bluuebunny/crossref_metadata_2025 huggingface dataset:
KINNEYIA-TYPE WRINKLE STRUCTURES ON SANDSTONE BEDS: NOT MICROBIALLY INDUCED BUT DEFORMATION FEATURES CAUSED BY SYNSEDIMENTARY EARTHQUAKES
Authors: PRATT BRIAN R.
Published: October 2021

A category of wrinkle structures, often termed Kinneyia structure or Runzel marks, comprises bedding plane features consisting typically of anastomosing, low-relief, flat-topped ridges with intervening depressions. Topographic relief is usually less than a millimeter. They are locally common on the upper surfaces of fine- to medium-grained sandstone beds interbedded with mudstone deposited in offshore settings, especially in Precambrian and lower Paleozoic strata but as young as Cretaceous. For more than the last two decades these wrinkle structures have been widely regarded as due to microbial mats, and have been taken as evidence for dominance in the Proterozoic of microbially stabilized sediment and, in the Phanerozoic, a matground marine benthic ecology which gradually gave way to a mixground ecology. The detailed morphology and cross-cutting relationships demonstrated by a range of specimens of Proterozoic, Cambrian, and Silurian age, however, cast this interpretation into doubt. The relationship between the wrinkled surface and bioclasts such as shells and both prior- and later-formed scour surfaces, and horizontal and vertical burrows show that these wrinkles did not develop due to the surface topography of microbial mats or compaction of microbial mats during burial, but instead formed at the top of a sand bed at the interface with an overlying layer of mud. Deformation is ascribed to vibration from low-magnitude earthquakes. The presence in some units of small-scale sedimentary dikelets and crack arrays that formed later after some stiffening, along with locally associated seismites and other evidence for nearby faulting, show that syndepositional tectonic activity was not unexpected and support the interpretation that this category of wrinkle structures is a type of seismite.
Post-buckling behaviors of thin-film soft-substrate bilayers with finite-thickness substrate
Authors: Li Meng , Sun Bohua
Published: October 2021

Surface buckling behaviors of thin-film soft-substrate bilayers have important research value. Recent research has focused on bilayers with infinite-thickness substrates. However, bilayers with finite-thickness substrates widely exist. To study this problem more comprehensively, we extended the stability theory of a beam on an elastic foundation to bilayers and then established a finite element method of bilayers using the neo-Hookean hyperelastic constitutive model. A self-contact analysis method was coupled to the finite element method so that the further buckling evolution of the film surface after folding could be simulated. Based on our analysis of various modulus ratios and thickness ratios, the evolution of the buckling path was significantly influenced by the thickness ratio. Without considering the situation of a prestressed substrate, four new buckling paths were found. Thus, we extended the single buckling path (under infinite thickness substrate) to five types. Our study also found that for path four, the substrate with a certain thickness exhibited a special final stable surface morphology. That is, regardless of the friction, a new periodic morphology after film folding appeared due to the contact slip of the film surface. Finally, further analysis showed that these five buckling paths were all dependent on different modulus ratios and thickness ratios.
Stereotactic Radiosurgery Versus Active Surveillance for Asymptomatic, Skull-Based Meningiomas: An International, Multicenter Matched Cohort Study
Authors: Mantziaris Georgios , Pikis Stylianos , Samanci Yavuz , Peker Selcuk , Nabeel Ahmed M. , Reda Wael A. , Tawadros Sameh R. , El-Shehaby Amr M.N. , Abdelkarim Khaled , Emad Reem M. , Delabar Violaine , Mathieu David , Lee Cheng-chia , Yang Huai-che , Liscak Roman , Hanuska Jaromir , Alvarez Roberto Martinez , Moreno Nuria Martinez , Tripathi Manjul , Speckter Herwin , Albert Camilo , Benveniste Ronald J , Bowden Greg N , Patel Dev N , Kondziolka Douglas , Bernstein Kenneth , Lunsford Dade L. , Jenkinson Michael D. , Islim Abdurrahman I. , Sheehan Jason P
Published: October 2021

Objective: The optimal management of asymptomatic, skull-based meningiomas is not well defined. The aim of this study is to compare the imaging and clinical outcomes of patients with asymptomatic, skull-based meningiomas managed either with upfront stereotactic radiosurgery (SRS) or active surveillance.Methods: This retrospective, multicenter study involved patients with asymptomatic, skull-based meningiomas. The study end-points included local tumor control and the development of new neurological deficits attributable to the tumor. Factors associated with tumor progression and neurological morbidity were also analyzed.Results: The combined unmatched cohort included 417 patients. Following propensity score matching for age, tumor volume, and follow-up 110 patients remained in each cohort. Tumor control was achieved in 98.2% and 61.8% of the SRS and active surveillance cohorts, respectively. SRS was associated with superior local tumor control (p<0.001, HR=0.01, 95% CI=0.002-0.13) compared to active surveillance. Three patients (2.7%) in the SRS cohort and six (5.5%) in the active surveillance cohort exhibited neurological deterioration. One (0.9 %) patient in the SRS-treated and 11 (10%) patients in the active surveillance cohort required surgical management of their meningioma during follow-up.Conclusions: SRS is associated with superior local control of asymptomatic, skull-based meningiomas as compared to active surveillance and does so with low morbidity rates. Active surveillance with regular neuroimaging studies does not always detect tumor growth before symptomatic progression. SRS should be considered as an alternative to active surveillance at diagnosis of an asymptomatic skull base meningioma. If active surveillance is initially chosen, SRS should be recommended when tumor growth from the original presenting volume is noted during follow-up.
Structural Connectivity in Ventral Language Pathways Characterizes Nonverbal Autism
Authors: Olivé Guillem , Slušná Dominika , Vaquero Lucía , Muchart-López Jordi , Rodríguez-Fornells Antoni , Hinzen Wolfram
Published: October 2021

