Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Designated Eye Care Protocol on Prevention of Ocular Surface Disorders among Patients in Intensive Care Unit

Ocular surface disorders (OSD) are frequently encountered in critically ill unconscious patients due to the loss of normal ocular protective mechanisms. in addition to the drawback effect of mechanical ventilation & the use of sedations which leads to decrease tear production and increase evaporation due to eye lid opening, may progress to microbial keratitis and vision defect. Unfortunately, this common problem is underappreciated by ICU clinicians, who usually focused on the management of organ failures, and eye care becomes a side issue. Eye care guidelines and protocols have been developed for increasing eye care implementation in intensive care units. However, the guidelines lack consistency in assessment or intervention methodology. The study aim was to examine the effect of designated eye care protocol on prevention of ocular surface diseases (OSD) among intensive care units (ICU) patient. Methods: To achieve this aim A quasi experimental/interrupted timeseries design with nonequivalent group design was utilized to guide and achieve the aim of the current research. Study results of this study revealed that there were high statistical significance differences between pre eye care protocol application and post protocol application among study group regarding OSD sub items as eye discharges, eye lid position, presence of conjunctival edema and corneal changes (P<0.001). The study concluded that, regular screening by ICU staff, protocolised care is necessary to prevent the OSD and subsequent complications and prompt ophthalmic referral can significantly decrease the ocular morbidity and improve the quality of life following discharge. The study recommended; establishing a written update protocol of eye care for ventilated & sedated patients in CCU to ensure providing complete and professional care for patients; it’s also recommended to implement the current study on the other hospitals in Egypt.
Evaluation of Some Rice (Oryza sativa L.) Genotypes for Drought Tolerance

Rice (Oryza sativa L.) is one of the most dominant cereal food crops worldwide. It is estimated that about 50% of the world rice is affected by drought (Bouman et al., 2005). Drought is the most crucial and major abiotic stress limitation for rice production Drought International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 10 Number 02 (2021) Journal homepage: http://www.ijcmas. com
Tabs.do: Task-Centric Browser Tab Management

Despite the increasing complexity and scale of people’s online activities, browser interfaces have stayed largely the same since tabs were introduced in major browsers nearly 20 years ago. The gap between simple tab-based browser interfaces and the complexity of users’ tasks can lead to serious adverse effects – commonly referred to as “tab overload. ” This paper introduces a Chrome extension called Tabs.do, which explores bringing a task-centric approach to the browser, helping users to group their tabs into tasks and then organize, prioritize, and switch between those tasks fluidly. To lower the cost of importing, Tabs.do uses machine learning to make intelligent suggestions for grouping users’ open tabs into task bundles by exploiting behavioral and semantic features. We conducted a field deployment study where participants used Tabs.do with their real-life tasks in the wild, and showed that Tabs.do can decrease tab clutter, enabled users to create rich task structures with lightweight interactions, and allowed participants to context-switch among tasks more efficiently.
Laplace Approximation for Uncertainty Estimation of Deep Neural Networks

Deep learning is at the frontier of machine learning and automation, using deep neural networks as the main workhorse, which have revolutionized the way we extract information from large amounts of data in computer vision, natural language processing and other domains. Moving from purely academic to real world scenarios has renewed interest into the way those powerful algorithms draw their conclusions and how to quantify the quality of their predictions beyond mere accuracy. From a practitioner’s point of view, the most important information to obtain alongside the algorithm’s prediction is the uncertainty attached to it, which is the basis for an accurate assessment of confidence. Unfortunately, extracting this information from large models and datasets has proven to be difficult. A common approach so far has been to devise a method that makes as many approximations as necessary to render the problem tractable while still yielding at least somewhat useful uncertainty estimates. This work looks at the problem from a slightly different angle: By first choosing a tractable and comparatively simple method, the burden then lies on the model design to lend itself to the chosen approximation. To this end, the most popular deep neural network architectures are compared based on their compliance to uncertainty estimation by Laplace approximation, assessing empirically the methods potentials and deficiencies as well as its applicability to large models and datasets while working towards an understanding how architectural choices correlate with the quality of obtained uncertainty estimates.
Factors affecting bioleaching of metal contaminated sediment with sulfur-oxidizing bacteria

Bioleaching is one of the feasible methods for the treatment of sediments contaminated with heavy metals. Effects of solid content, substrate (sulfur) concentration and pH on the performance of bioleaching process were investigated in this study. It was found that rates of sediment acidification and metal solubilization decreased with increasing solid content. Besides, sulfur concentration greater than 5 g/l was found to be inhibitory to bacterial activity and metal solubilization from sediment. It was concluded that a substrate concentration of 5 g/l in reactor was the optimum concentration for bioleaching process. It was also observed that solubilization of heavy metal from the sediment was highly pH-dependent. For all values of solid content and sulfur concentration tested, the efficiency of metal solubilization from sediment followed the order Cu>Zn>Pb>Cr.
The emulsifying properties of Persian gum (Amygdalus scoparia Spach) as compared with gum Arabic

