Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulations of quintessential cold dark matter: beyond the cosmological constant

We study the non-linear growth of cosmic structure in different dark energy models, using large volume N-body simulations. We consider a range of quintessence models which feature both rapidly and slowly varying dark energy equations of state, and compare the growth of structure to that in a universe with a cosmological constant. We use a four-parameter equation of state for the dark energy which accurately reproduces the quintessence dynamics over a wide range of redshifts. The adoption of a quintessence model changes the expansion history of the universe, the form of the linear theory power spectrum and can alter key observables, such as the horizon scale and the distance to last scattering. We incorporate these effects into our simulations in stages to isolate the impact of each on the growth of structure. The difference in structure formation can be explained to first order by the difference in growth factor at a given epoch; this scaling also accounts for the non-linear growth at the 15 per cent level. We find that quintessence models that are different from Λ cold dark matter (ΛCDM) both today and at high redshifts (z∼ 1000), and which feature late (z 0 compared to ΛCDM and so measurements of the mass function should allow us to distinguish these quintessence models from a cosmological constant. However, we find that a second class of quintessence models, whose equation of state makes an early (z > 2) rapid transition to w=−1, cannot be distinguished from ΛCDM using measurements of the mass function or the BAO, even if these models have non-negligible amounts of dark energy at early times.
eAgri: Smart Agriculture Monitoring Scheme using Machine Learning Strategies

The logic of Machine Learning and its predictive strategies are applied to many different applications to attain good benefits over now-a-days. This paper associates the machine learning concept to improve the production on agricultural field as well as the novel adaptive technologies are associated into this learning concept to make a proper agricultural monitoring system in fine manner. This paper is intended to design a new Agricultural Monitoring robot called eAgriBot, in which it integrates the logic of Machine Learning and produce an intelligent predictions to prevent the crops from affections including weather conditions, rainfall and soil water level. In parallel, the eAgriBot contains a high resolution digital camera to capture the pictures of the crops and maintains that into the server unit in proper manner. In literature, there are many approaches designed to provide an automated watering system, systematic pesticide spraying and so on. But all are dependent on the human operations, in which the automatic watering system requires the manual trigger from either SMS or other internet associated operations; similarly the systematic pesticide mechanism requires the same kind of trigger to perform the action. These cases are critical in terms of monitoring the agricultural field from remote environment. The concept of Internet of Things (IoT) is associated over this approach to push and update the agricultural data collected by the eAgriBot to the Cloud Server. This entire process is controlled and manipulated by the novel machine learning strategy called Smart Learning Assisted Data Manipulation (SLADM), in which it is derived from the traditional Random Forest Classification logic with specific parameter modification called dynamic threshold fixation. In general the Random Forest logic uses the constant threshold for data processing, but in this approach dynamic principles are applied to improve the prediction accuracy. With the help of this system plants leaf disease can easily be monitored with the help of digital camera associated with the eAgriBot. It captures the crop field images and pass it to the server end for processing, in which the server end accumulates that and process that by using proposed machine learning called Smart Learning Assisted Data Manipulation. The proposed SLADM scheme is designed robustly for analyzing the both the image and data content, so that the logic identifies the severity in leaves and the data as well. In case of any severity level mismatching found by the algorithm, it immediately notifies that to the respective farmer to take an appropriate action to save the plants from the disease spread. The data available into the cloud server can easily monitored by the farmers from anywhere in the globe as well as this approach of SLADM provides an accurate agricultural field predictions, so that the farmers can easily monitor the field without any complexities and attain good production level easily
The Cost of Application-Class Processing: Energy and Performance Analysis of a Linux-Ready 1.7-GHz 64-Bit RISC-V Core in 22-nm FDSOI Technology