Autism spectrum disorder (ASD) involves a large variety of language capacities, from normal scores on standardized language tests to absence of functional language in a substantial minority of 30% of individuals with ASD. Due to practical difficulties of scanning at this severe end of the autism spectrum, insights from MRI are scarce. Here we used manual deterministic tractography to investigate, for the first time, the integrity of the core white matter tracts defining the language connectivity network in nonverbal ASD (nvASD): the arcuate (AF), inferior fronto-occipital (IFOF), inferior longitudinal (ILF) and uncinate (UF) fasciculi, and the frontal aslant tract (FAT). A multiple case series of nine individuals with nvASD were compared to normative benchmarks from matched individuals with verbal ASD (vASD) and typical development (TD). Bonferroni-corrected repeated measure ANOVAs were performed separately for each tract –Hemisphere (2:Left/Right) x Group (3:TD/vASD/nvASD). Results revealed (i) a main effect of group consisting in a reduction in fractional anisotropy (FA) in the IFOF in nvASD relative to TD; (ii) a significant interaction of hemisphere and group in the UF, which showed reduced volume in the left hemisphere when compared to the right, in the vASD group only; and (iii) main effects of hemisphere in both the AF (left-lateralized in volume) and the ILF (left-lateralized in FA). These results do not replicate deficits of the dorsal language route previously observed in nvASD, and instead point to a disruption of the ventral language pathway, which is in line with semantic deficits observed behaviourally in this group.
Image-Matching Digital Macro-Slide—A Novel Pathological Examination Method For Microvascular Invasion Detection In Hepatocellular Carcinoma
Authors: Yu Hong-Ming , Wang Kang , Feng Jin-Kai , Lu Lei , Qin Yu-Chen , Cheng Yu-Qiang , Guo Wei-Xing , Shi Jie , Cong Wen-Ming , Lau Wan Yee , Dong Hui , Cheng Shu-Qun
Published: October 2021

Background: Microvascular invasion (MVI) is a prominent risk factor of postoperative recurrence for hepatocellular carcinoma (HCC). The MVI detection rate of conventional pathological examination approaches is relatively low and unsatisfactory.Methods: By integrating pathological macro-slide with whole-mount slide imaging, we first created a novel pathological examination method called image-matching digital macro-slide (IDS). Surgical samples from eligible patients were collected to make IDS. The MVI detection rates, tumor recurrence rates and recurrence-free survival were compared among conventional 3-Point and 7-Point baseline sampling protocols and IDS. Additionally, biomarkers to recognize MVI false negative patients were probed via combining conventional pathological sampling protocols and IDS. Receiver operating characteristic curve (ROC) analysis was used to obtain the optimal cutoff of biomarkers to distinguish MVI false negative status.Results: The MVI detection rates were 21.98%, 32.97% and 63.74%, respectively, in 3-Point, 7-Point baseline sampling protocols and IDS (P< 0.001). Tumor recurrence rate of patients with MVI negative status in IDS (6.06%) was relatively lower than that of patients with MVI negative status in 3-Point (16.90%) and 7-Point (16.39%) sampling protocols. Alpha-fetoprotein (AFP) and protein induced by vitamin K absence or antagonist-II (PIVKA-II) was selected as potential biomarkers to distinguish MVI false negative patients.Conclusions: Our study demonstrated that IDS can help enhance the detection rate of MVI in HCC and refine the prediction of HCC prognosis. Alpha-fetoprotein is identified as a suitable and robust biomarker to recognize MVI false-negative patients in conventional pathological protocols.
Changes in temperature-precipitation correlations over Europe: Are climate models reliable?
Authors: Vrac Mathieu , Thao Soulivanh , Yiou Pascal
Published: October 2021

Inter-variable correlations (e.g., between daily temperature and precipitation) are key statistical properties to characterise probabilities of simultaneous climate events and compound events. Their correct simulations from climate models, both in values and in changes over time, is then a prerequisite to investigate their future changes and associated impacts.

Therefore, this study first evaluates the capabilities of one 11-member multi-model ensemble (CMIP6) and one 40-member multi-run single model ensemble (CESM) over Europe to reproduce the characteristics of a reanalysis dataset (ERA5) in terms of temperature-precipitation correlations and their historical changes. Next, the ensembles’ correlations for the end of the 21st century are compared to assess the robustness of the future correlation changes.

Over historical period, both CMIP6 and CESM ensembles have season-dependent and spatially structured biases. Moreover, the inter-variable correlations from both ensembles mostly appear stationary. Thus, although reanalyses display significant correlation changes, none of the ensembles is able to reproduce them. However, future correlations show significant changes over large spatial patterns. Yet, those patterns are rather different for CMIP6 and CESM, reflecting a large uncertainty in changes.