ABSTRACT The current study compares the emulsifying properties of Persian gum (PG) and gum Arabic (GA) in emulsions. The effects of concentration (0.5–3% w/v PG, 2.5–15% w/v PG), pH (2–7), ionic strength [NaCl, CaCl2 (0–300 mM)], and temperature (40–90°C) were investigated. The surface–volume mean diameter (D32) of the emulsions showed that the minimum values were 9.89 ± 0.68 and 4.52 ± 0.03 µm for emulsions containing 1.5% w/v PG and 15% w/v GA, respectively. In addition, the zeta potential of PG and GA emulsion changed from −23.5 to −39.5 and −30.5 to −46.0 mV, respectively. The interfacial tensions of PG and GA emulsions were varied in the ranges of 34.0–15.0 and 29.0–9.0 mN/m, respectively. Changes in the D32 value of GA emulsions showed were not significantly different (p > 0.05) with respect to the effects of pH, NaCl, CaCl2, and temperature. The NaCl concentration had no significant effect on D32; but its value decreased from 13.11 to 5.70 µm as the CaCl2 concentration increased. The interfacial tension of PG significantly increased with decreasing pH 7–2 and increasing 0–300 mM salts. After heating (25–90°C), the D32 values of PG and GA emulsions changed to 11.04–14.54 and 4.21–4.21 μm, respectively. The results of this study can be useful for the application of PG as an emulsifier in beverage emulsions.
Non-isothermal kinetic analysis of the thermal decomposition of spruce wood in air atmosphere

Ondro T. , Vitázek I. , Húlan T. , Lawson M. , Csáki Š. (2018): Non-isothermal kinetic analysis of the thermal decomposition of spruce wood in air atmosphere. Res. Agr. Eng., 64: 41–46. Thermal decomposition of spruce wood (Picea abies) was studied using the thermogravimetric (TG) analysis in air atmosphere from 30°C to 600°C with the heating rates of 5, 10, 15, 20, 25 and 30°C.min–1. The TG results show that the main decomposition region is in the temperature range of 250–360°C, where a total disintegration of hemicellulose and cellulose with partial lignin decomposition can be observed. The values of apparent activation energy for this process are between 168.6–196.5 kJ·mol–1, 179.8–188.1 kJ·mol–1 and 179.1–187.7 kJ·mol–1 determined by the Friedman, FlynnWall-Ozawa and Kissinger-Akahira-Sunose methods, respectively.
Comparative study of conventional cell and cyclonic microbubble flotation column for upgrading a difficult-to-float Chinese coking coal using statistical evaluation

ABSTRACT Investigations were executed to upgrade a difficult-to-float coking slime (38.40°Contact angle and 40.14% ash content) by conventional flotation cell and cyclonic microbubble flotation column technologies. Firstly, flotation performance of conventional cell considering interactions of collector dosage, pulp density, and frother dosage was estimated by statistical evaluation. The conventional cell results indicated that clean coal with 11.89% ash content was obtained at 53.94% yield and 79.40% combustible recovery. Secondly, the effects of controlling factors (froth depth and circulating pulp pressure) on the flotation performance of cyclonic microbubble flotation column technology (FCMC) were investigated according to the earlier conventional cell studies. The combustible recovery of the clean coal could be further increased to 90.54% at 62.78% yield and 11.67% ash content by using the FCMC. Finally, the flotation performance in the conventional flotation cell and FCMC was compared with that of the release analysis data. It was concluded that, in general, the performance of the conventional flotation cell was poorer, while the flotation performance of the FCMC was better than that of the release analysis data. Therefore, this difficult-to-float coking coal can be concentrated to a qualified product with minimal usage of reagent and low cost by using the cyclonic microbubble flotation column technology.
Effect of Alkaline Types on the Production of Calcium Carbonate Particles from Gypsum Waste for Fixation of CO2 by Mineral Carbonation

ABSTRACT Industrial by-products have been used as an alternative raw material for the long-term storage of CO2 as a mineral carbonate with various polymorphs and properties. For example; desulfurization gypsum (DG) obtained from a power station has great potential due to its high CaO content. This study used a mineral carbonation process to produce CaCO3 particles (PCC) from DG wastes for fixation of CO2 The effects of solid-to-liquid ratio (1:13, 1:9, and 1:7) and hydroxide sources (NaOH, NH4OH) on properties of PCC were determined using XRD, SEM, FTIR, AAS, and wet chemical analyses. Calcite crystals were produced in all cases with the use of NaOH, whereas calcite crystals along with spherical vaterite crystals were observed in the presence of NH4+. This study suggested a good option due to not only fixation of CO2 but also production of PCC with a high purity.
RoBERTaIQ: An Efficient Framework for Automatic Interaction Quality Estimation of Dialogue Systems