The open-source RISC-V instruction set architecture (ISA) is gaining traction, both in industry and academia. The ISA is designed to scale from microcontrollers to server-class processors. Furthermore, openness promotes the availability of various open-source and commercial implementations. Our main contribution in this paper is a thorough power, performance, and efficiency analysis of the RISC-V ISA targeting baseline “application class” functionality, i.e., supporting the Linux OS and its application environment based on our open-source single-issue in-order implementation of the 64-bit ISA variant (RV64GC) called Ariane. Our analysis is based on a detailed power and efficiency analysis of the RISC-V ISA extracted from silicon measurements and calibrated simulation of an Ariane instance (RV64IMC) taped-out in GlobalFoundries 22FDX technology. Ariane runs at up to 1.7-GHz, achieves up to 40-Gop/sW energy efficiency, which is superior to similar cores presented in the literature. We provide insight into the interplay between functionality required for the application-class execution (e.g., virtual memory, caches, and multiple modes of privileged operation) and energy cost. We also compare Ariane with RISCY, a simpler and a slower microcontroller-class core. Our analysis confirms that supporting application-class execution implies a nonnegligible energy-efficiency loss and that compute performance is more cost-effectively boosted by instruction extensions (e.g., packed SIMD) rather than the high-frequency operation.
The density variance–Mach number relation in supersonic turbulence – I. Isothermal, magnetized gas

It is widely accepted that supersonic, magnetized turbulence plays a fundamental role for star formation in molecular clouds. It produces the initial dense gas seeds out of which new stars can form. However, the exact relation between gas compression, turbulent Mach number and magnetic field strength is still poorly understood. Here, we introduce and test an analytical prediction for the relation between the density variance and the rms Mach number in supersonic, isothermal, magnetized turbulent flows. We approximate the density and velocity structure of the interstellar medium as a superposition of shock waves. We obtain the density contrast considering the momentum equation for a single magnetized shock and extrapolate this result to the entire cloud. Depending on the field geometry, we then make three different assumptions based on observational and theoretical constraints: B independent of ρ, B∝ρ1/2 and B∝ρ. We test the analytically derived density variance–Mach number relation with numerical simulations, and find that for B∝ρ1/2, the variance in the logarithmic density contrast, , fits very well to simulated data with turbulent forcing parameter b= 0.4, when the gas is super-Alfvenic. However, this result breaks down when the turbulence becomes trans-Alfvenic or sub-Alfvenic, because in this regime the turbulence becomes highly anisotropic. Our density variance–Mach number relations simplify to the purely hydrodynamic relation as the ratio of thermal to magnetic pressure β0∞.
Retração acentual e verbos transitivos com leitura intransitiva

The focus of this paper is on the relation between syntax and prosody,by discussing the role of the empty syntactic categories in the application of the stress shift rule. The discussion about the influence of empty categories on phonological processes is not new. Usually, phonology papers argue that the access to syntax is indirect, and there is no access to phonological empty syntactic categories (cf. NESPOR;VOGEL, 1986). However, Santos (2002) argues that phonological empty syntactic categories can intervene on the rhythmic organization of utterances. She defends that pro intervene on stress shift rule, while trace is not taken into account for that rule. In order to show that,she tests utterances with stress clash between verb and adverb.In this presentation, the syntactic structures with verbs which can have a transitive or intransitive reading are tested with pro.The hypothesis is that when there is a transitive reading, the stress clash can not be solved. In the sentences where the intransitive reading is possible, there is no pro between the verb and adverb, and the stress shift rule is allowed. This prediction can be used as an evidence which favors Galves (1989) analysis that null object in Brazilian Portuguese is a pro, and not a trace.
Dark Matter: The evidence from astronomy, astrophysics and cosmology

Department of Physics, FI-00014 University of Helsinki, FinlandE-mail: matts.roos@helsinki.fiAbstract. Dark matter has been introduced to explain many independent gravitationale ects at di erent astronomical scales, in galaxies, groups of galaxies, clusters, superclustersand even across the full horizon. This review describes the accumulated astronomical,astrophysical, and cosmological evidence for dark matter. It is written at a non-specialistlevel and intended for an audience with little or only partial knowledge of astrophysics orcosmology.
CoNICE: Consensus in Intermittently-Connected Environments by Exploiting Naming With Application to Emergency Response

