Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy efficient virtual machines placement in cloud datacenters using genetic algorithm and adaptive thresholds

Cloud computing platform provides on-demand IT services to users and advanced the technology. The purpose of virtualization is to improve the utilization of resources and reduce power consumption. Energy consumption is a major issue faced by data centers management. Virtual machine placement is an effective technique used for this purpose. Different algorithms have been proposed for virtual machine placement in cloud environments. These algorithms have considered different parameters. It is obvious that improving one parameter affects other parameters. There is still a need to reduce energy consumption in cloud data centers. Data centers need solutions that reduce energy consumption without affecting other parameters. There is a need to device solutions to effectively utilize cloud resources and reduce energy consumption. In this article, we present an algorithm for Virtual Machines (VMs) placement in cloud computing. The algorithm uses adaptive thresholding to identify over utilized and underutilized hosts to reduce energy consumption and Service Level Agreement (SLA) violations. The algorithm is validated with simulations and comparative results are presented.
Social vulnerability to floods in two coastal megacities: New York City and Mumbai

In this paper we assess differential exposure to flooding in two coastal megacities, New York and Mumbai, both of which suffered major flood-related disasters in the past decade. Specifically, we examine whether the most exposed populations are also the most socially vulnerable. First, we developed Social Vulnerability Indices (SoVIs) for each city with census data. We then overlaid the SoVI scores onto flood extent maps for Hurricane Sandy (New York, October 2012) and the Mumbai flash floods (July 2005), as well as for the evacuation zones for New York, to examine patterns of differential exposure. Our results suggest a degree of differential exposure in New York, especially in the highest flood risk areas, and provide fairly clear evidence for differential exposure in Mumbai. However, differences in the input resolution and confidence in the datasets for Mumbai make the results more uncertain. The paper concludes with a discussion of the policy implications and the data needs for urban spatial vulnerability assessments.
Market segmentation and consumer motivations in protected natural parks: A study from Spain

There has been an increase in the interest of tourists in the environment and enjoying it in recent years. This research aims to: a) Identify the motivational dimensions in the protected natural parks and b) Analyze the different segments in the protected natural parks. The research was conducted in the Posets-Maladeta protected area in Spain. The sample comprises 422 surveys got in situ. Data analysis involved the execution of factor analysis and non-hierarchical K-means segmentation. The findings suggest the presence of nine motivational dimensions in the protected natural park studied: self-development, interpersonal relationships, security measures, establishing personal bonds, escape, ego-defensive function, nature, entertainment, and rewards. In addition, within this protected natural park is confirmed the presence of two distinct segments: one focused on nature and the other encompassing multiple motives. The results contribute management guidelines for natural park managers for the benefit of communities and visitors. Additionally, this work can serve as a valuable addition to the academic literature concerning ecotourism.
Premature Deaths Due To Heat Exposure: The Potential Effects of Neighborhood‐Level Versus City‐Level Acclimatization Within US Cities

Abstract For the population of a given US city, the risk of premature death associated with heat exposure increases as temperatures rise, but risks in hotter cities are generally lower than in cooler cities at equivalent temperatures due to factors such as acclimatization. Those living in especially hot neighborhoods within cities might therefore suffer much more than average if such adaptation is only at the city‐wide level, whereas they might not experience greatly increased risk if adjustment is at the neighborhood level. To compare these possibilities, we use high spatial resolution temperature data to evaluated heat‐related deaths assuming either adjustment at the city‐wide or at the neighborhood scale in 10 large US cities. On average, we find that if inhabitants are adjusted to their local conditions, a neighborhood that was 10°C hotter than a cooler one would experience only about 1.0–1.5 excess heat deaths per year per 100,000 persons. By contrast, if inhabitants are acclimatized to city‐wide temperatures, the hotter neighborhood would experience about 15 excess deaths per year per 100,000 persons. Using idealized analyses, we demonstrate that current city‐wide epidemiological data do not differentiate between these differing adjustments. Given the very large effects of assumptions about neighborhood‐level acclimatization found here, as well as the fact that current literature is conflicting on the spatial scale of acclimatization, more neighborhood‐level epidemiological data are urgently needed to determine the health impacts of variations in heat exposure within urban areas, better constrain projected changes, and inform mitigation efforts.
Fossil fuel combustion and biomass burning sources of global black
carbon

