Miracle-dz/UniFAR-FTUs huggingface dataset:
Selective brain cooling achieves peripheral organs protection in hemorrhagic shock resuscitation via preserving the integrity of the brain-gut axis

Background: Although whole-body cooling has been reported to improve the ischemic/reperfusion injury in hemorrhagic shock (HS) resuscitation, it is limited by its adverse reactions following therapeutic hypothermia. HS affects the experimental and clinical bowel disorders via activation of the brain-gut axis. It is unknown whether selective brain cooling achieves beneficial effects in HS resuscitation via preserving the integrity of the brain-gut axis. Methods: Male Sprague-Dawley rats were bled to hypovolemic HS and resuscitated with blood transfusion followed by retrograde jugular vein flush (RJVF) with 4 °C or 36 °C normal saline. The mean arterial blood pressure, cerebral blood flow, and brain and core temperature were measured. The integrity of intestinal tight junction proteins and permeability, blood pro-inflammatory cytokines, and multiple organs damage score were determined. Results: Following blood transfusion resuscitation, HS rats displayed gut barrier disruption, increased blood levels of pro-inflammatory cytokines, and peripheral vital organ injuries. Intrajugular-based infusion cooled the brain robustly with a minimal effect on body temperature. This brain cooling significantly reduced the HS resuscitation-induced gut disruption, systemic inflammation, and peripheral vital organ injuries in rats. Conclusion: Resuscitation with selective brain cooling achieves peripheral vital organs protection in hemorrhagic shock resuscitation via preserving the integrity of the brain-gut axis.
An inside vs. outside classification system for Wi-Fi IoT devices

We are entering an era in which Smart Devices are increasingly integrated into our daily lives. Everyday objects are gaining computational power to interact with their environments and communicate with each other and the world via the Internet. While the integration of such devices offers many potential benefits to their users, it also gives rise to a unique set of challenges. One of those challenges is to detect whether a device belongs to one’s own ecosystem, or to a neighbor – or represents an unexpected adversary. An important part of determining whether a device is friend or adversary is to detect whether a device’s location is within the physical boundaries of one’s space (e.g. office, classroom, home). In this thesis we propose a system that is able to decide with 82% accuracy whether the location of an IoT device is inside or outside of a defined space based on a small number of transmitted WiFi frames. The classification is achieved by leveraging a machine-learning classifier trained and tested on RSSI data of Wi-Fi transmissions recorded by three or more observers. In an initialization phase the classifier is trained by the user on Wi-Fi transmissions of a variety of locations, inside (and outside). The system can be built with off-the-shelf Wi-Fi observing devices that do not require any special hardware modifications. With the exception of the training period, the system can accurately classify the indoor/outdoor state of target devices without any cooperation from the user or from the target devices.
Establishment of Rainfall Intensity-Duration-Frequency Equations and Curves Used to Design an Appropriate and Sustainable Hydraulic Structure for Controlling Flood in Nyabugogo Catchment-Rwanda

Due to the increase in the emission of greenhouse gases, the hydrologic cycle is being altered on the daily basis. This has affected the variations in relations of intensity, duration, and frequency of rainfall events. Intensity Duration Frequency (IDF) curves describe the relationship between rainfall intensity, rainfall duration and return period. IDF curves are one of the most often applied implements in water resource engineering, in areas such as for operating, planning and designing of water resource projects, or for numerous engineering projects aimed at controlling floods. In particular, IDF curves for precipitation answer problems of improper drainage systems or conditions and extreme characters of precipitation which are the main cause of floods in Nyabugogo catchment. This study aims to establish Rainfall IDF empirical equations, curves and hydrological discharge (predicted peak rate of runoff (Qlogy)) equations for eight Districts that will be used for designing an appropriate and sustainable hydraulic structures for controlling flood to reduce potential loss of human and aquatic life, degradation of water, air and soil quality and property damage and economic lessen caused by flood in Nyabugogo catchment. However Goodness of Fit tests revealed that Gumbel’s Extreme-Value Distribution method appears to have the most appropriate fit compared with Pearson type III distribution for validating the Intensity-Duration-Frequency curves and equations through the use of daily annual for each meteorological station. The findings of the study show that the intensity of rainfall increases with a decrease in rainfall duration. Additionally, a rainfall of every known duration will have a higher intensity if its return period is high, while the predicted peak rate of runoff (Qlogy) increases also with an increase in the intensity of rainfall.
Beneﬁts of Assistance over Reward Learning