In addition, for historical and future projections, an analysis conditional on atmospheric circulation regimes is performed. The conditional correlations given the regimes are found to be the main contributor to the biases in correlation over the historical period, and to the past and future changes of correlation.

These results highlight the importance of the large-scale circulation regimes and the need to understand their physical relationships with local-scale phenomena associated to specific inter-variable correlations.
The Effects of Macrophages Condition Media on the Vessel-Like Structure Formation of Pre-Vascularized Bone Marrow Mesenchymal Stem Cell Sheets
Authors: Long Siqi , Ren Lina , Liu Xiaoning , Shi Jiamin , Liu Jiaxin , Ma Dongyang , Zhou Ping , Ren Liling
Published: October 2021

Background With the development of tissue engineering and regenerative medicine, engineered tissue constructs have become more prevalent and are now used as substitutions of patients’ damaged organs or tissues. To date, a scaffold-free cell transplantation technique based on cell sheets have been widely used in clinic. While poor vascularization and adverse immune reactions to biomedical devices remain crucial challenges in tissue engineering. The inflammatory response represents one of mainly and important regulators of vascularization and engineered tissue function restoration. This study investigated the effect of macrophage secretion on the formation of microvascular-like structures of human umbilical vein endothelial cells (HUVECs) in the bone marrow mesenchymal stem cell (BMSC) sheets. Methods Researchers differentiated the human monocytic leukemia cell line (THP-1) cells into the resting state of macrophage (M0) by phorbol 12-myristate 13-acetate (PMA) and further activated them into pro-inflammation and pro-healing states with the use of various cytokines. Condition media derived from kinds of macrophages were used to investigate the impact of macrophage on the viability and arrangement of HUVECs on BMSC sheets. Cytokines related to angiogenesis were detected in the culture supernatant of HUVECs, BMSC sheets, and pre-vascularized sheets. Results Results indicated that macrophages may guide the arrangement of endothelial cell through the paracrine pathway. The cell sheets that were cultured in the microenvironment with pro-inflammatory macrophages had fewer cell layers compared to those generated in other media. Furthermore, after experiencing high levels of vascular endothelial growth factor (VEGF) and tumor necrosis factor alpha (TNF-α) in the first 3 days while high level of platelet-derived growth factor (PDGF)-BB but low TNF-α and VEGF concentration in the next 4 days, pre-vascularized sheets had the most significant micro-vessel network. Conclusions The fates of pre-vascularized sheets regulated by macrophages secreted factors in microenvironment and sequential released cytokines could even promote neovascularization and angiogenesis.
Impact of ICT on Environment
Authors: Mahdavi Samaneh , Sojoodi Sakineh
Published: October 2021

The impact of information and communications technologies (ICT) on the environment is a complex highly-debated subject. Indeed, ICT can have both positive and negative impacts on the environment. While ICT tools and devices can be used to improve energy efficiency, which results in reduced CO2 emissions and environmental degradation, the manufacturing and use of ICT devices can become a major source of emission. Also, many ICT devices contain non-renewable and non-recyclable components that can cause significant environmental damage. Therefore, one may question that whether ICT improves environmental quality in countries with different income levels? To answer this question, this study investigated the environmental impacts of ICT in three groups of high, middle, and low-income countries from 2005 to 2019 using the Generalized Method of Moments (GMM). The ICT Development Index (IDI) was used as the measure of ICT development. Empirical results showed that the use of ICT led to reduced total CO2 emissions, CO2 emissions from solid fuel consumption, CO2 emissions damage, particulate emissions damage, and energy consumption in the studied countries. Therefore, ICT was found to have a generally negative (favorable) impact on environmental degradation in these countries. Considering this effect of ICT on environmental degradation and pollution, governments are recommended to pursue their energy consumption and emission objectives by promoting the use of ICT in the environmental sector and the implementation of green ICT projects.
Evaluation of Landslide Susceptibility of the Ya'an-Linzhi Section of the Sichuan-Tibet Railway based on Deep Learning
Authors: Wang Shibao , Zhuang Jianqi , Mu Jiaqi , Zheng Jia , Zhan Jiewei , Wang Jie , Fu Yuting
Published: October 2021

The Qinghai-Tibet Plateau is one area with the most frequent landslide hazards due to its unique geology, topography, and climate conditions, posing severe threats to engineering construction and human settlements. The Sichuan-Tibet Railway that is currently under construction crosses the Qinghai-Tibet Plateau; there are frequent landslide disasters along the line, which seriously threaten the construction of the railway. This paper applied two deep learning (DL) algorithms, the convolutional neural network (CNN) and deep neural network (DNN), to landslide susceptibility mapping of the Ya’an-Linzhi section of the Sichuan-Tibet Railway. A geospatial database was generated based on 587 landslide hazards determined by Interferometric Synthetic Aperture Radar (InSAR) Stacking technology, field geological hazard surveys, and 18 landslide influencing factors were selected. The landslides were randomly divided into training data (70%) and validation data (30%) for the modeling training and testing. The Pearson correlation coefficient and information gain method were used to perform the correlation analysis and feature selection of 18 influencing factors. Both models were evaluated and compared using the receiver operating characteristic (ROC) curve and confusion matrix. The results show that better performance in both the training and testing phases was provided by the CNN algorithm (AUC = 0.88) compared to the DNN algorithm (AUC = 0.84). Slope, elevation, and rainfall are the main factors affecting the occurrence of landslides, and the high and very high landslide susceptibilities were primarily distributed in the Jinsha, Lancang, and Nujiang River Basins along the railway. The research results provide a scientific basis for the construction of the Ya'an-Linzhi section of the Sichuan-Tibet Railway within the region, as well as the disaster prevention and mitigation work during future safe operations.
CFDIL: A Context-aware Feature Deep Interaction Learning for App Recommendation
Authors: Hao Qingbo , Zhu Ke , Wang Chundong , Wang Peng , Mo Xiuliang , Liu Zhen
Published: October 2021