Automatically evaluating large scale dialogue systems’ response quality is a challenging task in dialogue research. Existing automated turn-level approaches train supervised models on Interaction Quality (IQ) labels or annotations provided by experts, which is costly and time-sensitive. Moreover, the small quantity of annotated data limits the trained model’s ability to generalize to the long tail and out of domain cases. In this paper, we propose a learning framework that improves the model’s generalizability by leveraging various unsupervised data sources available in large-scale conversational AI systems. We mainly rely on the following three techniques to improve the performance of dialogue evaluation models: First, we propose extending the RoBERTa model to encode multi-turn di-alogues to capture the temporal differences between different turns. Second, we add two additional pretraining processes on top of enhanced multi-turn RoBERTa to take advantage of large quantity of existing historical dialogue data through self-supervised training. Third, we perform fine-tuning on IQ labels in a multi-task learning setup, leveraging domain-specific information from other tasks. We show that the above techniques significantly reduce annotated data requirements. We achieve the same F1 score on IQ prediction task as our baseline with only 5% of IQ training data and further beat the baseline by 5.4% absolute F1 score if we use all of the training data.
Argumentatively Phony? Detecting Misinformation via Argument Mining

As the Internet media grows, fact-checking news articles online becomes increasingly difficult as it requires a vast amount of background knowledge. Recent studies proposed the concept of reason-checking , which focuses on analyzing the argumentative reasoning style of texts to identify low-quality news articles. While argument mining techniques are leveraged in automatic systems analyzing the quality of formally written texts such as essays, both its efficiency on news-editorial texts and its benefit in fake news detection are under-investigated. To this end, we analyze the performance of argument mining algorithms on fake news and explore how argumentation knowledge will help computational systems to identify fake news.
Fermented Shrimp Waste Hydrolysates: Promising Source of Functional Molecules with Antioxidant Properties

ABSTRACT Protein hydrolysates were prepared through fermentation of shrimp waste. The protein-rich liquid hydrolysate was further dried using two methods: oven drying at 70°C and freeze drying. The functional properties and in vitro antioxidant activities of the two hydrolysates were then investigated. Slight modifications in solubility, emulsifying properties, and oil retention capacity were distinguished between the two dried hydrolysates. The antioxidant activities were evaluated at different concentrations, using various in vitro assays. The dried hydrolysates possessed varying degrees of antioxidant activity. In fact, the two hydrolysates exhibited high DPPH radical scavenging activity comparable to the positive control BHA. The oven-dried hydrolysate (ODH) present higher reducing power than the freeze-dried hydrolysate (FDH), while the latter showed much higher ability to prevent bleaching of β-carotene than did ODH but little higher Fe2+-chelating ability. Therefore, fermented hydrolysates from shrimp processing by-products could be used as a promising source of functional molecules with antioxidant properties.
Photoinduced degradation of sulfonamides, kinetic, and structural characterization of transformation products and assessment of environmental toxicity

ABSTRACT This study focuses on the degradation of the sulfonamide antibiotics, sulfadiazine, sulfamethazine, sulfamethoxazole, and sulfathiazole, using ultraviolet irradiation in various conditions. Different pHs were investigated in combination with the addition of hydrogen peroxide and further oxygen removal. High-performance liquid chromatography electrospray ionization ion-trap mass spectrometry was used to identify and elucidate degradation products and to establish concentration–time curves. Previously unknown degradation products could be characterized. Reaction rate constants of all compounds and transformation products were determined. The parent sulfonamides decayed according to first-order kinetics, while the concentrations of the transformation products varied with time according to a subsequent reaction of an intermediate product. Quantum efficiencies were analyzed for mechanistic purposes. As example, sulfamethoxazole was added to effluents from a wastewater treatment plant and irradiated. Phototoxicity and environmental hazard were assessed through quantitative structure-activity relationship computations. In addition, the minimal inhibition concentrations were determined for Pseudomonas fluorescens and Bacillus subtilis. Conclusions for UV-C irradiation as a fourth purification wastewater treatment stage were derived.
Can conservation incentives promote willingness to coexist with large carnivores in the eastern Serengeti ecosystem?