Much recent work has focused on how an agent can learn what to do from human feedback, leading to two major paradigms. The ﬁrst paradigm is reward learning , in which the agent learns a reward model through human feedback that is provided externally from the environment. The second is assistance , in which the human is modeled as a part of the environment, and the true reward function is modeled as a latent variable in the environment that the agent may make inferences about. The key difference between the two paradigms is that in the reward learning paradigm, by construction there is a separation between reward learning and control using the learned reward. In contrast, in assistance these functions are performed as needed by a single policy. By merging reward learning and control, assistive agents can reason about the impact of control actions on reward learning, leading to several advantages over agents based on reward learning. We illustrate these advantages in simple environments by showing desirable qualitative behaviors of assistive agents that cannot be found by agents based on reward learning.
ACCUMULATION OF HEAVY METALS PB, CU, AND ZN IN THE MANGROVE FOREST OF MUARA ANGKE, NORTH JAKARTA

In this study, the concentrations of three kinds of heavy metals, namely Pb, Zn, and Cu from 3 species of mangrove that grow in Muara Angke were measured and analyzed. Our result showed that substrate of mangrove ecosystem in Muara Angke was dominated by clay (30.5% - 62.4%), silt (21.7% -35.6%), and sand (2% -39.5%). The heavy metals accumulation in roots is higher than in sediment, water and leaves with concentration of Zn as the highest. Bioconcentration Factor (BCF; content ratio of heavy metal concentrations in roots or leaves and sediment) and Translocation Factor (TF; ratio of heavy metal concentrations in leaves and roots) of non-essential heavy metals (Pb) is higher in leaves than in roots, but for essential heavy metals (Zn and Cu), the BCF and TF was higher in roots than in leaves. TF values for heavy metals Pb, Cu, and Zn were 0.98-2.59, 0.17-0.51, and 0.52-0.86, respectively. The values of root BCF of those three heavy metals were 0.71-3.17, 0.27-0.74, and 0.95-1.53, while the values of leaf BCF were 1.84-3.45, 0.07-0.34, and 0.72-1.19, respectively. Furthermore, by calculating the phytoremediation (FTD), i.e. the difference between BCF and TF, it is obtained that Sonneratia caseolaris and Avicennia marina can be used in phytoremidiation, with leaves and roots FTD of 1.93 and 2.09, respectively for Sonneratia caseolaris and 1.93 and 1.98 for Avicennia marina. Keywords: heavy metals, mangroves, phytoremidiation, Muara Angke, bioconcentration factor, translocation factor
Measurement Invariance in the CESD-8 and Assessment of Mood Correlates Between American and Mexican Community Studies on the Multisystemic Geriatric Depression Cycle

7 Introduction . 8 Measurement Invariance . 8 Method . 12 Results . 17 Discussion . 20 CHAPTER 3: STUDY TWO . 25 Abstract . 25. 25 Introduction . 26 Loneliness and Social Isolation . 26 Physical Activity and Psychomotor Functioning . 27 Theoretical Synthesis . 29
Antiviral effect of honey extract Camelyn against SARS-CoV-2

This study aimed to evaluate the potential antiviral effects of honey extract “Camelyn” against Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). The baby hamster kidney cell line 21 (BHK‐21), bone marrow-derived hematopoietic stem cells (HSCs), and splenic cells were used for Camelyn cytotoxicity assay. After the isolation procedures, cell viability was assessed by trypan blue dye exclusion under a microscope using a hemocytometer. The in vitro cell growth rate was carried out using the cell counting Kit 8 (CCK-8) assay. The cells were seeded in growth media with various Camelyn concentrations (35 μg, 50 μg, 70 μg, 100 μg, 150 μg, and 200 μg). The absorbance at 450 nm was determined by the multiplate reader. The antiviral effect was assessed by plaque reduction assay for the determination of drug susceptibility against SARS-CoV-2. Serial dilution of the selected compounds was pre-incubated with 40 to 100 plaque-forming units (PFUs) of SARS-CoV-2. The pre-incubated mix of Camelyn and SARS-CoV-2 was then added to the confluent Vero E6 cells after incubation cells were fixed and stained and the number of PFUs was counted under an inverted microscope and plotted against the logarithm of antiviral concentrations. Our study showed that Camelyn is not cytotoxic, has a stimulatory effect on cell proliferation, and has an inhibitory effect against SARS-CoV-2 with EC50 (half-maximal effective concentration) from 85.7 μg/mL to 192.4 μg/mL depending on product concentration and viral plaque per cell. © 2021 Global Research Online. All rights reserved.
Prevalence and risk assessment of coccidiosis in dairy animals of transitional plain in luni basin of Rajasthan