Abstract. We identify sources (fossil fuel versus biomass burning) of black carbon (BC) in the atmosphere and in deposition using a global 3D chemical transport model GEOS-Chem. We validate the simulated sources against carbon isotope measurements of BC around the globe and find that the model reproduces biomass burning contribution (fbb, %) in various regions within a factor of 2. GEOS-Chem shows that contribution from biomass burning in the Northern Hemisphere (fbb: 34 %) is much less than that in the Southern Hemisphere (52 %). Specifically, we find comparable contribution from biomass burning and fossil fuel in South Asia, S. America, S. Pacific, Australia and the Antarctic. fbb is the largest in Africa (64 %), followed by that in East Asia (40 %), Siberia (35 %), the Arctic (33 %), Canada (31 %), the US (25 %), and Europe (19 %). fbb is higher in summer (59–78 %) than in winter (28–32 %) in the Arctic, while it is higher in winter (42–58 %) and lower in summer (16–42 %) over the Himalayan–Tibetan plateau. The seasonal variations of fbb are relatively flat in North America, Europe, and Asia. We find that double biofuel emissions for domestic heating during cold seasons northern than 45° N increases fbb values in the Arctic and Europe in winter by ~ 30 %, resulting in a ~ 20 % reduction of discrepancies of fbb in the two regions. The remaining large negative discrepancies (Europe: 41 %; Arctic: 46 %) suggest that the biofuel emissions are probably still underestimated at high latitudes. Increasing fraction of thickly coated hydrophilic BC from 20 % to 70 % in fresh biomass burning plumes increases the fraction of hydrophilic BC in biomass burning plumes by 0–20 % (vary with seasons and regions), and thereby reduces atmospheric fbb by up to 11 %. Faster aging (4 hour e-folding time versus 1.15 days of e-folding time) of BC in biomass burning plumes reduces atmospheric fbb by 7 % (1–14 %), with the largest reduction in remote regions, such as the Arctic, the Antarctic and S. Pacific. Using size resolved scavenging accelerates scavenging of BC particles in both fossil fuel and biomass burning plumes, with a larger increase of the former. Thus, atmospheric fbb increases in most regions by 1–14 %. Overall, atmospheric fbb is determined by fbb in emissions mainly and by atmospheric processes, such as aging and scavenging, to a less extent.
The epidemiological situation of tuberculosis in Spain according to surveillance and hospitalization data, 2012–2020

Background Before the COVID-19 pandemic, tuberculosis (TB) was the leading cause of death from a single infectious agent. In Spain, TB notifications are registered through the National Epidemiological Surveillance Network (RENAVE). The Minimum Basic Data Set (CMBD) provides information on TB hospital discharges. This study aims to assess both registries to complete the picture of TB in order to improve national control strategies and make further progress toward its elimination. Methods A retrospective study was performed considering CMBD´s hospital discharges with TB as first diagnosis and notifications to RENAVE between 2012 and 2020. After describing the records of both systems and their differences by using descriptive and multivariate analysis, annual incidences rates were calculated in order to evaluate temporal trends and geographical patters. Results According to the CMBD database, there were 29,942 hospitalizations due to TB (65% pulmonary forms and 66% male) during the study period. RENAVE collected 44,520 reported cases, mostly males (62%) with pulmonary forms (72%). Young children were similar in both groups, showing the high frequency of hospitalization in this group. Almost all autonomous communities showed a downward trend, especially Asturias. Hospitalizations in 2020 were analyzed by month separately, and comparing with previous years, the impact of the COVID-19 pandemic can be seen. Conclusions A decreasing trend on TB incidence was observed in Spain since 2012, although this trend might change after COVID-19 pandemic. The analysis of both databases, CMBD and RENAVE, has contributed to improve our knowledge of TB in Spain and will help improve the control of this disease.
Academics’ continuance intention to use learning technologies during COVID-19 and beyond

