Miracle-dz/UniFAR-FTUs huggingface dataset:
Forest covers, land fire hotspots, and atmospheric pollutions (CO, SO2) in the lower Batanghari River Basin landscape during dry season (June-August 2021)

Abstract. Wibowo AA, Basukriadi A, Nurdin E. 2021. Forest covers, land fire hotspots, and atmospheric pollutions (CO, SO2) in the lower Batanghari River Basin landscape during dry season (June-August 2021). Biodiversitas 22: 5678-5687. Land fire is a major threat to the intact forest in Indonesia, including the rainforests of Sumatra. Land fires are caused by several factors, ranging from deforestation, slash and burn to farm, and also weather where land fires occur during dry seasons. Land fires that occur in forests can release significant amounts of atmospheric pollution in the form of CO and SO2 emissions. Since there is a paucity of information about land fire hotspot distribution and atmospheric pollution in Sumatra’s forest, this study aims to assess the distribution and impacts of land fires within the lower Batanghari forest landscape on atmospheric pollution during the dry season from June to August 2021. The study was conducted in 15 sampling locations covering three districts in the lower Batanghari landscape. The method uses a coupled ground-based and remote sensing measurement. For ground-based measurement, the CO and SO2 emissions were determined based on in-situ observation of burned biomass in the field and calculation using Seiler and Crutzen equation. While the land fire hotspots were detected using combinations of VIIRS (Visible Infrared Imaging Radiometer Suite) and MODIS (Moderate-resolution Imaging Spectroradiometer) remote sensing sensors. The result shows that 65.85% of the land fires that happened in the lower Batanghari landscape occurred within forests. In West Tanjung Jabung District, 70.37% of land fires were observed within forests, in East Tanjung Jabung was 60% and 55.55% for Muaro Jambi District. The weekly land fires, CO, and SO2 emissions were high in June as the onset of dry season. In West Tanjung Jabung, this district has the highest weekly land fires, CO, and SO2 emissions. The ranges of CO and SO2 emissions when land fires occur were 200-350 ppbv and 1.5-2.75 ug/m3. The Principal Component Analysis confirms that the frequency of land fires was positively correlated with CO rather than SO2 emissions. This concludes the magnitude of land fires in forests that have the potential to release significant atmospheric pollutants.
Identification and differential expression of cold-stress-responsive microRNAs in cold-tolerant and -susceptible Hemerocallis fulva varieties

ABSTRACT Exploring microRNA (miRNA) expression patterns in Hemerocallis under low-temperature stress helps understanding the mechanisms of miRNA-mediated stress responses. Here, eight separate libraries were generated from the leaves and roots of two different varieties, cold-tolerant ‘Jinyan 7’ and cold-sensitive ‘Lucretius 4’, which were exposed to 20°C and −4°C for 8 h. In total, 333 cold-responsive miRNAs, including 85 putative novel and 248 conserved miRNAs, were identified during different temperature treatments. Under cold-stress conditions, two miRNAs were down-regulated and one was up-regulated in the roots, and no differentially expressed miRNAs were detected in the leaves in ‘Lucretius 4’. In ‘Jinyan 7’, there were two novel and one conserved differentially expressed miRNAs in leaves, whereas three conserved and two novel miRNAs were differentially expressed in roots. The target genes were mainly involved in metabolic processes and cellular components. The differential expression levels of 10 miRNAs were validated using quantitative RT–PCR. Some candidate miRNAs (e.g. ath-miR165a, ath-miR166a, ath-miR395a and novel-miR67) may be involved in plant response-related processes to low-temperature.
Single-Cell Analysis Uncovers Osteoblast Factor Growth Differentiation Factor 10 as Mediator of Vascular Smooth Muscle Cell Phenotypic Modulation Associated with Plaque Rupture in Human Carotid Artery Disease