The overall prevalence of coccidiosis of dairy animals was 28.00% (native; 35.71%, crossbred; 25.00% and buffaloes; 22.58%) with a highly significant difference (p<0.01). Among Eimeria species, Eimeria bovis showed highest prevalence (25.39%), followed by E. ellipsoidalis (17.23%), E. pellita (13.20%), E. subspherica (12.75%), E. auburnensis (11.00%), E. zuernii (9.01%), E. cylindrica (6.66%) and E. bukidonensis (4.79%). Among seasons, the prevalence was significantly higher (p<0.01) in winter (37.50%) followed by summer (27.48) and rainy (20.56%) seasons. The district wise analysis revealed significantly higher (p<0.05) prevalence of coccidiosis in Pali district (35.86%) followed by Sirohi (30.00%), Jalore (24.43%) and Jodhpur (22.72%) districts. Quantitative analysis of positive faecal samples for Eimeria sp. revealed a range between 800-3700, 500-3100 and 500-2600 with an average of (2340±201.1), (2050±275.37) and (1740±232.47), among native cattle, crossbred cattle and buffaloes, respectively.
Fruit performances of the selected fig types in Turkey

In this study, fruit performances of some types of fig (Ficus carica L.) were determined in Dara and Yardere villages of Mardin, Turkey. Seven fig types were evaluated in the study for two years. A lot of pomological characteristics to determine the fruit performances of the these types were examined during the 2004 and 2005. According to the averages in two years, fruit weight ranged between 56.29 and 30.88 g, fruit length ranged from 41.80 to 31.97 mm, ostiolum width ranged between 3.90 and 2.44 mm, total soluble solids content (TSS) ranged between 23.40 and 18.25% and acidity ranged between 0.29 and 0.14%. 47-00-4, 47-00-6 and 47-00-7 types scored the highest in overall quality according to the results of the weighted ranked method.
Non-Alcoholic Fatty Liver Disease is Associated with
an Increased Mortality in Adult Patients with Group B Streptococcus Invasive Disease

Background: Group B Streptococcus (GBS) is a significant cause of invasive disease among adult non-pregnant patients with increasing incidence and mortality rates. Although non-alcoholic fatty liver disease (NAFLD) is associated with components of metabolic syndrome previously recognized as risk factors for GBS, the impact of NAFLD on GBS course and outcomes is unknown. Methods: We conducted a retrospective cohort study of all non-pregnant adult patients diagnosed with invasive GBS infection during a 15-year period. Results: 102 patients were included in the study (46.1% males; median age 69, IQR 58-78 years). Disease primarily presented as bacteremia without a defined source (37; 36.3%), cellulitis/erysipelas (35; 34.3%), pneumonia (13; 12.7%) and endocarditis (8; 7.8%). The most common comorbidities were diabetes (42; 41.2%), dyslipidemia (39; 38.2%), cardiovascular disease (34; 33.3%), peripheral vascular disease (21; 20.6%), obesity (21; 20.6%) and malignancy (10; 9.8%). Based upon the results of abdominal ultrasound, the patients were divided into two groups: the ones with steatosis (44; 43.1%) and the ones without steatosis (58; 56.9%). There were no significant differences in clinical presentations and comorbidities between groups. In-hospital mortality was 29.5% (13/44) in patients with NAFLD and 10.3% (6/58) in the control group (p=0.0200). Endocarditis (OR 6.69; 95%CI 1.045-44.46, p=0.0410), acute renal failure (OR 13.92; 95%CI 3.00-77.71, p=0.0013), qSOFA > 2 (OR 23.93; 95%CI 4.66-171.2) and NAFLD (OR 6.64; 95%CI 1.23-47.88, p=0.0258) were independently associated with in-hospital mortality. Conclusions: NAFLD is associated with higher mortality in patients suffering from invasive GBS disease which appears to be independent of other components of the metabolic syndrome, such as obesity and diabetes mellitus.
EFL Teachers' Feedback to Oral Errors in EFL Classroom: Teachers' Perspectives