The COVID-19 pandemic has revolutionized the teaching pedagogy in higher education as universities are forecasted to increase investments in learning technology infrastructure to transition away from traditional teaching methods. Therefore, it is crucial to investigate whether academics intend to continually integrate learning technologies as part of a permanent pedagogical change beyond the COVID-19 pandemic. Drawing upon the Unified Theory of Acceptance and Use of Technology (UTAUT), and Expectation Confirmation Model (ECM), this study examines the salient determinants influencing the continuance intention of academics to use learning technologies in their teaching pedagogy during and after COVID-19. Primary data collected from a private university was analyzed using the partial least squares structural equation modelling technique (PLS-SEM). The findings revealed two sequential mediating relationships which serve as the mechanism linking the relationship between facilitating conditions and their continuance intention to use learning technologies during and beyond the COVID-19 pandemic.
Bioethanol Production Potentials of Corn Cob, Waste Office Paper and Leaf of Thaumatococcus daniellii

Aims: Lignocelluloses-based waste materials are prospective and renewable feedstocks for bioethanol production. Despite their widespread availability, little attention has been paid to their utilization as fermentation feedstocks for bioethanol production especially in developing countries like Nigeria. In this study, three lignocelluloses-based wastes: corn cobs, office paper waste, and Thaumatococcus daniellii leaves, commonly generated in Southwestern Nigeria were evaluated as fermentation feedstocks for bioethanol production. Study Design: The study was a laboratory based experimental study which involved chemical hydrolysis and microbiological fermentation. Place and Duration of Study: Department of Environmental Health Sciences, Faculty of Public Health, University of Ibadan, Ibadan, Nigeria, between July 2014 and December 2014. Methodology: Separate hydrolysis and fermentation method was adopted for the study. Hydrolysis of the feedstocks was carried out at H 2 SO 4 concentration of 6 M, 9 M and 13 M at 100°C for 60 min. Hydrolysates obtained were ferment ed at 30°C for 72 hours using Saccharomyces cerevisiae . Results: Reducing sugar yields in the hydrolysates ranged from 51.5 – 27.3%, with highest yields from all the feedstocks obtained at 9M treatment, suggesting that 9M is the optimal concentration of H 2 SO 4 for hydrolysis of the tested feedstocks. Highest ethanol yields of 20.2, 16.8 and 15.9 g/L were obtained at 48-hour fermentation period from waste office paper, corn cob and leaves of Thaumatococcus daniellii , respectively. Conclusion: The results thus indicate that 48 hours is the optimal fermentation period for the feedstocks using Saccharomyces cerevisiae . The study has demonstrated that ethanol could be produced from the paper, corncobs and leaves of Thaumatococcus daniellii leaves with maximum yield obtained from office paper waste.
System Size Dependence of the Diffusion Coefficients in MD Simulations: A Simple Correction Formula for Pure Dense Fluids.

A practical correction formula relating the self-diffusion coefficient of dense liquids from molecular dynamics (MD) simulations with periodic boundary conditions to the self-diffusion coefficient in the thermodynamic limit is discussed. This formula applies to pure dense fluids and has a very simple form D = D0(1 - γN-1/3), where D0 is the self-diffusion coefficient in the thermodynamic limit and N is the number of particles in the simulation. The numerical factor γ is dependent on the geometry of the simulation cell. Remarkably, γ ≃ 1.0 is the most popular cubic geometry. The success of this formula is supported by results from MD simulations, including very recent simulations with a "magic" simulation geometry.
Trajectory Deformation-Based Multi-Modal Adaptive Compliance Control for a Wearable Lower Limb Rehabilitation Robot

Adaptive compliance control is critical for rehabilitation robots to cope with the varying rehabilitation needs and enhance training safety. This article presents a trajectory deformation-based multi-modal adaptive compliance control strategy (TD-MACCS) for a wearable lower limb rehabilitation robot (WLLRR), which includes a high-level trajectory planner and a low-level position controller. Dynamic motion primitives (DMPs) and a trajectory deformation algorithm (TDA) are integrated into the high-level trajectory planner, generating multi-joint synchronized desired trajectories through physical human-robot interaction (pHRI). In particular, the amplitude modulation factor of DMPs and the deformation factor of TDA are adapted by a multi-modal adaptive regulator, achieving smooth switching of human-dominant mode, robot-dominant mode, and soft-stop mode. Besides, a linear active disturbance rejection controller is designed as the low-level position controller. Four healthy participants and two stroke survivors are recruited to conduct robot-assisted walking experiments using the TD-MACCS. The results show that the TD-MACCS can smoothly switch three control modes while guaranteeing trajectory tracking accuracy. Moreover, we find that appropriately increasing the upper bound of the deformation factor can enhance the average walking speed (AWS) and root mean square of trajectory deviation (RMSTD).
The role of naturally acquired intracellular Pseudomonas aeruginosa in the development of Acanthamoeba keratitis in an animal model

