression model and descriptive statistics were adopted for data analysis. Perceived climate events include increased rainfall intensity, prolonged dry seasons, frequent floods, rising temperature, severe windstorms, unpredictable rainfall pattern and distribution, late onset rain, and early cessation of rain. Farmers’ socioeconomic, farm and institutional characteristics influenced their perception of climate change. Additionally, rice farmers used a variety of climate-smart practices and technologies to respond to the perceived climate events. Such climate-smart practices include planting improved rice varieties, insurance, planting different crops, livelihood diversification, soil and water conservation techniques, adjusting planting and harvesting dates, irrigation, reliance on climate information and forecasts, planting on the nursery, appropriate application of fertilizer and efficient and effective use of pesticides. These climate-smart agricultural measures were further delineated into five broad packages using principal component analysis. These packages include crop and land management practices, climate-based services and irrigation, livelihood diversification and soil fertility management, efficient and effective use of pesticide and planting on the nursery. High fertilizer costs, lack of access to inputs, insufficient land, insufficient capital, pests and diseases, floods, scorching sun, high labour cost, insufficient climate information, and poor extension services were the barriers to uptake of climate-smart agriculture in rice production. Rice farmers should be supported to implement climate-smart agriculture in rice production in order to achieve the objectives of increased rice productivity and income, food security, climate resilience and mitigation.
Automatic Multi-Label ECG Classification with Category Imbalance and Cost-Sensitive Thresholding
Authors: Liu Yang , Li Qince , Wang Kuanquan , Liu Jun , He Runnan , Yuan Yongfeng , Zhang Henggui
Published: November 2021

Automatic electrocardiogram (ECG) classification is a promising technology for the early screening and follow-up management of cardiovascular diseases. It is, by nature, a multi-label classification task owing to the coexistence of different kinds of diseases, and is challenging due to the large number of possible label combinations and the imbalance among categories. Furthermore, the task of multi-label ECG classification is cost-sensitive, a fact that has usually been ignored in previous studies on the development of the model. To address these problems, in this work, we propose a novel deep learning model–based learning framework and a thresholding method, namely category imbalance and cost-sensitive thresholding (CICST), to incorporate prior knowledge about classification costs and the characteristic of category imbalance in designing a multi-label ECG classifier. The learning framework combines a residual convolutional network with a class-wise attention mechanism. We evaluate our method with a cost-sensitive metric on multiple realistic datasets. The results show that CICST achieved a cost-sensitive metric score of 0.641 ± 0.009 in a 5-fold cross-validation, outperforming other commonly used thresholding methods, including rank-based thresholding, proportion-based thresholding, and fixed thresholding. This demonstrates that, by taking into account the category imbalance and predefined cost information, our approach is effective in improving the performance and practicability of multi-label ECG classification models.
Non-Interventional and High-Precision Temperature Measurement Biochips for Long-Term Monitoring the Temperature Fluctuations of Individual Cells
Authors: Han Danhong , Xu Jingjing , Wang Han , Wang Zhenhai , Yang Nana , Yang Fan , Shen Qundong , Xu Shengyong
Published: November 2021

Monitoring the thermal responses of individual cells to external stimuli is essential for studies of cell metabolism, organelle function, and drug screening. Fluorescent temperature probes are usually employed to measure the temperatures of individual cells; however, they have some unavoidable problems, such as, poor stability caused by their sensitivity to the chemical composition of the solution and the limitation in their measurement time due to the short fluorescence lifetime. Here, we demonstrate a stable, non-interventional, and high-precision temperature-measurement chip that can monitor the temperature fluctuations of individual cells subject to external stimuli and over a normal cell life cycle as long as several days. To improve the temperature resolution, we designed temperature sensors made of Pd–Cr thin-film thermocouples, a freestanding Si3N4 platform, and a dual-temperature control system. Our experimental results confirm the feasibility of using this cellular temperature-measurement chip to detect local temperature fluctuations of individual cells that are 0.3–1.5 K higher than the ambient temperature for HeLa cells in different proliferation cycles. In the future, we plan to integrate this chip with other single-cell technologies and apply it to research related to cellular heat-stress response.
Subjective Time in Dementia: A Critical Review
Authors: Liu Lulu , Bulley Adam , Irish Muireann
Published: November 2021