Communities living adjacent to protected areas tend to express more willingness to coexist with large carnivores in their areas when they receive tangible benefits. The aim of this study was to explore people’s willingness to coexist with large carnivores, including lions (Panthera leo), leopards (Panthera pardus), cheetahs (Acinonyx jubatus), spotted hyenas (Crocuta crocuta), African wild dogs (Lycaon pictus) and black-backed jackals (Canis mesomelas schmidti). The authors used a pre-test and posttest approach by implementing a chemoprophylactic program as a conservation incentive among the Maasai and Sonjo tribes living in the eastern Serengeti, Tanzania. Chemoprophylaxis is the prevention of infectious disease by using chemical agents. The pre-test results showed that both tribes had low willingness to coexist with these large carnivores. Of the two tribes, the Sonjo tribe was less willing than the Maasai tribe. Our post-test results indicated an increase in willingness to coexist with large carnivores in their area because the livestock loss due to large carnivore depredation was significantly lower than that caused by diseases in both tribes. Therefore, this study calls for more conservation incentives to local people to promote their willingness to coexist with large carnivores in their areas.
Polarized Raman scattering on single crystals of rare earth orthochromite RCrO3 (R = La, Pr, Nd, and Sm)

We report on polarized Raman scattering on orthorhombic RCrO3 (R = La, Pr, Nd, and Sm) single crystals at room temperature. The analysis of polarized Raman spectra as a function of polarizer and analyzer angles with respect to crystallographic axes allowed to observe in these flux grown crystals phonon modes that were not detected yet. On the basis of both Raman selection rules and lattice dynamics calculations within density functional perturbations theory framework, the observed Ag, B1g, B2g, and B3g phonon modes were unambiguously assigned. Phonon mode wave number evolutions as a function of orthorhombic distortion, related to rare earth ionic radius, were investigated and highlighted a complex behavior for several low wave number modes allowed crossing. For the modes of same symmetry, a mode mixing behavior is observed, and numerical calculations based on two or three coupling systems were performed to fit experimental data and to extract the coupling constants.
Adoption of Chemical Fertilizer Technology and Household Food Security, in Southern Ethiopia, in Case of Soro District in Hadiya Zone

Adoption of chemical fertilizer technologies is a prerequisite for achieving sustainable agricultural development. However, the link between chemical fertilizer technology adoption decision and food security remains poorly understood due to lack of comprehensive measures of food security. Therefore, this study attempts to investigate the factors affecting chemical fertilizer technology adoption decision, intensity of employing and its impact on the food security in Soro district, southern Ethiopia. A cross – sectional field survey was conducted among 382 cereal crop growers in Soro district in 2019 cropping season. Descriptive statistics and econometric methods such as probit regression, Heckman two stage and propensity score matching was developed for the data analysis. The results of probit regression revealed that the technology participant was significantly affected by size of family, education, family labor force, livestock holding, credit service, extension service, information, distance to market, distance to road and non-farm activity. Intensity of the technology significantly influenced by sex, size of family, family labor force, educational, marital status, membership to cooperative, extension service, access to credit and livestock holding. The findings suggest that the role of technology adoption at farm level due to higher yield and income could translate in to reduced poverty. Rural development office, extension office, and another concern body should give an important attention to adoption decision which is base for enhancing yield. Expansion in the level of adoption would consequently improve welfare economy.
New Data, New Doubts: A Comment on Burnside and Dollar's

The Burnside and Dollar (2000, AER) finding that aid raises growth in a good policy environment has had an important influence on policy and academic debates. We conduct a data gathering exercise that updates their data from 1970 -93 to 1970 -97, as well as filling in missing data for the original period 1970 -93. We find that the Burnside and Dollar (2002, AER) finding is not robust to the use of this additional data.
To Buffer or Not To Buffer: IEEE 802.11p/bd Performance Under Different Buffering Strategies

A fundamental paradigm of the Internet of Things (IoT) consists of agents that communicate updates to each other to perform joint actions, e.g., cooperative awareness in transportation systems, swarms of Unmanned Aerial Vehicles (UAVs), fleet of robots, automated assembly lines and logistics. A common feature of update messaging is emphasis on reliable throughput and freshness of collected data. We develop an analytical model that yields accurate predictions of all relevant metrics, both in terms of moments and probability distributions, for the case of one-hop broadcast update messages exchanged by using a CSMA-based wireless network. The model is validated against simulations and then applied to compare two update message scheduling approaches: providing a minimal buffer resource or providing no buffer. Surprisingly, we prove that having no buffer improves Age of Information (AoI) performance as well as message delivery rate, in spite of dropped packets. This is essentially due to much smaller congestion and hence collision probability in the wireless channel. From a system point of view this suggests a simple design of message handling, with no need of buffering and overwriting older messages. From a modeling point of view, the result supports the definition of simpler models that need not keep into account buffer state.