Background Acanthamoeba is an environmental host for various microorganisms. Acanthamoeba is also becoming an increasingly important pathogen as a cause of keratitis. In Acanthamoeba keratitis (AK), coinfections involving pathogenic bacteria have been reported, potentially attributed to the carriage of microbes by Acanthamoeba. This study assessed the presence of intracellular bacteria in Acanthamoeba species recovered from domestic tap water and corneas of two different AK patients and examined the impact of naturally occurring intracellular bacteria within Acanthamoeba on the severity of corneal infections in rats. Methodology/Principal findings Household water and corneal swabs were collected from AK patients. Acanthamoeba strains and genotypes were confirmed by sequencing. Acanthamoeba isolates were assessed for the presence of intracellular bacteria using sequencing, fluorescence in situ hybridization (FISH), and electron microscopy. The viability of the bacteria in Acanthamoeba was assessed by labelling with alkyne–functionalized D–alanine (alkDala). Primary human macrophages were used to compare the intracellular survival and replication of the endosymbiotic Pseudomonas aeruginosa and a wild type strain. Eyes of rats were challenged intrastromally with Acanthamoeba containing or devoid of P. aeruginosa and evaluated for the clinical response. Domestic water and corneal swabs were positive for Acanthamoeba. Both strains belonged to genotype T4F. One of the Acanthamoeba isolates harboured P. aeruginosa which was seen throughout the Acanthamoeba’s cytoplasm. It was metabolically active and could be seen undergoing binary fission. This motile strain was able to replicate in macrophage to a greater degree than strain PAO1 (p<0.05). Inoculation of Acanthamoeba containing the intracellular P. aeruginosa in rats eyes resulted in a severe keratitis with increased neutrophil response. Acanthamoeba alone induced milder keratitis. Conclusions/Significance Our findings indicate the presence of live intracellular bacteria in Acanthamoeba can increase the severity of acute keratitis in vivo. As P. aeruginosa is a common cause of keratitis, this may indicate the potential for these intracellular bacteria in Acanthamoeba to lead to severe polymicrobial keratitis.
Evaluation of the anti-androgenic and cytotoxic effects of benzophenone-3 in male Sprague-Dawley rats

ABSTRACT Benzophenone-3 (BP-3, 2-hydroxy-4-methoxybenzophenone, oxybenzone) is one of the most widely used types of benzophenone organic sunscreen. However, this compound is a potentially harmful toxicant. The aim of this study was 2-fold to: (1) utilize a Hershberger bioassay in vivo in castrated male Sprague-Dawley rats to investigate the anti-androgenic activities of BP-3, and (2) use in vitro a methyl tetrazolium assay to compare the toxicity between Leydig cells (TM3 cells) and mouse fibroblast (NIH-3T3) cell lines. In the Hershberger assay, rats were divided into 6 groups (each of n = 7): a vehicle control, negative control, positive control, PB-3 low (40 mg/kg), BP-3 intermediate (200 mg/kg), and BP-3 high (1000 mg/kg)-dose. The weight of the ventral prostate was significantly decreased at BP-3 doses of 200 or 1,000 mg/kg/day. In addition, the levator anibulbocavernosus muscle weights were also significantly reduced at BP-3 doses of 40, 200, or 1,000 mg/kg/day. In the MTT assay, the viability of NIH-3T3 mouse fibroblast cells was within the normal range. However, the TM3 mouse testis Leydig cell viability was significantly lowered in a concentration-dependent manner. Therefore, data indicate that BP-3 might exert in vivo anti-androgenic and in vitro cytotoxic effects in cells associated with the male reproductive system compared to normal non-reproductive cells. Abbreviation: BP-3: benzophenone-3; CG: Cowper’s gland; DMEM: Dulbecco’s modified Eagle’s medium; DMSO: dimethyl sulfoxide; GP: glans penis; LABC: levator anibulbocavernosus muscle; MTT: methyl tetrazolium; NC: negative control; PC: positive control; SV: seminal vesicle; TP: testosterone propionate; VC: vehicle control; VP: ventral prostate
The Relationship Between Vegetation Growth and the Combination of Water and Heat in the Qilian Mountain

