Miracle-dz/UniFAR-FTUs huggingface dataset:
A Review on TAM and TOE Framework Progression and How These Models Integrate

Article history: Received: 08 December, 2020 Accepted: 27 March, 2021 Online: 20 May, 2021 The TAM is a model that is widely used to understand IT adoption and usage process accordingly and the reason for its popularity is that the model clarifies variances like behavioral intention (BI) relevant to IT appropriation and use over a broad range of settings. The model's main factors for system use is perceived usefulness (PU) and perceived ease of use (PEOU). Likewise, the T-O-E framework is a popular framework for three stimuli that influence organizational adoption namely technology, organization, and environment. Much literature has dealt with the use of TAM and T-O-E frameworks together with their derivatives without looking at the shortfall of these models. This paper reviewed one hundred and seventeen papers that used or reviewed TAM or TOE models. The contribution of this paper is the address of the usefulness, limitations, and criticism of the two models and also how the TAM and the T-O-E frameworks can be integrated into a hybrid model using a generic framework. In conclusion these models can be used separately or as a hybrid depending on the situation at hand. In future it important to harmonize the so many factors of the models that have been suggested and used in literature.
New Strategy for Solubilization of poorly soluble drug- SEDDS

Self-emulsifying drug delivery systems (SEDDSs) have gained exposure for their ability to increase solubility and bioavailability of poorly soluble drugs. Self-emulsifying drug delivery systems (SEDDS) are mixtures of oils, surfactants, and cosurfactants, which are emulsified in aqueous media under conditions of gentle stirring and digestive motility that would be encountered in the gastrointestinal tract. We found that SEDDS could efficiently improve oral absorption of the sparingly soluble drugs by rapid self-emulsification and subsequently dispersion in the absorption sites.
A Trans-Disciplinary Vocabulary for Assessing the Visual Performance of BIPV

It is widely acknowledged that the visual dimension of photovoltaics (PV) is fundamental for social acceptance. In this sense, the so-called Building Integrated Photovoltaics (BIPV) is a possible catalyzer, as PV is hidden (integrated) into building envelope morphologies that are familiar to the public. It is crucial to be able to design and assess a BIPV system so that its visual performance is optimal. Many studies exist in this regard, but still they do not deliver a clear theoretical organization of the concepts used for defining the visual performance of BIPV. This paper elaborates a trans-disciplinary systemic formalization of BIPV and proposes a vocabulary focusing on the formal perception of BIPV as a part of the building’s envelope system. The proposed vocabulary is based on a set of 11 visual keywords; as the proposed method unifies the formal and the cognitive information contents. It will facilitate the dialogue among different stakeholders (e.g., architects, clients, modules manufacturers, and public authorities) and, in general, the visual performance assessment of BIPV. In consequence, it allows for objective comparison and thus informed decision-making.
The effect of COVID-19 process on patients with endocrinological disease in a pandemic hospital: What happened to the others?

ABSTRACT Objective: To evaluate the effects of the pandemic process on those with an endocrinological disease that will require close follow-up from the last visit before the pandemic. Materials and methods: Patients of 3,903 with thyroid, calcium-bone metabolism, adrenal gland, pituitary diseases, and neuroendocrine tumor (NET) were retrospectively scanned. The remaining 855 (656 females and 199 males) patients with active disease or who still needed multidisciplinary approaches were included. The number of patients who continued the disease-related medical procedures and could complete these procedures on time in the pandemic period was determined, and medical deprivation rate (MDR) was calculated. Results: The prepandemic period of our patients with thyroid disease (n = 594), calcium-bone metabolism disorder (n = 130), adrenal disease (n = 85), pituitary disease, and NET (n = 46) had MDRs of 85%, 56%, 81%, and 89%, respectively. For each subgroup of patients, the lowest MDR (67%) was in medullary thyroid carcinoma, the highest MDR (89%) was in differentiated thyroid carcinoma; the lowest MDR (6%) was in osteoporosis, the highest MDR (100%) was in the active Paget's disease; the lowest MDR (0%) was in primary adrenocortical insufficiency, the highest MDR (100%) was in hyperfunctional adrenal adenomas; the lowest MDR (81%) was in pituitary nonfunctional adenomas, and the highest MDR (100%) was in Cushing's disease, active prolactinoma, TSHoma, and NET, respectively. Conclusion: This study showed that not only those who had COVID-19 but also those who had medical deprivation due to their current endocrinological disease were not to be underestimated during the pandemic period.
Built-up area expansion in the Wa Municipality of Ghana: implications for vegetation cover loss and fragmentation