(1) Background: Vascular smooth muscle cells (VSMCs) undergo a complex phenotypic switch in response to atherosclerosis environmental triggers, contributing to atherosclerosis disease progression. However, the complex heterogeneity of VSMCs and how VSMC dedifferentiation affects human carotid artery disease (CAD) risk has not been clearly established. (2) Method: A single-cell RNA sequencing analysis of CD45− cells derived from the atherosclerotic aorta of Apolipoprotein E-deficient (Apoe−/−) mice on a normal cholesterol diet (NCD) or a high cholesterol diet (HCD), respecting the site-specific predisposition to atherosclerosis was performed. Growth Differentiation Factor 10 (GDF10) role in VSMCs phenotypic switch was investigated via flow cytometry, immunofluorescence in human atherosclerotic plaques. (3) Results: scRNAseq analysis revealed the transcriptomic profile of seven clusters, five of which showed disease-relevant gene signature of VSMC macrophagic calcific phenotype, VSMC mesenchymal chondrogenic phenotype, VSMC inflammatory and fibro-phenotype and VSMC inflammatory phenotype. Osteoblast factor GDF10 involved in ossification and osteoblast differentiation emerged as a hallmark of VSMCs undergoing phenotypic switch. Under hypercholesteremia, GDF10 triggered VSMC osteogenic switch in vitro. The abundance of GDF10 expressing osteogenic-like VSMCs cells was linked to the occurrence of carotid artery disease (CAD) events. (4) Conclusions: Taken together, these results provide evidence about GDF10-mediated VSMC osteogenic switch, with a likely detrimental role in atherosclerotic plaque stability.
Dynamical simulation of marine diesel crankshaft system

Aiming at vibration analysis of marine diesel engine shaft systems and effects on hull structure,the dynamics model of rigid body in the marine diesel engine shaft systems of type 4160 were built by the software of SolidWorks and ADAMS.The motions and dynamics of crankshaft system were simulated based on virtual prototype,and the simulating curves of pistons motions,action force on the link and crank-pin were studied.The results indicate that simulation model conforms to its reality,and a new design method is given for further study of the diesel engine vibration.
How we engage the principles of nationalism in making sense of uncertainty and disruptive social change

ABSTRACT Much attention has been devoted to the salience of nationalism in crisis times. At the micro-level, people often talk about the nation when they perceive established social norms as disrupted. Yet, the role of individual agency in reproducing nationalism in such contexts has been underexplored. Everyday nationalist practices are understood as following an unreflective adoption of nationalist ideology. This article challenges this perspective and proposes approaching nationalism as an “engaged ideology”. This means attending also to people’s active reflection on nationalist principles. A discussion of in-depth interviews from Russia provides an empirical illustration. I show how interviewees deliberate over the continuity and progress of the nation in making sense of uncertain times. The discussion highlights the interaction of ideology and agency in everyday nationalism. In doing so, it opens new avenues for exploring connections between nationalism and crisis.
A New Species of Cone Shell (Gastropoda: Conidae) from the Saharan Coast of Northwestern Africa

A new species of Lautoconus (Conidae: Puncticulinae) is described from the intertidal rocky environments of Dahkla Bay, central Western Sahara. The new species is most similar to L. guanche from the Canary Islands, but differs in having a stockier, more darkly-colored, and lowerspired shell. The new species, here named L. saharicus n. sp. , is endemic to Dahkla Bay and the Dahkla area of Western Sahara, roughly 400 km south of the Canary Islands.
Overview of Loss Sensitivity Analysis in Modern Distribution Systems

Distribution system planning and operation has seen many structural changes due to the increased participation of consumers in the energy market and the adaptation of new technologies such as distributed energy resources (DERs), electric vehicles (EV) and local energy storage systems (ESSs). Despite the convenience of such technologies and the gradual drop in their prices, new technical challenges (e.g., excessive power losses) have emerged at the system level. Over the past few decades, power loss minimization in distribution systems has gained popularity and the need for loss sensitivity analysis (LSA) frameworks has become a necessity for its successful implementation. Existing work on LSA mostly focuses on system planning aspects through DER optimal placement and sizing. However, enabling LSA-based system operational applications is a vital step toward the successful transition to modern distribution systems (MDSs). Therefore, this paper presents a comprehensive overview on the state of the art in LSA for MDSs. First, the theoretical formulations of existing LSA methods are summarized. Then, the applications of LSA in distribution systems are highlighted. Finally, based on the analysis of literature, open research gaps and future research pathways are discussed.
The diversity of endophitic fungi on Annua mutant plantation (Artemisia annua L.) based on ITS rDNA marker