The rapid development of Mobile Internet has spa-wned various mobile applications (apps). A large number of apps make it difficult for users to choose apps conveniently, causing the app overload problem. As the most effective tool to solve the problem of app overload, the app recommendation has attracted extensive attention of researchers. Traditional recommendation methods usually use historical data of apps used by users to explore their preferences, and then make an app recommendation list for users. Although the traditional app recommendation methods have achieved certain results, the performance of app recommendation still needs to be improved due to the following two reasons. On the one hand, it is difficult to construct traditional app recommendation models when facing with the sparse user-app interaction data. On the other hand, contextual information has a large impact on users’ app usage preferences, which is often overlooked by traditional app recommendation methods. To overcome the aforementioned problems, we proposed a Context-aware Feature Deep Interaction Learning (CFDIL) method to explore user preferences, and then perform app recommendation by learning potential user-app relationships in different contexts. The novelty of CFDIL is as follows: (1) CFDIL incorporates contextual features into users' preferences modeling by constructing a novel user and app feature portrait. (2) The problem of data sparsity is effectively solved by the use of dense user and app feature portraits, as well as the tensor operations for label sets. (3) CFDIL trains a new deep network structure, which can make accurate app recommendation using the contextual information and attribute information of users and apps. We applied CFDIL on three real datasets and conducted extensive experiments, which showed that CFDIL outperformed the benchmark method.
Early Diagnosis of Skin and Breast Cancer in Women: Influence of Body Image Perception
Authors: Giacomo Dina , Guerra Federica , Ranieri Jessica , Cilli Eleonora , Ciciarelli Valeria , Ventura Alessandra , Ficorella Corrado , Fargnoli Maria Concetta
Published: October 2021

Background. The diagnosis of melanoma and breast cancer may impact many aspects of life with significant reductions in emotional functioning and quality of life. Aims. Aim of the study was to analyze the emotional traits of female patients with oncological diagnosis (early stage melanoma/breast cancer) investigating prevalence and predictors for psychological stress. Methods. A sample of 84 female patients (age range 30-50 years) with diagnosis of melanoma/breast cancer stage T0-T2 participated in the study. The examined emotional variables were: psychological distress, depression, stress, anxiety, metacognitions and body self-perception. Results. Findings showed higher psychological distress in breast cancer than melanoma patients and, that was related to lower positive self-perception of body image. No significant difference between cancer staging. Conclusions. Prevention and intervention protocols must be adapted taking into account tumor type in the adoption of preventive behaviors and compliance with medical recommendations during survivorship.
Better Network Modeling For Link Prediction In Protein-Protein Interaction Networks
Authors: Yuen Ho Yin , Jansson Jesper
Published: October 2021

Background: Protein-protein interaction (PPI) data is an important type of data used in functional genomics. However, inaccuracies in high-throughput experiments often result in incomplete PPI data. Computational techniques are thus used to infer missing data and to evaluate confidence scores, with link prediction being one such approach that uses the structure of the network of PPIs known so far to find good candidates for missing PPIs. Recently, a new idea called the L3 principle introduced biological motivation into PPI link predictions, yielding predictors that are superior to general-purpose link predictors for complex networks. However, the previously developed L3 principle-based link predictors are only an approximate implementation of the L3 principle. As such, not only is the full potential of the L3 principle not realized, they may even lead to candidate PPIs that otherwise fit the L3 principle being penalized. Result: In this article, we propose a formulation of link predictors without approximation that we call ExactL3 (L3E) by addressing missing elements within L3 predictors in the perspective of network modeling. Through statistical and biological metrics, we show that in general, L3E predictors perform better than the previously proposed methods on seven datasets across two organisms (human and yeast) using a reasonable amount of computation time. In addition to L3E being able to rank the PPIs more accurately, we also found that L3-based predictors, including L3E, predicted a different pool of real PPIs than the general-purpose link predictors. This suggests that different types of PPIs can be predicted based on different topological assumptions and that even better PPI link predictors may be obtained in the future by improved network modeling.
High-speed device-independent quantum key distribution against collective attacks
Authors: Zhang Qiang , Liu Wen-Zhao , Zhang Yu-Zhe , Zhen Yi-Zheng , Li Ming-Han , Liu Yang , Fan Jingyun , Xu Feihu , Pan Jian-Wei
Published: October 2021