ABSTRACT This study draws on the patch-mosaic model and uses geospatial and statistical methods to assess vegetation fragmentation specifically from built-up area expansion between 1990 and 2018 in the Wa Municipality of Ghana. The study finds that 0.19% and 0.33% annual expansion in the built-up area from 1990-2006 and 2006-2018 contributed to annual vegetation patch size variability (coefficient of variation in the patch size) of 1.82% and 120.97% from 1990-2006 and 2006-2018, respectively. Our results suggest that a higher rate of increase in built-up area would likely create larger quantities of intermixed vegetation and built-up patches.
Multitask Model for Person Re-identification by Attribute-aware

The image-based person re-identification problem can be transformed into a similar image retrieval problem. At present, most of the current identity-based methods do not consider pedestrian attributes. Moreover, many methods that consider pedestrian attributes and identities fail to fully simulate the relationship between pedestrian attributes and identities. In this article, we propose a new image-based person re-identification method by attributeaware. Based on the introduction of instance batch normalization, the nonlocal module based on attention is used to transform the ResNet network structure to improve the feature extraction performance. After using generalized mean pooling for feature aggregation, the identity-based and attribute-based double stream network modules pay attention to the relationship between identities and pedetrian features, and the relationship between attributes and pedestrian features, so as to fully activate the relationship between pedestrian attributes and identities. Experiments are carried out on two classic person re-identification by attribute dataset Market-1501 and DukeMTMC-reID, and the results prove the effectiveness of the method. The method proposed in this paper has achieved the best performance on some evaluation metrics.
Enhacement of Microgrid Technologies using Various Algorithms

The electric power systems around the globe are gradually shifting from conventional fossil fuel-based generating units to green renewable energy sources. The motivation behind this change is the environmental and economic concerns. Furthermore, the existing power systems are being overloaded day by day due to the continuously increasing population, which consequently led to the overloading of transformers, transmission, and distribution lines. Despite the overwhelming advantages of renewable energy sources, there are few major issues associated with them. For example, the injection and detachment of DGs into the current power system causes disparity among produced power along with connected load, thus distracting system’s equilibrium and causes unwanted voltage and frequency oscillations and overshoots. These oscillations and overshoots may cause the failure of connected equipment or power system if not properly controlled. The investigation as such challenges to improve the frequency and voltage, the islanded’s power regulation and connected MG under source and load changes, which contain classic and artificial intelligence techniques. Moreover, these techniques are used also for economic analysis. To evaluate the exhibitions of microgrid (MG) operations and sizing economic analysis acts as a significant tool. Optimization method is obligatory for sizing and operating an MG as reasonably as feasible. Diverse optimization advances remain pertained to microgrid to get optimal power flow and management.
Modeling Sediment Yield-Case Study Guder Watershed, Blue Nile Basin, Central Ethiopia

Guder watershed is one of the watershed found in Blue Nile basin, central Ethiopia, mostly eroded area due to the widespread of agricultural land. This study is based on the Soil and Water Assessment Tool (SWAT) model interface of GIS environment to simulate sediment yield of the watershed at outlet. The stream flow was calibrated for ten years (1996-2005) and validated for seven years (2006-2012) at Guder gauging station using SWAT-CUP to check performance of the model. The model performance has been evaluated by using statistical parameters of coefficient of determination (R²) and Nash-Sutcliffe simulation efficiency (NSE) 0.92 and 0.80 respectively for calibration. Model validation results 0.83 and 0.65 for R² and NSE, respectively. Both calibration and validation results indicate that the measured values show good agreement with simulated flow. Sediment yield from each sub watershed were determined and prone soil erosion areas has been identified for management planning.
Population Assessment and Threat Categorization of Endangered Medicinal Orchid Malaxis Acuminata D. Don. from North-West Himalaya

Studies on population assessment and threat categorization in selected populations of Malaxis acuminate D. Don. , a rare, terrestrial, endangered medicinal orchid of Himalayan region and an important “Astverga” plant were undertaken. Status was determined on siteto-site basis as well as for entire Kumaun region. Based on species occurrence in selected areas, the species were identified as critically endangered to endangered in different sites studied. The results also revealed that natural distribution of the species was narrowing down due to habitat destruction and over exploitation. Immediate remedial measures are needed for the conservation of natural sites to ensure sustainable mode of utilization.
A generalized control scheme for system uncertainty estimation and cancellation

This paper addresses the control of a continuous-time system with possibly large uncertainty of unknown internal dynamics or external disturbance. A novel control scheme is proposed to estimate and cancel the system uncertainty effectively so as to enhance disturbance rejection (DR) performance. Unlike asymptotic analysis with infinite gain in the literature, the estimation transient analysis is carried out for the proposed scheme with a finite estimator gain and the precise error formulas are derived, based on a classical low-order plant description. The control performance associated with a realizable gain is quantified by tight bounds with respect to the ideal case, which enables easy parameter tuning. The necessary and sufficient condition for the internal stability of the control system is established, along with a D-decomposition method for determining the complete set of the gain intervals that could internally stabilize the plant. In the presence of measurement noise, a low-pass filter is introduced to attenuate its adverse effect. Simulations and semi-realistic experiments are performed to demonstrate the effectiveness of the proposed scheme, which shows evident improvement on DR performance over the well-known active DR control.
Daily Variation of Lipid Regulators and Personal Care Products in a River Impacted by Domestic Effluents in Southern Brazil