Artemisia annua is a plant that produces artemisinin which is an antimalarial compound. The production of artemisinin compounds is influenced by the interaction of endophytic molds with their host plants. This study was conducted to identify endophytic molds found in plant tissues of A. annua which previously had been treated by mutations with Ethyl metahnesulfonate (EMS) to increase artemisinin production levels. Identification was carried out by using BLAST analysis, while the phylogenetic tree analysis used the minimum evolution (ME) method on MEGA 7 and the maximum parsimony (MP) method on PAUP 4.0b10. Phylogenetic analysis used noncoding sequences of the Internal Transcribe Spacer (ITS) rDNA region. Twelve endophytic molds (8 isolates from leaves, 2 isolates from stems, 1 isolate from petioles, and 1 isolate from flowers) in the Biogen Culture collection. This study identified to the species level phylogenetically. The endophytic molds identified were dominated by the Sordariomycetes group. It consist of 4 species, such as Clonostachys rosea, Fusarium oxysporum, Microascus gracillis, and Scopulariopsis brevicaulis, and another species belonging to the Eurotiomycetes group, is Aspergillus sydowii. A total of 4 families were obtained, such as Nectriaceae, Bionectriaceae, Microascaceae, and Aspergillaceae. All acquired classes belong to the Ascomycota division.
Redundancy cancellation of compressed measurements by QRS complex alignment

The demand for long-term continuous care has led healthcare experts to focus on development challenges. On-chip energy consumption as a key challenge can be addressed by data reduction techniques. In this paper, the pseudo periodic nature of ElectroCardioGram(ECG) signals has been used to completely remove redundancy from frames. Compressing aligned QRS complexes by Compressed Sensing (CS), result in highly redundant measurement vectors. By removing this redundancy, a high cluster of near zero samples is gained. The efficiency of the proposed algorithm is assessed using the standard MIT-BIH database. The results indicate that by aligning ECG frames, the proposed technique can achieve superior reconstruction quality compared to state-of-the-art techniques for all compression ratios. This study proves that by aligning ECG frames with a 0.05% unaligned frame rate(R-peak detection error), more compression could be gained for PRD > 5% when 5-bit non-uniform quantizer is used. Furthermore, analysis done on power consumption of the proposed technique, indicates that a very good recovery performance can be gained by only consuming 4. 9μW more energy per frame compared to traditional CS.
Research on the Timetable Optimization Model of Public Traffic to Improve Service Quality

With the pace of social and economic development,the focus of public traffic scheduling is gradually changing from the previous pure emphasis on the economic benefits of public traffic enterprises to improving their service quality.This paper presented an optimization scheduling model for a non-equivalent coordinated public transport network to maximize passenger's benefit under the guidance of the basic idea while meeting the objective function,and to minimize the total cost of passenger and public traffic operators.The research used an algorithm-hybrid of Genetic-simulated annealing(GA-SA) to optimize the frequency of public traffic scheduling,while using public traffic survey data of Shanghai to verify the model.The results indicate that the optimal model has strong practicability
“I got a bunch of weed to help me through the withdrawals”: Naturalistic cannabis use reported in online opioid and opioid recovery community discussion forums