The capacity for subjective time in humans encompasses the perception of time’s unfolding from moment to moment, as well as the ability to traverse larger temporal expanses of past- and future-oriented thought via mental time travel. Disruption in time perception can result in maladaptive outcomes—from the innocuous lapse in timing that leads to a burnt piece of toast, to the grievous miscalculation that produces a traffic accident—while disruption to mental time travel can impact core functions from planning appointments to making long-term decisions. Mounting evidence suggests that disturbances to both time perception and mental time travel are prominent in dementia syndromes. Given that such disruptions can have severe consequences for independent functioning in everyday life, here we aim to provide a comprehensive exposition of subjective timing dysfunction in dementia, with a view to informing the management of such disturbances. We consider the neurocognitive mechanisms underpinning changes to both time perception and mental time travel across different dementia disorders. Moreover, we explicate the functional implications of altered subjective timing by reference to two key and representative adaptive capacities: prospective memory and intertemporal decision-making. Overall, our review sheds light on the transdiagnostic implications of subjective timing disturbances in dementia and highlights the high variability in performance across clinical syndromes and functional domains.
A Retrospective Analysis of Randomized Controlled Trials on Traumatic Brain Injury: Evaluation of CONSORT Item Adherence
Authors: Elcivan Meltem , Kowark Ana , Coburn Mark , Hamou Hussam Aldin , Kremer Benedikt , Clusmann Hans , Höllig Anke
Published: November 2021

Traumatic brain injury (TBI) contributes to death and disability, resulting in an enormous individual and socio-economic challenges. Despite huge efforts, there are still controversies on treatment strategies and early outcome estimation. We evaluate current randomized controlled trials (RCTs) on TBI according to their fulfillment of the CONSORT (Consolidated Statement of Reporting Trials) statement’s criteria as a marker of transparency and the quality of study planning and realization. A PubMed search for RCTs on TBI (January 2014–December 2019) was carried out. After screening of the abstracts (n = 1.926), the suitable full text manuscripts (n = 72) were assessed for the fulfillment of the CONSORT criteria. The mean ratio of consort statement fulfillment was 59% (±13%), 31% of the included studies (n = 22) complied with less than 50% of the CONSORT criteria. Citation frequency was moderately related to ratio of CONSORT item fulfillment (r = 0.4877; p < 0.0001) and citation frequency per year (r = 0.5249; p < 0.0001). The ratio of CONSORT criteria fulfillment was associated with the impact factor of the publishing journal (r = 0.6428; p < 0.0001). Essential data for study interpretation, such as sample size determination (item 7a), participant flow (item 13a) as well as losses and exclusions (item 13b), were only reported in 53%, 60% and 63%, respectively. Reporting and methodological aspects in RCTs on TBI still may be improved. Thus, the interpretation of study results may be hampered due to methodological weaknesses.
Heart Rate Variability in Insulo-Opercular Epilepsy
Authors: Tran Thi Phuoc Yen , Pouliot Philippe , Assi Elie Bou , Rainville Pierre , Myers Kenneth A. , Robert Manon , Bouthillier Alain , Keezer Mark R. , Nguyen Dang Khoa
Published: November 2021

Background: We aimed to evaluate heart rate variability (HRV) changes in insulo-opercular epilepsy (IOE) and after insulo-opercular surgery. Methods: We analyzed 5-min resting HRV of IOE patients before and after surgery. Patients’ SUDEP-7 risk inventory scores were also calculated. Results were compared with age- and sex-matched patients with temporal lobe epilepsy (TLE) and healthy individuals. Results: There were no differences in HRV measurements between IOE, TLE, and healthy control groups (and within each IOE group and TLE group) in preoperative and postoperative periods. In IOE patients, the SUDEP-7 score was positively correlated with pNN50 (percentage of successive RR intervals that differ by more than 50 ms) (p = 0.008) and RMSSD (root mean square of successive RR interval differences) (p = 0.019). We stratified IOE patients into those whose preoperative RMSSD values were below (Group 1a = 7) versus above (Group 1b = 9) a cut-off threshold of 31 ms (median value of a healthy population from a previous study). In group 1a, all HRV values significantly increased after surgery. In group 1b, time-domain parameters significantly decreased postoperatively. Conclusions: Our results suggest that in IOE, HRV may be either decreased in parasympathetic tone or increased globally in both sympathetic and parasympathetic tones. We found no evidence that insulo-opercular surgeries lead to major autonomic dysfunction when a good seizure outcome is reached. The increase in parasympathetic tone observed preoperatively may be of clinical concern, as it was positively correlated with the SUDEP-7 score.
Sensory-Motor Modulations of EEG Event-Related Potentials Reflect Walking-Related Macro-Affordances
Authors: Tosoni Annalisa , Altomare Emanuele Cosimo , Brunetti Marcella , Croce Pierpaolo , Zappasodi Filippo , Committeri Giorgia
Published: November 2021