In urban areas, wastewater treatment plants (WWTPs) play a major role in the water quality of rivers. The removal efficiency of emerging contaminants by WWTPs is strongly correlated with the type of treatment and the hydraulic retention time (HRT) of the process, which can vary according to the volumetric influent flow of wastewater and occasional peak flows. This paper aims, for the first time, to assess the daily variation of lipid regulators and personal care products in an urban river impacted by domestic effluents. Samples were collected upstream and downstream of a WWTP. The concentrations downstream of the effluent discharge were higher than upstream, but they varied significantly during the day. Concentration peaks upstream of the WWTP were detected at 07:00, 15:00 and 21:00, while downstream of the effluent discharge, concentration peaks occurred between 13:00 and 19:00 and between 21:00 and 23:00. The highest downstream concentrations of triclosan and methylparaben (420 ng L−1 and 460 ng L−1) were 6.8 and 5.4 times higher than the lowest concentrations detected, respectively. These results show that in WWTP-impacted rivers, the time of the sampling has a great influence on the final results and conclusions of a monitoring study.
Joint Assortment and Inventory Planning for Heavy Tailed Demand

We study a joint assortment and inventory optimization problem faced by an online retailer who needs to decide on both the assortment along with the inventories of a set of N substitutable products before the start of the selling season to maximize the expected profit. The problem raises both algorithmic and modeling challenges. One of the main challenges is to tractably model dynamic stock-out based substitution where a customer may substitute to the most preferred product that is available if their first choice is not offered or stocked-out. We first consider the joint assortment and inventory optimization problem for a Markov Chain choice model and present a near-optimal algorithm for the problem. Our results significantly improve over the results in Gallego and Kim (2020) where the regret can be linear in T (where T is the number of customers) in the worst case. We build upon their approach and give an algorithm with regret O(\sqrt{NT}) with respect to an LP upper bound. Our algorithm achieves a good balance between expected revenue and inventory costs by identifying a subset of products that can pool demand from the universe of substitutable products without significantly cannibalizing the revenue in the presence of dynamic substitution behavior of customers. We also present a multi-step choice model that captures the complex choice process in an online retail setting characterized by a large universe of products and a heavy-tailed distribution of mean demands. Our model captures different steps of the choice process including search, formation of a consideration set and eventual purchase. We conduct computational experiments that show that our algorithm empirically outperforms previous approaches both on synthetic and realistic instances.
Integrating disparate datasets to model the functional response of a marine predator: A case study of harbour porpoises in the southern North Sea

Abstract Quantifying consumption and prey choice for marine predator species is key to understanding their interaction with prey species, fisheries, and the ecosystem as a whole. However, parameterizing a functional response for large predators can be challenging because of the difficulty in obtaining the required data on predator diet and on the availability of multiple prey species. This study modeled a multi‐species functional response (MSFR) to describe the relationship between consumption by harbour porpoises (Phocoena phocoena) and the availability of multiple prey species in the southern North Sea. Bayesian methodology was employed to estimate MSFR parameters and to incorporate uncertainties in diet and prey availability estimates. Prey consumption was estimated from stomach content data from stranded harbour porpoises. Prey availability to harbour porpoises was estimated based on the spatial overlap between prey distributions, estimated from fish survey data, and porpoise foraging range in the days prior to stranding predicted from telemetry data. Results indicated a preference for sandeels in the study area. Prey switching behavior (change in preference dependent on prey abundance) was confirmed by the favored type III functional response model. Variation in the size of the foraging range (estimated area where harbour porpoises could have foraged prior to stranding) did not alter the overall pattern of the results or conclusions. Integrating datasets on prey consumption from strandings, predator foraging distribution using telemetry, and prey availability from fish surveys into the modeling approach provides a methodological framework that may be appropriate for fitting MSFRs for other predators.
Reverse Causality between Fiscal and Current Account Deficits in ASEAN: Evidence from Panel Econometric Analysis