The current paper aims at identifying how EFL learners perceive teachers' feedback when committing oral mistakes. For this purpose, a short questionnaire, having tested its validity and reliability, was designed and distributed among a sample of 103 EFL teachers. The results showed that (a) the receptive-transmission approach was the most adopted approach in the feedback process, then the constructive followed by the co-constructive approaches; (b) the clarification request was the most feedback way used by the EFL teachers while the metalinguistic way was the least one used; and the correlation coefficients were high between feedback approached and feedback ways in light of superficial vs. deep feedback. The study concluded with some relevant recommendations.
Application of Pre-fabricated Concrete Elements (PCE) in Construction Projects in Iran

In recent decades, construction waste has become a serious environmental problem in many large cities around the globe. The construction sector in Tehran/Iran produced 50,000 tonnes of waste each day in 2010. Furthermore the growing young population, changing lifestyles and rising demand for housing increases the construction material consumption, hence generating more waste. Two main materials are used to construct buildings in Iran: steel and concrete. Various studies have exposed that use of PCE significantly decrease in the amount of waste production. This study aims to explore advantages, barriers, and potential improvement activities on PCE in Iran based on interviews and a questionnaire survey. Moreover, the three methods of concrete construction that are used in the Iranian, namely in-situ concrete, ready-mixed concrete and PCE have been examined. A case study in Tehran was used to illustrate the concrete waste generation and financial issues of these three concrete work methods. The results of questionnaires illustrate that the main advantages of applying PCE in Iran areon-site concrete waste reduction; improve environmental performance; and shorten project time. Moreover, the most significant hindrances are higher project costs; lack of legislation and regulations; limited manufacturers; and limited products. The findingsof the case study indicate that use of PCE has the most cost and the least on-site concrete waste than the other two methods. Finally, the most mentioned recommendation for improving use of PCE in Iran were governmental incentives for using PCE; and education and training.
Artificial Intelligence and Machine Learning in Chronic Airway Diseases: Focus on Asthma and Chronic Obstructive Pulmonary Disease

Chronic airway diseases are characterized by airway inflammation, obstruction, and remodeling and show high prevalence, especially in developing countries. Among them, asthma and chronic obstructive pulmonary disease (COPD) show the highest morbidity and socioeconomic burden worldwide. Although there are extensive guidelines for the prevention, early diagnosis, and rational treatment of these lifelong diseases, their value in precision medicine is very limited. Artificial intelligence (AI) and machine learning (ML) techniques have emerged as effective methods for mining and integrating large-scale, heterogeneous medical data for clinical practice, and several AI and ML methods have recently been applied to asthma and COPD. However, very few methods have significantly contributed to clinical practice. Here, we review four aspects of AI and ML implementation in asthma and COPD to summarize existing knowledge and indicate future steps required for the safe and effective application of AI and ML tools by clinicians.
CryoGuard: A Near Refresh-Free Robust DRAM Design for Cryogenic Computing