One fundamental principle of the brain functional organization is the elaboration of sensory information for the specification of action plans that are most appropriate for interaction with the environment. Using an incidental go/no-go priming paradigm, we have previously shown a facilitation effect for the execution of a walking-related action in response to far vs. near objects/locations in the extrapersonal space, and this effect has been called “macro-affordance” to reflect the role of locomotion in the coverage of extrapersonal distance. Here, we investigated the neurophysiological underpinnings of such an effect by recording scalp electroencephalography (EEG) from 30 human participants during the same paradigm. The results of a whole-brain analysis indicated a significant modulation of the event-related potentials (ERPs) both during prime and target stimulus presentation. Specifically, consistent with a mechanism of action anticipation and automatic activation of affordances, a stronger ERP was observed in response to prime images framing the environment from a far vs. near distance, and this modulation was localized in dorso-medial motor regions. In addition, an inversion of polarity for far vs. near conditions was observed during the subsequent target period in dorso-medial parietal regions associated with spatially directed foot-related actions. These findings were interpreted within the framework of embodied models of brain functioning as arising from a mechanism of motor-anticipation and subsequent prediction error which was guided by the preferential affordance relationship between the distant large-scale environment and locomotion. More in general, our findings reveal a sensory-motor mechanism for the processing of walking-related environmental affordances.
Editorial: New Perspectives and Methodologies in the Diagnosis and Rehabilitation of Aphasia
Authors: Pisano Francesca , Marangolo Paola
Published: November 2021

Aphasia is a highly disabling acquired language disorder, usually caused by left-lateralized brain damage [...]
Determinants of Quality of Life after Stroke in Southern Portugal: A Cross Sectional Community-Based Study
Authors: Lourenço Eva , Sampaio Mário Rui dos Mártires , Nzwalo Hipólito , Costa Emília Isabel , Ramos José Luis Sánchez
Published: November 2021

Introduction: the perception of Quality of Life (QoL) has been used to evaluate the treatment and evolution of several pathologies. QoL evaluation allows a better understanding of the patient and his adaptation to the disease. An observational, community-based and descriptive correlational study was carried out to analyze stroke survivors’ perception of QoL. Methods: consecutive case-series of stroke survivors (≥3 months) followed in a single public primary health center (“Tavira Primary Health Centre”) from Algarve, southern Portugal. The Portuguese version of the World Health Organization Quality of life instrument was administered in 102 stroke survivors. Results: Perception of QoL was associated (p < 0.05) with specific sociodemographic (age, sex, marital status, academic training), economic (monthly family income) and clinical factors (number of vascular risk factors, type of stroke, evolution, chronic mRankin score). On multivariate analysis, chronic mRankin score on physical (R2 = 0.406; F = 8.757; p < 0.001), psychological (R2 = 0.286; F = 5.536; p < 0.001) and general domain (R2 = 0.357; F = 7.287; p < 0.001); and family income (R2 = 0.160; F = 3.156; p < 0.005) on environmental domain, emerged as predictors of QoL. Conclusion: Different socio-demographic, economic and health factors are associated with post-stroke QoL. Description of QoL contributes to the overall evaluation of the impact of stroke on health and should be a priority for health professionals.
Classification of Ankle Joint Stiffness during Walking to Determine the Use of Ankle Foot Orthosis after Stroke
Authors: Sekiguchi Yusuke , Honda Keita , Owaki Dai , Izumi Shin-Ichi
Published: November 2021

Categorization based on quasi-joint stiffness (QJS) may help clinicians select appropriate ankle foot orthoses (AFOs). The objectives of the present study were to classify the gait pattern based on ankle joint stiffness, also called QJS, of the gait in patients after stroke and to clarify differences in the type of AFO among 72 patients after stroke. Hierarchical cluster analysis was used to classify gait patterns based on QJS at least one month before the study, which revealed three distinct subgroups (SGs 1, 2, and 3). The proportion of use of AFOs, articulated AFOs, and non-articulated AFOs were significantly different among SGs 1–3. In SG1, with a higher QJS in the early and middle stance, the proportion of the patients using articulated AFOs was higher, whereas in SG3, with a lower QJS in both stances, the proportion of patients using non-articulated AFOs was higher. In SG2, with a lower QJS in the early stance and higher QJS in the middle stance, the proportion of patients using AFOs was lower. These findings indicate that classification of gait patterns based on QJS in patients after stroke may be helpful in selecting AFO. However, large sample sizes are required to confirm these results.
Grounding Adaptive Cognitive Control in the Intrinsic, Functional Brain Organization: An HD-EEG Resting State Investigation
Authors: Duma Gian Marco , Di Bono Maria Grazia , Mento Giovanni
Published: November 2021