A growing body of research has reported on the potential opioid-sparing effects of cannabis and cannabinoids, but less is known about specific mechanisms. The present research examines cannabis-related posts in two large online communities on the Reddit platform (“subreddits”) to compare mentions of naturalistic cannabis use by persons self-identifying as actively using opioids versus persons in recovery. We extracted all posts mentioning cannabis-related keywords (e.g., “weed”, “cannabis”, “marijuana”) from December 2015 through August 2019 from an opioid use subreddit and an opioid recovery subreddit. To investigate how cannabis is discussed at-scale, we identified and compared the most frequent phrases in cannabis-related posts in each subreddit using term-frequency-inverse document frequency (TF-IDF) weighting. To contextualize these findings, we also conducted a qualitative content analysis of 200 random posts (100 from each subreddit). Cannabis-related posts were about twice as prevalent in the recovery subreddit (n = 908; 5.4% of 16,791 posts) than in the active opioid use subreddit (n = 4,224; 2.6% of 159,994 posts, p < .001). The most frequent phrases from the recovery subreddit referred to time without using opioids and the possibility of using cannabis as a “treatment. ” The most frequent phrases from the opioid subreddit referred to concurrent use of cannabis and opioids. The most common motivations for using cannabis were to manage opioid withdrawal symptoms in the recovery subreddit, often in conjunction with anti-anxiety and GI-distress “comfort meds,” and to enhance the “high” when used in combination with opioids in the opioid subreddit. Despite limitations in generalizability from pseudonymous online posts, this examination of reports of naturalistic cannabis use in relation to opioid use identified withdrawal symptom management as a common motivation. Future research is warranted with more structured assessments that examines the role of cannabis and cannabinoids in addressing both somatic and affective symptoms of opioid withdrawal.
Reducing calibration time in motor imagery-based BCIs by data alignment and empirical mode decomposition

One of the major reasons that limit the practical applications of a brain-computer interface (BCI) is its long calibration time. In this paper, we propose a novel approach to reducing the calibration time of motor imagery (MI)-based BCIs without sacrificing classification accuracy. The approach aims to augment the training set size of a new subject by generating artificial electroencephalogram (EEG) data from a few training trials initially available. The artificial EEG data are obtained by first performing empirical mode decomposition (EMD) and then mixing resulting intrinsic mode functions (IMFs). The original training trials are aligned to common reference point with Euclidean alignment (EA) method prior to EMD and pooled together with artificial trials as the expended training set, which is input into a linear discriminant analysis (LDA) classifier or a logistic regression (LR) classifier. The performance of the proposed algorithm is evaluated on two motor imagery (MI) data sets and compared with that of the algorithm trained with only real EEG data (Baseline) and the algorithm trained with expanded EEG data by EMD without data alignment. The experimental results showed that the proposed algorithm can significantly reduce the amount of training data needed to achieve a given performance level and thus is expected to facilitate the real-world applications of MI-based BCIs.
Multiple haplotype-based analyses provide genetic and evolutionary insights into tomato fruit weight and composition

Abstract Improving fruit quality traits such as metabolic composition remains a challenge for tomato breeders. To better understand the genetic architecture of these traits and decipher the demographic history of the loci controlling tomato quality traits, we applied an innovative approach using multiple haplotype-based analyses, aiming to test the potentials of haplotype based study in association and genomic prediction studies. We performed and compared haplotype vs SNP-based associations (hapQTL) with multi-locus mixed model (MLMM), focusing on tomato fruit weight and metabolite contents (i.e. sugars, organic acids and amino acids). Using a panel of 163 tomato accessions genotyped with 5995 SNPs, we detected a total of 784 haplotype blocks, with an average size of haplotype blocks ~58 kb. A total of 108 significant associations for 26 traits were detected thanks to Haplotype/SNP-based Bayes models. Haplotype-based Bayes model (97 associations) outperformed SNP-based Bayes model (50 associations) and MLMM (53 associations) in identifying marker-trait associations as well as in genomic prediction (especially for those traits with moderate to low heritability). To decipher the demographic history, we identified 24 positive selective sweeps using the integrated haplotype score (iHS). Most of the significant associations for tomato quality traits were located within selective sweeps (54.63% and 71.7% in hapQTL and MLMM models, respectively). Promising candidate genes were identified controlling tomato fruit weight and metabolite contents. We thus demonstrated the benefits of using haplotypes for evolutionary and genetic studies, providing novel insights into tomato quality improvement and breeding history.
Delayed Admission to the Intensive Care Unit and Mortality of Critically Ill Adults: Systematic Review and Meta-analysis