This study aims to explore the causal relationship between fiscal deficit (FD) and current account deficit (CAD) along with policy recommendations based on long-run and short-run dynamics and sensitivities. A panel data span from 1990 to 2019 is analyzed based on panel unit root tests, panel co-integration with auto-regressive distributed lag (ARDL), panel co-integration regression with fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS), and causal analysis with the Dumitrescu and Hurlin (DH) technique. The results disclosed that all tested variables are stationary at the first difference I(1) except the real interest rate (IR), which is stationary at level I(0). The ARDL estimates suggested that there is a long-run relationship between tested variables and 92% annual convergence is possible for long-run equilibrium. The FMOLS and DOLS estimates indicated that the CAD is sensitive towards the FD and the exchange rate. The DH causality test showed that the CAD is significantly affecting the FD, supporting the current account targeting hypothesis. Furthermore, it is observed that the interest rate is acting as a moderating factor between the FD and the CAD because it causes both the deficits. Thus, reverse causality is concluded from the CAD to the FD. These results have macroeconomic implications for fiscal policy in the Association of South-East Asian Nations (ASEAN-10).
Design Considerations of a Nonvolatile Accumulator Based 8-bit Processor

The rise of the Internet of Things (IoT) and the constant growth of portable electronics have leveraged the concern with energy consumption due to the use of batteries in these devices. The nonvolatile memory (NVM) emerged as a solution to mitigate the problem due to its ability to retain data on sleep mode without a power supply. Nonvolatile processors (NVPs), in turn, may further improve energy saving, by making use of nonvolatile flip-flops (NVFFs) that store system state in parallel, allowing the device to be turned off when idle and resume execution instantly after power-on. This work describes the initial steps to implement a nonvolatile version of Neander, a hypothetical processor created for educational purposes. First, we implemented Neander in Register Transfer Level (RTL), separating the combinational logic from the sequential elements. Then, the latter were replaced by transistor-level descriptions ofvolatile flip-flops. We then validated this implementation by employing a mixed-signal simulation over a set of benchmarks. Results shown the expected behavior for the whole instruction set. Then, we implemented MTJ-based non-volatile flip-flops in circuit-level, using an open-source MTJ model. These elements were exhaustive validated using electrical simulations. With these results, we intend to carry on the implementation and fully equip our processor with nonvolatile features such as instant wake up.
Influence of Adjuvants on Foliar Absorption of Nitrogen and Phosphorus by Soybeans

Adjuvants at various concentrations were evaluated for phytotoxicity and capacity to enhance foliar absorption of N and P. Some adjuvants among the following classes were phytotoxic to soybean (Glycine max Merr.) leaves at concentrations of 0.25% and 0.5% active ingredient on a volume or weight/volume basis: sulfonates, alcohols, ethyoxylated hydrocarbons, esters, sulfates, and amines. Many adjuvants in the following classes: alcohols, sulfonates, ethoxylated hydrocarbons, polyethylene glycols, carbohydrates, proteins, and phosphates were not phytotoxic at concentrations as high as 1.0%. Sometimes increasing phytotoxicity occurred at increasing concentrations, but the humectants, such as glycerol and propylene glycol, were not phytotoxic at concentrations of 10.0%. Selected adjuvants were mixed with a foliar fertilizer (12.0N–1.7P–3.3K–0.5S) and evaluated for enhancement of foliar absorption of N and P. The average increases in percentage of N and P for the glycerol, lecithin, and Pluronic L-121 (an ethyoxylated hydrocarbon), and foliar fertilizer combinations, respectively, were 8.9%, 2.2%, and 2.5% for N and 34.2%, 27.6%, and 20.8% for P over the foliar fertilizer control, respectively, for the 3 adjuvants.
LIVE STREAM CLASSROOMS DURING PANDEMIC 2020: COMPARATIVE STUDY OF THE PERCEPTION OF TEACHERS AND STUDENTS

Due to the pandemic situation of the COVID-19 the live stream had being adopted for online learning in higher education system of Pakistan. The bidirectional communication in live stream is synchronized connection via Internet, such as video-audio conferencing though the software of the Microsoft team, zoom, google meet and Skype had utilized for learning. The purpose of the research were to compare the perception of teachers and students regarding the live stream classrooms during outbreak covid-19. The study were significant to teachers, students, new researchers and policy makers. The study were descriptive survey method. The research were quantitative and questionnaire were utilized by researcher to collect the respondent’s responses. Whereas descriptive and inferential statistics were used to analyzed the data. The results of the study were depicted that mostly respondents were not satisfied though online live stream classrooms, there is no difference between the perception of the teachers and students regarding the live stream classrooms during outbreak covid-19. Students were not self-motivated and to maintain discipline in live sessions is very difficult for teachers as well. Technical issues had made class boring, cause the cognitive exertion and become time consuming. The subjects like science mathematics and engineering cannot taught properly. Learners can engage through video conferencing and interactive discussion. Moreover research recommended that teachers should trained for these techniques, advance applications should provide by Government for online learning, interactive discussion is the best way to engage learners in live stream. Discussion method may be used and video conferencing may be preferred.