Cryogenic computing, which runs a computer device at an extremely low temperature, is highly promising thanks to the significant reduction of the wire latency and leakage current. A recently proposed cryogenic DRAM design achieved the promising performance improvement, but it also reveals that it must reduce the DRAM’s dynamic power to overcome the huge cooling cost at 77 K. Therefore, researchers now target to reduce the cryogenic DRAM’s refresh power by utilizing its significantly increased retention time driven by the reduced leakage current. To achieve the goal, however, architects should first answer many fundamental questions regarding the reliability and then design a refresh-free, but still robust cryogenic DRAM by utilizing the analysis result.In this work, we propose a near refresh-free, but robust cryogenic DRAM (NRFC-DRAM), which can almost eliminate its refresh overhead while ensuring reliable operations at 77 K. For the purpose, we first evaluate various DRAM samples of multiple vendors by conducting a thorough analysis to accurately estimate the cryogenic DRAM’s retention time and reliability. Our analysis identifies a new critical challenge such that reducing DRAM’s refresh rate can make the memory highly unreliable because normal memory operations can now appear as row-hammer attacks at 77 K. Therefore, NRFC-DRAM requires a cost-effective, cryogenic-friendly protection mechanism against the new row-hammer-like "faults" at 77 K.To resolve the challenge, we present CryoGuard, our cryogenic-friendly row-hammer protection method to ensure the NRFC-DRAM’s reliable operations at 77 K. With CryoGuard applied, NRFC-DRAM reduces the overall power consumption by 25.9 % even with its cooling cost included, whereas the existing cryogenic DRAM fails to reduce the power consumption.
Origins of Dissociations in the English Past Tense: A Synthetic Brain Imaging Model

Brain imaging studies of English past tense inflection have found dissociations between regular and irregular verbs, but no coherent picture has emerged to explain how these dissociations arise. Here we use synthetic brain imaging on a neural network model to provide a mechanistic account of the origins of such dissociations. The model suggests that dissociations between regional activation patterns in verb inflection emerge in an adult processing system that has been shaped through experience-dependent structural brain development. Although these dissociations appear to be between regular and irregular verbs, they arise in the model from a combination of statistical properties including frequency, relationships to other verbs, and phonological complexity, without a causal role for regularity or semantics. These results are consistent with the notion that all inflections are produced in a single associative mechanism. The model generates predictions about the patterning of active brain regions for different verbs that can be tested in future imaging studies.
The thermo-mechanical state of the Andes in the Altiplano-Puna region: insights from Curie isotherm and effective elastic thickness determination

We present new constraints on the temperature distribution beneath the Altiplano-Puna plateau region and a new model of effective elastic thickness for the Central Andes. The aim of this study is to better assess the thermal state of the plateau and surrounding regions and analyze its influence on the elastic thickness and strength of the lithosphere. We performed a statistical analysis of the magnetic anomaly in frequency domain in order to obtain the depth to the bottom of the magnetic layer, interpreted as the Curie isotherm. The effective elastic thickness was calculated from the flexure analysis in frequency domain of the deflection of the crust and the pseudo-topography (an artificial construction that allows accounting for the internal loads). We find that the Puna and the volcanic arc present the shallowest Curie isotherm and highest heat-flow in agreement with conductivity, velocity and attenuation anomalies suggesting the presence of partial melts within the crust. In addition, the Altiplano exhibits a deeper Curie isotherm in coincidence with other observations pointing to a stronger lithosphere than in the Puna. Our results show that the effective elastic thickness correlates only partially with the thermal state and that, consequently, other processes, such as inheritance of the elastic thickness, need to be considered to explain the observations and avoid misinterpretations in the variability of the thermal field.
Production and Optimization of Eco-Friendly Composite from KClO3 Treated Date Fiber Reinforced HDPE (high density polyethylene)

In the study, the untreated and potassium chlorate, (KClO3) treated micro sized Date Palm Petiole Fiber, (DPPF) were used to produce natural fiber/HDPE composites by injection molding machine. DPPF was characterized to determine their chemical compositions in terms of cellulose, hemicellulose and lignin. Central Composite Design (CCD) tool of RSM was applied for optimization processes. Analyses of the results showed that cellulose content is, hemicelluloses and lignin. Chemical treatment of the fibers modified and enhanced properties of the fibers. Quadratic model described the relationship between percentage cellulose yield and considered factors of chemical concentration, mass/volume ratio and time. From the three process variables considered, percentage cellulose is 60.3% at 3.5wt% concentration, 4g/l mass/volume ratio and time of 16hr. Quadratic model also described the relationship between tensile strength and process variables of temperature, fiber/polymer ratio and time. The composites produced gave tensile strength 42.0 Mpa fiber/polymer ratio 29wt%, temperature 172c and time 10min. The chemical treatment gave a better interfacial bonding of the DPPF/HDPE and resulted to increased properties of the composite.