Delayed admission of patients to the intensive care unit (ICU) is increasing worldwide and can be followed by adverse outcomes when critical care treatment is not provided timely. This systematic review and meta-analysis appraised and synthesized the published literature about the association between delayed ICU admission and mortality of adult patients. Articles published from inception up to August 2021 in English-language, peer-reviewed journals indexed in CINAHL, PubMed, Scopus, Cochrane Library, and Web of Science were searched by using key terms. Delayed ICU admission constituted the intervention, while mortality for any predefined time period was the outcome. Risk for bias was evaluated with the Newcastle-Ottawa Scale and additional criteria. Study findings were synthesized qualitatively, while the odds ratios (ORs) for mortality with 95% confidence intervals (CIs) were combined quantitatively. Thirty-four observational studies met inclusion criteria. Risk for bias was low in most studies. Unadjusted mortality was reported in 33 studies and was significantly higher in the delayed ICU admission group in 23 studies. Adjusted mortality was reported in 18 studies, and delayed ICU admission was independently associated with significantly higher mortality in 13 studies. Overall, pooled OR for mortality in case of delayed ICU admission was 1.61 (95% CI 1.44-1.81). Interstudy heterogeneity was high (I2 = 66.96%). According to subgroup analysis, OR for mortality was remarkably higher in postoperative patients (OR, 2.44, 95% CI 1.49-4.01). These findings indicate that delayed ICU admission is significantly associated with mortality of critically ill adults and highlight the importance of providing timely critical care in non-ICU settings.
Variations within Toll‐like receptor (TLR) and TLR signaling pathway‐related genes and their synergistic effects on the risk of Guillain‐Barré syndrome

Guillain‐Barré syndrome (GBS) is the commonest post‐infectious polyradiculopathy. Although genetic background of the host seems to play an important role in the susceptibility to GBS, genes conferring major risk are not yet known. Dysregulation of Toll‐like receptor (TLR) molecules exacerbates immune‐inflammatory responses and the genetic variations within TLR pathway‐related genes contribute to differential risk to infection. The aim of this study was to delineate the impact of genetic variations within TLR2, TLR3, and TLR4 genes as well as TLR signaling pathway‐related genes such as MyD88, TRIF, TRAF3, TRAF6, IRF3, NFκβ1, and IκBα on risk of developing GBS. Fourteen polymorphisms located within TLR2 (rs3804099, rs111200466), TLR3 (rs3775290, rs3775291), TLR4 (rs1927911, rs11536891), MyD88 (rs7744, rs4988453), TRIF (rs8120), TRAF3 (rs12147254), TRAF6 (rs4755453), IRF3 (rs2304204), NFκβ1 (rs28362491), and IκBα (rs696) genes were genotyped in 150 GBS patients and 150 healthy subjects either by PCR‐RFLP or TaqMan Allelic Discrimination Assay. Genotypes of two polymorphic variants, Del/Del of rs111200466 insertion and deletion (INDEL) polymorphism of TLR2 gene and TT of rs3775290 single nucleotide polymorphism (SNP) of TLR3 gene had significantly higher frequencies among GBS patients, while the frequencies of TT genotype of rs3804099 SNP of TLR2 gene and TT genotype of rs11536891 SNP of TLR4 gene were significantly higher in controls. Gene‐gene interaction study by Multifactor Dimensionality Reduction analysis also suggested a significant combined effect of TLR2, and NFκβ1 genes on the risk of GBS. The SNPs in the IκBα and IRF3 genes correlated with severity of GBS. The genes encoding TLRs and TLR signaling pathway‐related molecules could serve as crucial genetic markers of susceptibility and severity of GBS.
Impacts of using a performance measurement system in supply chain management: a case study

The study examines how the utilisation of a new performance measurement system (PMS) influences supply chain management (SCM) and what kind of impacts the new system has on the performance of the supply chain. The paper utilises a longitudinal research setting where the data was gathered in two semi-structured interview studies after an action research project in which a new measurement system was designed and developed. The findings show how a PMS serves as a catalyst of inter-organisational knowledge transfer and promotes shared learning. The results also show how knowledge transfer and shared learning led to improved performance of the supply chain. The paper contributes by opening up the practical mechanisms through which performance measurement provides value for SCM and by showing how inter-organisational transfer of performance information catalyses learning and performance improvement. The paper looks beyond the design of performance measures and provides a view on the practice of supply chain performance management. The paper illustrates how sharing performance information amongst supply chain companies improves managers’ awareness of shared targets and the status of network operations. This also resulted in improved performance in the studied case network. Overall, the results encourage organisations to engage in network-level performance measurement and share performance information with their network partners.