In many scenarios, information must be disseminated over intermittently-connected environments when the network infrastructure becomes unavailable, e.g., during disasters where first responders need to send updates about critical tasks. If such updates pertain to a shared data set, dissemination consistency is important. This can be achieved through causal ordering and consensus. Popular consensus algorithms, e.g., Paxos, are most suited for connected environments. While some work has been done on designing consensus algorithms for intermittently-connected environments, such as the One-Third Rule (OTR) algorithm, there is still need to improve their efficiency and timely completion. We propose CoNICE, a framework to ensure consistent dissemination of updates among users in intermittently-connected, infrastructure-less environments. It achieves efficiency by exploiting hierarchical namespaces for faster convergence, and lower communication overhead. CoNICE provides three levels of consistency to users, namely replication, causality and agreement. It uses epidemic propagation to provide adequate replication ratios, and optimizes and extends Vector Clocks to provide causality. To ensure agreement, CoNICE extends OTR to also support long-term network fragmentation and decision invalidation scenarios; we define local and global consensus pertaining to within and across fragments respectively. We integrate CoNICE’s consistency preservation with a naming schema that follows a topic hierarchy-based dissemination framework, to improve functionality and performance. Using the Heard-Of model formalism, we prove CoNICE’s consensus to be correct. Our technique extends previously established proof methods for consensus in asynchronous environments. Performing city-scale simulation, we demonstrate CoNICE’s scalability in achieving consistency in convergence time, utilization of network resources, and reduced energy consumption.
E-Service Quality Model for Assessing Customer Satisfaction of Mobile Banking Service

Banks are now extending their services from the traditional face-to-face banking interactions to a self-service system. Although mobile banking has grown exponentially, many users are not confident to transact using their phones due to the low e-service quality of mobile banking. This study proposes a model for assessing the e-service quality of mobile banking while examining the relationship between such e-service dimensions and customer satisfaction. The primary data obtained from users of the mobile banking service in Nigeria were measured and analysed. A total number of 156 responses were obtained and analysed using structural equation modelling (SEM). The results show that app design, fulfilment and security are positively significant to customer satisfaction. Hence, the findings provide guidance and useful information to service providers on how the e-service quality of mobile banking systems can be improved.
Identification of SNPs and Candidate Genes Associated with Salt Stress in Two Korean Sorghum Cultivars and Understanding Selection Pressures in the Breeding Process

One of the abiotic stresses, salt stress, has an impact on the production and development of crops around the world. Sorghum is a functional genomics model crop of C4 plants due to its small genome size, and it is suitable for providing a clue to the mechanism associated with salt tolerance at the transcriptomic level. However, the mechanism of salt-related genes in sorghum has not been well described. RNA sequencing, using QuantSeq, was performed on two Korean cultivars, ‘Sodamchal’ and ‘Nampungchal’, which are known to have different intensities in response to salt stress, between a control and high-salinity treatment over a different time-course. In addition, physiological responses such as the proline, anthocyanin, chlorophyll, and reducing sugar contents were evaluated under the salt-stress treatment between these two sorghum cultivars. Moreover, differentially expressed genes (DEGs) between the Nampungchal and Sodamchal cultivars were identified in their leaves and roots, respectively. Moreover, the function of DEGs was confirmed through GO classification and KEGG pathway. We also analyzed the correlation between the selection pressure with DEGs by identifying Ka/Ks of DEGs. In the breeding process, the role of positive or negative selected genes was analyzed. Therefore, a new hypothesis on selection pressure was proposed from the breeding perspective of cultivars. A comparative analysis of the two sorghum cultivars provides candidate genes involved in the salt-stress response and may offer a better understanding of the salt-tolerance mechanism in sorghum.
Molybdenum Cofactor Deficiency in Humans