The security of quantum key distribution (QKD) usually relies on that the users’s devices are well characterized according to the security models made in the security proofs. In contrast,device-independent QKD an entanglement-based protocol permits the security even without any knowledge of the underlying devices. Despite its beauty in theory, device-independent QKD is elusive to realize with current technology. This is because a faithful realization requires ahigh-quality violation of Bell inequality without the fair-sampling assumption. Particularly, in a photonic realization, a rather high detection efficiency is needed where the threshold values depend on the security proofs; this efficiency is far beyond the current reach. Here, both theoretical and experimental innovations yield the realization of device-independent QKD based on a photonic setup. On the theory side, to relax the threshold efficiency for practical deviceindependent QKD, we exploit the random post-selection combined with adding noise for preprocessing, and compute the entropy with complete nonlocal correlations. On the experiment side, we develop a high-quality polarization-entangled photonic source and achieve state-of-theart (heralded) detection efficiency of 87.49%, which outperforms previous experiments and satisfies the threshold efficiency for the first time. Together, we demonstrate device-independent QKD at a secret key rate of 466 bits/s over 20 m standard fiber in the asymptotic limit against collective attacks. Besides, we show the feasibility of generating secret keys at a fiber length of 220 meters. Importantly, our photonic implementation can generate entangled photons at a high rate and in the telecom wavelength, which is desirable for high-speed key generation over long distances. The results not only prove the feasibility of device-independent QKD with realistic devices, but also push the security of communication to an unprecedented level.
Machine Learning and Sustainable Mobility: The Case of the University of Foggia (Italy)
Authors: Cappelletti Giulio Mario , Grilli Luca , Russo Carlo , Santoro Domenico
Published: October 2021

Thanks to the development of increasingly sophisticated machine-learning techniques, it is possible to improve predictions of a certain phenomenon. In this paper, after having analyzed data relating to the mobility habits of University of Foggia (UniFG) community members and deter- mined their emissions of pollutants, we applied machine-learning techniques to these data to estimate the quantities of pollutants (in a certain time period) produced by new subjects not present in the data sets, using very little information. In this way, we developed a method that the university could apply to inform new students about what their emissions of pollutants could be in the near future, through several easily obtainable features. This method could allow the UniFG Rectorate to improve its sustainable mobility policies by encouraging the use of methods that are as appropriate as possible to the users’ needs. In addition, any public/private organization outside the academic environment can use the method, due to the need for little information.
Porous Cu-MOF Nanostructures with Anticancer Properties Prepared by a Controllable Ultrasound-Assisted Reverse Micelle Method
Authors: Zeraati Malihe , Moghaddam-Manesh Mohammadreza , Hosseinzadegan Sara , Kazemzadeh Parya , Chauhan Narendra Pal Singh , Sargazi Ghasem
Published: October 2021

The ultrasonic assisted reverse micelle method was used to create Cu-MOF from Cu(NO3)2•3H2O and 2,6-pyridine dicarboxylic acid in a 1:1 molar proportion. It has been characterized using FT-IR, XRD, nitrogen adsorption analysis SEM and TEM-EDX. Cu-MOF has anticancer properties against MCF-7 breast cancer cells. Cytotoxicity testing was performed on MCF-7 breast cancer cells using the MTT cell viability assay, and cell proliferation and viability were found to be approximately 24 % higher than the control.
Effect of Cultivation Methods on Seed Yield Traits, Oil Yield, and Fatty Acid Compositions of Cultivated Paeonia ostii
Authors: Zhang Tong , Zhang Zheng , Qiao Qi , Liu Wei , Hou Xiaogai
Published: October 2021

Paeonia ostii is recognized as an important oilseed tree peony species with potential as a raw material source for cosmetic and health care products, strong seed setting capacity, high seed oil yield, and abundant omega-3 polyunsaturated fatty acids. P. ostii, commonly called Fengdan, is widely cultivated in China. The cultivation method difference has an important influence on the oil-use feature, which is a key index for evaluating the quality of oilseed crops. This study aimed to select an optimal cultivation method to provide the first reference data for high-yield and high-quality seed oil harvesting and to facilitate the understanding of the quality difference in the formation mechanism of seed oil in cultivated P. ostii. This study selected five representative cultivation methods, open field cultivation, sunny slope cultivation, shady slope cultivation, understory intercropping cultivation, and high-altitude cultivation, and investigated the influence of cultivation method differences on the oil-use feature based on the three aspects of seed yield traits, oil yield, and fatty acid compositions. Six seed yield traits (fruit pod length, fruit pod width, fruit pod thickness, number of fruit pods per plant, 1000-grain weight, and seed yield per plant) and oil yield reached the maximum values of 7.75 cm, 6.99 cm, 1.57 cm, 11.33, 290.45 g, 85.8 g, and 30.41%, respectively, using the understory intercropping cultivation method. Fatty acid compositions were mainly identified as α-linolenic acid, linoleic acid, oleic acid, stearic acid, and palmitic acid, with significant content differences among different cultivation methods (P < 0.05). Functional component α-linolenic acid and total amounts of unsaturated fatty acids reached the maximum values of 46.85% and 65.23%, respectively, with high-altitude cultivation and understory intercropping cultivation. The seed yield traits, oil yield, and total amounts of unsaturated fatty acids were optimal with the understory intercropping cultivation method, whereas high-altitude cultivation was conducive to the accumulation of α-linolenic acid. Understory intercropping cultivation with appropriate altitude increases is recommended as a preponderant cultivation method for high-yield and high-quality seed oil harvesting for this crop.
Modelling COVID-19 Scenarios for the States and Federal Territories of Malaysia
Authors:   School of Mathematical Sciences, Universiti Sains Malaysia, Pulau Pinang, Malaysia, Ahmad Noor Atinah , Mohd Mohd Hafiz ,   School of Mathematical Sciences, Universiti Sains Malaysia, Pulau Pinang, Malaysia, Musa Kamarul Imran ,   School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia, Abdullah Jafri Malin ,   School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia, Othman Nurul Ashikin ,   School of Mathematical Sciences, Universiti Sains Malaysia, Pulau Pinang, Malaysia
Published: October 2021