Climatic conditions,mainly heat and water as well as the combination of these two factors,are the fundamental factors that decide the zonal distribution of different vegetation types.Qilian Mountain in the south of Hexi Corridor which locates in China's major climatic transitional zone was schosen as the study area and the remote sensing vegetation indexes were used as the quantitative methods to describe the growth status and spatial distribution of vegetation cover in the region.Besides that,the precipitation and air temperature raster data were also used by means of spatial overlay and multi-factor analysis of GIS.The effect of the combination of water and heat to the status of vegetation cover was revealed.
Automatic Change Detection in Interwoven Sequences: A Visual Mismatch Negativity Study

Abstract In this study, we investigated whether the cognitive system, known to be able to register regular visual event sequences and the violation of these sequences automatically, had the capacity of processing two sequences simultaneously. To this end, we measured the visual mismatch negativity (vMMN) component of ERPs as interwoven event sequences simultaneously presented to the left and right side of the screen. One of the sequences consisted of geometric patterns (diamonds); the other, photographs of human faces. In successive cycles, parts of the stimuli vanished and then re-appeared (the OFF/ON method). The vanishing parts served as either standard (frequently vanishing parts) or infrequent (deviant) events, but these events were task-irrelevant. The 20 adult participants (age 21.40 ± 2.72 years) performed a visual tracking task, with the OFF/ON task being a passive oddball paradigm. According to the results, both OFF and ON events, and both diamond and face stimuli elicited the vMMN component, showing that the system underlying this activity is capable of processing two event sequences if the sequences consist of fairly different kind of objects as stimuli. The sLORETA analysis showed that the source of vMMN was more frequent contralaterally to the deviant event, and the sources comprised loci from ventral and dorsal structures, as well as some anterior loci.
IgG marker of optic-spinal multiple sclerosis binds to the aquaporin-4 water channel

Neuromyelitis optica (NMO) is an inflammatory demyelinating disease that selectively affects optic nerves and spinal cord. It is considered a severe variant of multiple sclerosis (MS), and frequently is misdiagnosed as MS, but prognosis and optimal treatments differ. A serum immunoglobulin G autoantibody (NMO-IgG) serves as a specific marker for NMO. Here we show that NMO-IgG binds selectively to the aquaporin-4 water channel, a component of the dystroglycan protein complex located in astrocytic foot processes at the blood-brain barrier. NMO may represent the first example of a novel class of autoimmune channelopathy.
Entropy-based Probing Beam Selection and Beam Prediction via Deep Learning

Hierarchical beam search in mmWave communications incurs substantial training overhead, necessitating deep learning-enabled beam predictions to effectively leverage channel priors and mitigate this overhead. In this study, we introduce a comprehensive probabilistic model of power distribution in beamspace, and formulate the joint optimization problem of probing beam selection and probabilistic beam prediction as an entropy minimization problem. Then, we propose a greedy scheme to iteratively and alternately solve this problem, where a transformer-based beam predictor is trained to estimate the conditional power distribution based on the probing beams and user location within each iteration, and the trained predictor selects an unmeasured beam that minimizes the entropy of remaining beams. To further reduce the number of interactions and the computational complexity of the iterative scheme, we propose a two-stage probing beam selection scheme. Firstly, probing beams are selected from a location-specific codebook designed by an entropy-based criterion, and predictions are made with corresponding feedback. Secondly, the optimal beam is identified using additional probing beams with the highest predicted power values. Simulation results demonstrate the superiority of the proposed schemes compared to hierarchical beam search and beam prediction with uniform probing beams.