Molybdenum cofactor (Moco) deficiency (MoCD) is characterized by neonatal-onset myoclonic epileptic encephalopathy and dystonia with cerebral MRI changes similar to hypoxic–ischemic lesions. The molecular cause of the disease is the loss of sulfite oxidase (SOX) activity, one of four Moco-dependent enzymes in men. Accumulating toxic sulfite causes a secondary increase of metabolites such as S-sulfocysteine and thiosulfate as well as a decrease in cysteine and its oxidized form, cystine. Moco is synthesized by a three-step biosynthetic pathway that involves the gene products of MOCS1, MOCS2, MOCS3, and GPHN. Depending on which synthetic step is impaired, MoCD is classified as type A, B, or C. This distinction is relevant for patient management because the metabolic block in MoCD type A can be circumvented by administering cyclic pyranopterin monophosphate (cPMP). Substitution therapy with cPMP is highly effective in reducing sulfite toxicity and restoring biochemical homeostasis, while the clinical outcome critically depends on the degree of brain injury prior to the start of treatment. In the absence of a specific treatment for MoCD type B/C and SOX deficiency, we summarize recent progress in our understanding of the underlying metabolic changes in cysteine homeostasis and propose novel therapeutic interventions to circumvent those pathological changes.
C iv EMISSION-LINE DETECTION OF THE SUPERNOVA REMNANT RCW 114

We report the detection of the C iv λλ1548,1551 emission line in the region of the RCW 114 nebula using the FIMS/SPEAR data. The observed C iv line intensity indicates that RCW 114 is much closer to us than WR 90, a Wolf–Rayet star that was thought to be associated with RCW 114 in some of the previous studies. We also found the existence of a small H i bubble centered on WR 90, with a different local standard of rest velocity range from that of the large H i bubble which was identified previously as related to RCW 114. These findings imply that the RCW 114 nebula is likely an old supernova remnant that is not associated with WR 90. Additionally, the global morphologies of the C iv, Hα, and H i emissions show that RCW 114 has evolved in a non-uniform interstellar medium.
Research features between Urology and Nephrology authors in articles regarding UTI related to CKD, HD, PD, and renal transplantation

Background: A urinary tract infection (UTI) is one of the most common types of infections affecting the urinary tract. When bacteria enter the bladder or kidney and multiply in the urine, a URI can occur. The urethra is shorter in women than in men, which makes it easier for bacteria to reach the bladder or kidneys and cause infection. A comparison of the research differences between Urology and Nephrology (UN) authors regarding UTI pertaining to the 4 areas (i.e., Chronic Kidney Disease, Hemodialysis, Peritoneal Dialysis, and Renal Transplantation [CHPR]) is thus necessary. We propose and verify 2 hypotheses: CHPR-related articles on UTI have equal journal impact factors (JIFs) in research achievements (RAs) and UN authors have similar research features (RFs). Methods: Based on keywords associated with UTI and CHPR in titles, subject areas, and abstracts since 2013, we obtained 1284 abstracts and their associated metadata (e.g., citations, authors, research institutes, departments, countries of origin) from the Web of Science core collection. There were 1030 corresponding and first (co-first) authors with hT-JIF-indices (i.e., JIF was computed using hT-index rather than citations as usual). The following 5 visualizations were used to present the author’s RA: radar, Sankey, time-to-event, impact beam plot, and choropleth map. The forest plot was used to distinguish RFs by observing the proportional counts of keyword plus in Web of Science core collection between UN authors. Results: It was observed that CHPR-related articles had unequal JIFs (χ2 = 13.08, P = .004, df = 3, n = 1030) and UN departments had different RFs (Q = 53.24, df = 29, P = .004). In terms of countries, institutes, departments, and authors, the United States (hT-JIF = 38.30), Mayo Clinic (12.9), Nephrology (19.14), and Diana Karpman (10.34) from Sweden had the highest hT-JIF index. Conclusion: With the aid of visualizations, the hT-JIF-index and keyword plus were demonstrated to assess RAs and distinguish RFs between UN authors. A replication of this study under other topics and in other disciplines is recommended in the future, rather than limiting it to UN authors only, as we did in this study.
PD-1 and CTLA-4 inhibitors in combination vs. alone for the treatment of advanced melanoma: A systematic review and meta-analysis