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 disease, which has become pandemic since December 2019. In the recent months, among five countries in the Southeast Asia, Malaysia has the highest per-capita daily new cases and daily new deaths. A mathematical modelling approach using a Singular Spectrum Analysis (SSA) technique was used to generate data-driven 30-days ahead forecasts for the number of daily cases in the states and federal territories in Malaysia at four consecutive time points between 27 July 2021 and 26 August 2021. Each forecast was produced using SSA prediction model of the current major trend at each time point. The objective is to understand the transition dynamics of COVID-19 in each state by analysing the direction of change of the major trends during the period of study. The states and federal territories in Malaysia were grouped in four categories based on the nature of the transition. Overall, it was found that the COVID-19 spread has progressed unevenly across states and federal territories. Major regions like Selangor, Kuala Lumpur, Putrajaya and Negeri Sembilan were in Group 3 (fast decrease in infectivity) and Labuan was in Group 4 (possible eradication of infectivity). Other states e.g. Pulau Pinang, Sabah, Sarawak, Kelantan and Johor were categorised in Group 1 (very high infectivity levels) with Perak, Kedah, Pahang, Terengganu and Melaka were classified in Group 2 (high infectivity levels). It is also cautioned that SSA provides a promising avenue for forecasting the transition dynamics of COVID-19; however, the reliability of this technique depends on the availability of good quality data.
Elevation of Highly Sensitive Cardiac Troponin T Among End-Stage Renal Disease Patients Without Acute Coronary Syndrome
Authors:   Department of Pathology, Hospital Selayang, Batu Caves, Selangor, Malaysia, Wan Mohd Zamri Wan Nur Aimi , Shafii Noorazliyana ,   Department of Chemical Pathology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia, Tuan Ismail Tuan Salwani ,   Department of Chemical Pathology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia, Zakaria Adlin Zafrulan ,   Department of Pathology, Hospital Raja Perempuan Zainab II, Kota Bharu, Kelantan, Malaysia, Yaacob Najib Majdi ,   Unit of Biostatistics and Research Methodology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia, Che Soh Noor Azlin Azraini ,   Department of Chemical Pathology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia
Published: October 2021

Background: In end-stage renal disease (ESRD), troponin T concentrations can be elevated even without cardiac ischaemia, which hampers the diagnosis of acute myocardial infarction (AMI). The objectives of our study were to determine the proportion of dialysisdependent ESRD patients without acute coronary syndrome (ACS) but with highly sensitive cardiac troponin T (hs-cTnT) levels above the 99th percentile upper reference limit and to evaluate the range of hs-cTnT among this population. Methods: A cross-sectional study was conducted at the haemodialysis (HD) unit of a tertiary hospital in Malaysia from January 2018 to February 2019. Dialysis-dependent ESRD patients were included and those with a recent history of ACS (within 30 days) were excluded. Pre-dialysed serum hs-cTnT levels were measured using Cobas e411. The upper limit of the 99th percentile value for troponin T was 14 ng/L. Results: A total of 150 patients were recruited as study participants. The majority were female (62%) and of Malay ethnicity (94%), and the mean (SD) age was 45.19 (16.36) years old. The hs-cTnT range (min, max) was 11.39–738.30 ng/L and the median (interquartile range [IQR]) of hs-cTnT was 59.20 (83.41) ng/L. Elevated hs-cTnT levels were observed in 149/150 (99%) of the study participants (54/55 [98.2%] of the patients were on HD, and 95/95 [100.0%] of the patients were on continuous ambulatory peritoneal dialysis). Conclusion: This study supports prior research showing that even without ACS, most ESRD patients have elevated concentrations of cardiac troponin. Furthermore, our study illustrates the need to revisit the use of absolute troponin values when making a diagnosis of ACS in ESRD patients.
Formal and Non-formal Skills Improvement for the Marginalised Youth in Uganda
Authors: Mugabi Racheal Ddungu , Nakijoba Rosemary , Nakirijja Deborah Sarah , Sengendo May
Published: October 2021