In a recent study, we used the dynamic temporal prediction (DTP) task to demonstrate that the capability to implicitly adapt motor control as a function of task demand is grounded in at least three dissociable neurofunctional mechanisms: expectancy implementation, expectancy violation and response implementation, which are supported by as many distinct cortical networks. In this study, we further investigated if this ability can be predicted by the individual brain’s functional organization at rest. To this purpose, we recorded resting-state, high-density electroencephalography (HD-EEG) in healthy volunteers before performing the DTP task. This allowed us to obtain source-reconstructed cortical activity and compute whole-brain resting state functional connectivity at the source level. We then extracted phase locking values from the parceled cortex based on the Destrieux atlas to estimate individual functional connectivity at rest in the three task-related networks. Furthermore, we applied a machine-learning approach (i.e., support vector regression) and were able to predict both behavioral (response speed and accuracy adaptation) and neural (ERP modulation) task-dependent outcome. Finally, by exploiting graph theory nodal measures (i.e., degree, strength, local efficiency and clustering coefficient), we characterized the contribution of each node to the task-related neural and behavioral effects. These results show that the brain’s intrinsic functional organization can be potentially used as a predictor of the system capability to adjust motor control in a flexible and implicit way. Additionally, our findings support the theoretical framework in which cognitive control is conceived as an emergent property rooted in bottom-up associative learning processes.
Experimental Investigation of Two Test Setups on Straw Bales Used as Load-Bearing Elements of Buildings
Authors: Lehner Petr , Horňáková Marie , Vlček Pavel , Teslík Jiří
Published: November 2021

The importance of green and sustainable materials in civil engineering is undeniable. Alongside modern practices that improve the properties of standard building materials, there are ways to revive forgotten techniques, including straw bale buildings. Straw bales are load-bearing structures, which are applied based on handed-down experience and lack standard approaches in testing, design, and application. Therefore, a goal ahead is to describe every aspect of the process in technical detail. The objective of this paper is to highlight practical ideas for testing straw bales on a hydraulic press machine and to provide a basic statistical investigation of the results obtained. Two basic series were prepared, one without a side barrier and the other with a side barrier. The reason for this was to delineate the limits of the real behaviour of the straw bale on the load bearing wall of the house. Due to the assumed slight embedment of adjacent bales, the real result were within these limits. The experimental plan, basic results, simplified correlations, and statistical evaluation are presented. Recommendations for a further testing and evaluation are provided. As expected, the results with and without the lateral barrier differ by almost 18% for the true strain.
Stress Distribution in Microregion of Core–Shell Structure Lightweight Aggregate Concrete
Authors: Zhu Meng , Zhang Lihua , Wang Weilong , Zhang Hongping , Xing Wenjin
Published: November 2021

An in-depth understanding of the effect of cordierite/belite core–shell structure lightweight aggregate (CSLWA) on the mechanical performance of LWA concrete (LWAC) is critical for improving the failure resistance of LWAC. In this study, the stress distribution of the microregion in CSLWA was systematically investigated via a finite element analysis to explore its effect on the mechanical properties of LWAC. In detail, the material components, core–shell thickness ratio, porosity and width of interfacial transition zone (ITZ), and absence or presence of interfacial bonding zone (IBZ) were considered during the stress distribution analysis of the microregion of LWAC. The results showed that a reduction in the material components, with a high-elastic modulus in the core, a decrease in the core–shell thickness ratio, and the formation of the core–shell IBZ are beneficial for optimizing the stress distribution of the microregion and alleviating the stress concentration phenomenon of LWAC. Moreover, due to the continuous hydration of belite shell, the ITZ of CSLWA becomes increasingly dense, thus the stress distribution is more uniform than that of ordinary LWAC, indicating that CSLWA exhibits the potential to improve the failure resistance of LWAC. This study helps to develop an understanding of the role played by the core–shell structure in improving the toughness of LWAC, and provides a new solution and methodology for improving the brittleness of LWAC.
Digital Simulation for Buildings’ Outdoor Thermal Comfort in Urban Neighborhoods
Authors: Zhang Yingyi , Liu Chang
Published: November 2021

Buildings’ outdoor thermal comfort influences environment quality and human behavior in urban neighborhoods. The Universal Thermal Climate Index (UTCI) has been broadly applied to the study of buildings’ outdoor thermal comfort in urban areas. However, complex environmental conditions in climate-sensitive urban areas can make UTCI assessment complicated and ineffective. This paper introduces digital techniques into buildings’ outdoor thermal comfort analysis for the improvement of the urban habitant environment. A digital simulation system is generated to facilitate the analysis procedure for buildings’ outdoor thermal comfort assessment in urban neighborhoods. The analysis addresses the research question: “Can digital simulation techniques provide a modeling system to assess buildings’ outdoor thermal comfort continuously and effectively?” Methods include a case study of neighborhoods in Beijing, qualitative and quantitative analysis based on digital processes, and parametric modeling. The results indicate that digital simulation techniques and tools have the capability to support the analysis of buildings’ outdoor thermal comfort by providing three-dimensional models, algorithm-based analysis, and visual simulation. The findings include a critique of digital simulation as applied to architecture study and insights on potentially improving buildings’ outdoor thermal comfort through human–computer interactions.