Background: Metastatic melanoma treatment has drastically changed during the past decade with the advent of immunotherapy. We conducted a meta-analysis, to assess PD-1 and CTLA-4 inhibitors in combination vs. alone for the treatment of advanced melanoma. Methods: The EMBASE, Medline via PubMed, Scopus, Cochrane Central, and Web of Science databases were searched. The records retrieved were screened for eligibility. Odds ratio (OR) was applied to compare dichotomous variables. All the results were reported with 95% confidence intervals (CI). Mantel–Haenszel method was used to estimate pooled OR and 95% confidence intervals for dichotomous data. Results: We retrieved 3092 citations of which we included 3 randomized controlled trials and 2 retrospective, cohort studies. The pooled OR was 2.144 (95% CI: 1.650–2.786, I2 = 80.38% P = .000) for overall response and 2.117 (95% CI: 1.578–2.841, I2 = 70.17% P = .000) for the complete response (CR). Subgroup analysis in nivolumab category showed that the pooled OR was 1.766 (95% CI: 1.324–2.355, I2 = 0.0% P = .000) for the overall response and was 1.284 (95% CI: 0.889–1.855, I2 = 0.0% P = .182) for the CR and in the ipilimumab category the pooled OR was 5.440 (95% CI: 2.896–10.220, I2 = 70.89% P = .001) for the overall response and was 5.169 (95% CI: 3.163–8.446, I2 = 0.0% P = .000) for the CR. The incidence of any treatment-related adverse events was significantly higher in the combination group than that of the nivolumab monotherapy 4.044 (95% CI: 1.740–9.403, I2 = 91.64% P = .001) or the ipilimumab monotherapy 2.465 (95% CI: 0.839–7.236, I2 = 93.02 % P = .101). Conclusion: Combination therapy with ipilimumab plus nivolumab is a promising strategy in the treatment of patients with advanced melanoma with superior overall and complete responses over either monotherapies.
Comparative efficacy and safety of pharmacological interventions for severe COVID-19 patients: An updated network meta-analysis of 48 randomized controlled trials

Background: To date, there has been little agreement on what drug is the "best" drug for treating severe COVID-19 patients. This study aimed to assess the efficacy and safety of different medications available at present for severe COVID-19. Methods: We searched databases for randomized controlled trials (RCTs) published up to February 28, 2022, with no language restrictions, of medications recommended for patients (aged 16 years or older) with severe COVID-19 infection. We extracted data on trials and patient characteristics, and the following primary outcomes: all-cause mortality (ACM), and treatment-emergent adverse events (TEAEs). Results: We identified 4021 abstracts and of these included 48 RCTs comprising 9147 participants through database searches and other sources. For decrease in ACM, we found that ivermectin/doxycycline, C-IVIG (i.e., a hyperimmune anti-COVID-19 intravenous immunoglobulin), methylprednisolone, interferon-beta/standard-of-care (SOC), interferon-beta-1b, convalescent plasma, remdesivir, lopinavir/ritonavir, immunoglobulin gamma, high dosage sarilumab (HS), auxora, and imatinib were effective when compared with placebo or SOC group. We found that colchicine and interferon-beta/SOC were only associated with the TEAEs of severe COVID-19 patients. Conclusion: This study suggested that ivermectin/doxycycline, C-IVIG, methylprednisolone, interferon-beta/SOC, interferon-beta-1b, convalescent plasma (CP), remdesivir, lopinavir/ritonavir, immunoglobulin gamma, HS, auxora, and imatinib were efficacious for treating severe COVID-19 patients. We found that most medications were safe in treating severe COVID-19. More large-scale RCTs are still needed to confirm the results of this study.