The aim of the article was to explore ways in which formal and non-formal skills development programmes can be improved for education continuity and employability of marginalised youth. This is attributed to the fact that coronavirus disease (COVID-19) with its related lockdowns is causing not only unprecedented disruption in the provision of skills, but also catalysed innovation in distance learning. A qualitative case study with some elements of action research, systematic inquiry and non-participant classroom observation with capability and empowerment theories supported the inquiries. Thematic analysis was used. Results reveal that while access to skills development was maintained in some spaces through a rapid shift to distance learning, the pre-existing social and digital divides deprived marginalized groups of continued learning and putting them behind schedule. Many institutions and learners lack operational distance-learning platforms, digital skills and devices. Save for the few exceptions, distance learning policies by the government have not yet been able to facilitate the acquisition of practical skills, which are critical components for the success of education and employability. Evidence points not only to pedagogical dimensions with educator’s incompetence to provide a supportive environment, but also to designing structured educational resources versus the abundance of online resources, disruptions to assessment and certification, and a general decline in the quality of practical training causing demotivation among learners and educators. The general increased economic hardship has also increased the likelihood of marginalised youth dropping out of education. The study recommends a robust shift on how skills are delivered-shift to digital literacy and adoption to technology, forge national and regional public private partnerships to increase the availability of accessible distance learning solutions, allocate more financial resources, develop new training programmes by marrying curricula to real life working situations, assess and certify online for educational continuity and employability.
Estimação de Energia Assistida por Redes Neurais para o Calorímetro de Telhas do ATLAS no LHC
Authors: Dias Carlos Cardoso , Peralva Bernardo Sotto-Maior , Hufnagel Mateus , Silva Alessa Monay , Andrade Filho Luciano Manhães , Cerqueira Augusto Santiago , Seixas José Manoel
Published: October 2021

Em calorimetria de altas energias, a energia da partícula pode ser calculada através da estimação da amplitude do sinal produzido e digitalizado pelos canais de leitura. Entretanto, em condições de alta taxa de eventos e alta luminosidade, o sinal de resposta pode ser distorcido devido à presença de sinais proveniente de eventos adjacentes causando o efeito de empilhamento de sinais. Este efeito degrada a eficiência de métodos lineares tipicamente utilizados para estimar os parâmetros de interesse. Desta forma, este trabalho apresenta uma análise de desempenho de uma proposta de estimação da amplitude do sinal utilizando o método atualmente empregado no Calorímetro de Telhas (TileCal) do ATLAS no LHC, assistido por redes neurais artificiais. A rede neural tem a função de corrigir as não-linearidades introduzidas pelo empilhamento de sinais na estimativa linear. Os resultados, comparando diferentes métodos, mostram que a abordagem combinada aumenta consideravelmente a eficiência de estimação da energia em condições de empilhamento de sinais.
Como é ser diferente em administração? A performance de discentes gays e bissexuais em uma graduação heteronormativa
Authors: Mendes Diego Costa , Mendonça José Ricardo Costa de
Published: October 2021

Este estudo objetiva evidenciar a compulsoriedade heterossexual em Administração e sua relação com a performance de discentes gays e bissexuais do curso. Com base na compreensão sobre performatividade, performance, heteronormatividade e matriz de inteligibilidade, foram realizadas entrevistas com 16 discentes (gays e bissexuais) do curso de Administração de uma IES privada e, posteriormente, os enunciados coletados foram trabalhados a partir de análise do discurso. Percebemos que a heteronormatividade evidenciada na prática social da Administração compele práticas compulsórias aos discentes, sendo regida por normas que instigam a repetição de performances legitimadas e que se amparam na compreensão linear entre corpo, sexo e desejo. Os corpos dos discentes circunscritos no curso tendem a ser regulados com base em imposições estabelecidas a partir da compulsoriedade heteronormativa. Acreditamos ainda que a matriz heterossexual possibilita controle social na Administração a partir de elementos legitimados que projetam performances esperadas e que buscam conformar os corpos discentes sobre identidades previamente arquitetadas.
Working out loud: consegue ouvir meu trabalho?
Authors: Tavares Maruza Vieira Barboza , Pinheiro Vanessa Saldanha , Freitas Ana Augusta Ferreira de
Published: October 2021

O objetivo deste estudo é analisar a prática de Working Out Loud (WOL) na mídia social Instagram, com vistas a compreender a maneira como essa narrativa laboral é apresentada pelos indivíduos.  Para tanto, foi conduzida uma coleta de dados manual, quando perfis do Instagram foram utilizados para imersão no contexto da prática do WOL. Com uma abordagem para pesquisa de dados qualitativos nas mídias sociais, o corpus do estudo compreendeu 193 postagens que mostravam o usuário apresentando seu trabalho. Os resultados corroboram a importância do estudo do WOL para o entendimento da forma como o trabalho perpassa a vida pessoal dos indivíduos e revelam o modo como esse fenômeno abre a possibilidade para que indivíduos construam suas identidades enquanto profissionais perante o público das redes sociais, que nem sempre estão inseridos em seus ambientes de trabalho. O gerenciamento de impressões, através de legendas, tags e imagens que promovem exposições, ensinamentos e reflexões, mostra-se como elemento constituinte desse processo.
Dissolved oxygen modelling of the Yamuna River using different ANFIS models
Authors: Arora Sameer , Keshari Ashok K.
Published: October 2021

Dissolved oxygen (DO) is one of the prime parameters for assessing the water quality of any stream. Thus, the accurate estimation of DO is necessary to evolve measures for maintaining the riverine ecosystem and designing appropriate water quality improvement plans. Machine learning techniques are becoming valuable tools for the prediction and simulation of water quality parameters. A study has been performed in the Delhi stretch of the Yamuna River, India, and physiochemical parameters were examined for 5 years to simulate the DO using various machine learning techniques. Simulation and prediction competencies of adaptive neuro fuzzy inference system–grid partitioning (ANFIS–GP) and subtractive clustering (ANFIS–SC) were performed on high dimensional river characteristics. Four different models (M1, M2, M3 and M4) were developed using different combination of input parameters to predict DO. Results obtained from the models were evaluated using root mean square error and coefficient of determination (R2) to identify the appropriate combination of parameters to simulate the DO. Results suggest that both types of ANFIS models work adequately and accurately predict the DO; however, ANFIS–GP outperforms the ANFIS–SC. M4 generated R2 of 0.953 from ANFIS–GP compared to 0.911 from ANFIS–SC.
A review on the application of nanoporous zeolite for sanitary landfill leachate treatment
Authors: Turan Abdullah Zahid , Turan Mustafa
Published: October 2021

This review deals with low-cost nanoporous zeolites for the treatment of sanitary landfill leachate. Organic contaminants and ammoniacal nitrogen are significant parameters in landfill leachate treatment. Adsorption processes are regarded as promising alternative treatment options in this respect. Zeolites are aluminosilicate materials that are widely used in separation, ﬁltration, adsorption and catalysis. Natural zeolite is a low-cost and readily available form of zeolite and is a promising candidate to be used as an ion-exchange material for ammonia and other inorganic pollutant removal from landfill leachate. In this review, adsorption isotherms and kinetic models in batch systems are evaluated and adsorption design parameters of the fixed-bed system are presented. Studies on ammonia removal from landfill leachate via zeolites have been thoroughly investigated. Leachate treatment systems combined with zeolites are presented. Cost of zeolites are also reported in comparison with other adsorbents. The investigated studies demonstrate that activated zeolite can improve the removal of chemical oxygen demand, NH3-N and colour significantly compared to the case where raw zeolite is used. Moreover, the composite of activated carbon and zeolite is also favorable for ammonia removal according to reported findings, where best adsorptive removal is attained on the composite media (24.39 mg/g).
Small Molecules as LIM Kinase Inhibitors
Authors: Bukhari Syed N.A. , Tandiary Michael A. , Al-Sanea Mohammad M. , Abdelgawad Mohamed A. , Chee Chin F. , Hussain Muhammad A.
Published: October 2021

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LIMK1 and LIMK2 are involved in the regulation of cellular functions that depend
on the dynamics of actin cytoskeleton. Disregulation of LIM kinases has been associated
with diseases, such as tumor progression and metastasis, viral infection, and ocular
diseases. Motivated by this, numerous studies have been carried out to discover small organic
molecules capable of inhibiting LIM kinase effectively and selectively. In this review,
a comprehensive survey of small organic molecules for LIM kinase inhibitors is reported,
together with SAR study results, and the synthesis of these inhibitors.
Discovery, Development and Design of Anthocyanins-Inspired Anticancer Agents: A
Comprehensive Review
Authors: Majhi Sasadhar
Published: October 2021

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Mother Nature is an indispensable source of bioactive natural products. Bioactive secondary metabolites
have played a crucial role in the drug development and discovery process; mainly, anticancer and antibiotic molecules
are extensively enriched with molecules of natural origin. Anthocyanins are water-soluble secondary metabolites found
in most species in the plant domain, especially flowers, fruits, and tubers. These natural vacuolar pigments belong to
the chemical class of phenolic moieties, which are responsible for the shiny orange, red, blue, pink, and violet colors in
the fruits, flowers, and vegetables. Chemically, anthocyanins comprise a core structure in the form of flavylium cation
or 2-phenylbenzopyrylium, and these natural colorants are polyhydroxy and polymethoxy analouges of this flavylium
cation and can have sugar moieties or acylated groups linked at different positions. Currently, these molecules have
raised a growing interest because of their wide range of colors, innocuous and beneficial health effects, and commercial
application in functional foods, nutraceuticals, pharmaceutical and cosmetic industries. However, interest in anthocyanin
derivatives has noticeably enhanced in recent years due to their higher stability, improved bioavailability in
biological matrices, and better use in food matrices and cosmetic products. Due to the enormous potential of natural
anthocyanins and their derivatives, this review tries to cover syntheses of anthocyanins and their analogues, chemical
derivatization of anthocyanins, and anticancer activities, such as breast, colorectal, leukemia, lung, prostate, and skin
cancer of anthocyanins efficiently.
Strengthening North-South Relations: The Case of EU and ECOWAS Cooperation
Authors: Prinanda Devita , Prasodjo Haryo
Published: October 2021

Regional integration is discussing cooperation among states in a region and the influence of external states or organizations. The cooperation among regions is known as inter-regionalism. As a leader in regional integration, European Union (EU) has been cooperating with the other regions since their name was European Economic Community. Firstly, Europe established relations in the form of political dialogue and cooperation with ASEAN and Asian countries. For this occasion, the EU established Asia Europe Meeting (ASEM). Subsequently, the EU created external relations with African, Caribbean, & Pacific (ACP), South American, etc. This research elaborates on the relation of the EU with the West African region. The Economic Community of West African States (ECOWAS) is the regional institution chosen by the EU to engage in the relationship. Some scholars acknowledged that ECOWAS is one of the most organized institutions in the African Region. Asymmetric relation between EU and ECOWAS denotes the relation of The North and The South countries. By analyzing the inter-regionalism framework, this paper exercises a liberal institutional perspective as the main paradigm. The results found that inter-regionalism could reinforce strong institutions in both regions.