Miracle-dz/UniFAR-FTUs huggingface dataset:
Help-Seeking in Informal Family Caregivers of People with Dementia: A Qualitative Study with iSupport as a Case in Point

Supportive measures and training interventions can improve the care of people with dementia and reduce the burden on informal caregivers, whose needs remain largely unmet. iSupport is an evidence-based online intervention developed by the World Health Organization to provide support and self-guided education to informal family caregivers of people with dementia. This qualitative study explored barriers and facilitators in the access and use of supportive measures for family caregivers of people with dementia living in Southern Switzerland (Ticino). We conducted five focus groups and explored experiences, beliefs, and attitudes toward seeking help (SH), and used thematic analysis to identify key themes. Participants (N = 13) reported a general reluctance to SH. We identified four main barriers to SH: high level of burden; sense of duty; fear of being misunderstood by others; and difficulty in reaching information. We also identified facilitators of help seeking behaviors and unveiled the need of caregivers to be assisted by a dementia case manager to facilitate access to support resources. Local services and interventions should be adapted to caregivers’ needs and expectations, with the aim of facilitating the acceptance of, access to, and service integration of existing and future support measures, including iSupport.
Humanin and Humanin Analogs

Cognitive Vitality Reports® are reports written by neuroscientists at the Alzheimer’s Drug Discovery Foundation (ADDF). These scientific reports include analysis of drugs, drugs-indevelopment, drug targets, supplements, nutraceuticals, food/drink, non-pharmacologic interventions, and risk factors. Neuroscientists evaluate the potential benefit (or harm) for brain health, as well as for age-related health concerns that can affect brain health (e.g., cardiovascular diseases, cancers, diabetes/metabolic syndrome). In addition, these reports include evaluation of safety data, from clinical trials if available, and from preclinical models.
Portfolio Optimization and Diversification in China: Policy Implications for Vietnam and other Emerging Markets

This paper is conducted to examine risk, return and portfolio optimization at the industry level in China over the period 2007-2016. On the ground of the classical Markowitz framework for portfolio optimalisation, the mean-semivariance optimization framework is established for China’s stock market at the industry level. Findings from this study indicate that Healthcare sector plays a significant role among ten industries in China on a stand-alone basis. In addition, a significant change of rankings among the sectors in term of risk is found when the mean-semivariance optimization framework is used. We also find that utilising this new framework helps improve the optimal portfolios in relation to performance, measured by Sortino ratio, and diversification. A simulation technique, generally known as resampling method, is also utilised to check the robustness of the estimates. While the use of this resampling method appears not to improve the performance of optimal portfolios compared with the mean-semivariance framework for China, there is a remarkable advance in diversification of the optimal portfolios. Implications for investors and the governments in Vietnam and other emerging markets have emerged from the study.
Validation of IFS+RT OV/MFASIS solar reflectances against GOES-16 ABI observations

Solar reflectances simulated by running RTTOV/MFASIS (fast visible simulator) on input meteorological data from ECMWF’s operational IFS short-range forecasts are compared with corresponding GOES-16 ABI reflectances observed in channels 0.47, 0.64 and 0. 86μm. This is the first systematic validation of the IFS at wavelengths in the solar spectrum, which is expected to provide additional information about the prediction of meteorological features that are usually not well detected at infrared frequencies (e.g., low-level clouds). Month-long statistics of reflectances as well as individual images are used to identify deficiencies in both the IFS and in the RTTOV/MFASIS radiative transfer model. In the IFS, issues are found in the representation of trade-wind low-level clouds over ocean, shallow convection over the Amazon region and low-level clouds inside the eye of tropical cyclones. On the other hand, this study also confirms the existence of biases resulting from some of RTTOV/MFASIS’s simplifications, such as those made in the Rayleigh scattering computations and in the use of a look-up table. These conclusions are confirmed through an independent comparison of IFS with CERES observations. Results from this work are relevant to the developments towards the assimilation of solar reflectances in ECMWF’s 4-Dimensional Variational data assimilation system (4D-Var).
Bakery Waste is an Alternative of Maize to Reduce the Cost of Pork Production

Nepal is an agricultural country where more than 60% of people depend upon agriculture. Total contribution of agricultural sector in GDP of Nepal is 32.35%. Among them contribution of livestock sector in total GDP is 30% (MoAC, 2009). The pig population of Nepal is estimated to be 1.33 million and producing 24535 MT pork per annum. Out of 1.33 million, indigenous pigs constitute 58% of the total pig population while the remaining 42% are exotic or improved breeds (Krishi Diary, 2018).
Facial expression recognition based scoring system for restaurants by using deep learning concepts

Now-a-days in advance countries automated unmanned restaurants are more popular as this restaurants will not have any human power to take customer feedbacks about food quality and service and to automate this process author has introduce concept called ‘Deep Learning Facial Expression Recognition Based Scoring System For Restaurants’ where customers will be asked to give rating to food and upload his photo and based on user facial expression application will inform whether customer was satisfied or not. To extract facial expressions from photo we are using CNN (Convolution Neural Networks) machine learning algorithm. This algorithm can predict 3 different expression from photo such as satisfied, neutral or disappointed.
Proteolytic Enzyme Activity of RhizopusoligosporusSp

The objectives of this study was to obtain protease enzymes from two (2) isolates of RhizopusoligosporusSp, namely isolates of R. oligosporus WS and R. oligosporus RT. The short-term objectives of this study were to perform qualitative tests of protease enzyme activity, produce and optimize the production time of protease enzymes and to test the activity of protease enzymes. Two isolates of R.oligosporus WS and R.oligosporus RT were first rejuvenated on Potato Dextro Broth (PDB) media. Characterization was done by observing the macroscopic and microscopic characteristics of the fungus. Macroscopic observations included colony color, color and density of mycelium. Microscopically the isolates were observed under a microscope to see the color and shape of the conidia, sporangiospore length, length and shape of the columella.Then the isolates were tested for their proteolytic activity on Skim Milk Agar (SMA) selective media and then produced on selective liquid media. This study used a randomized block design (RAK) with variations in the incubation time of protease enzyme production, namely 3, 5, 7, 9 and 11 days with Three (3) replications for each treatment with parameter 1). Qualitative test of protease enzyme activity, 2) production and optimization of protease enzyme production time, 3) test protease enzyme activity (U/ml), protein content and specific enzyme activity (U/ml). The results showed that the two isolates R. oligosporus WS and R. oligosporus RT were identified macroscopically and microscopically as having brownish gray conidia with conidia lengths of 11.4 μm and 12.0 μm. Both isolates had the ability to hydrolyze protein with a hydrolysis index of 1.82 mm and 1.56 mm. The isolates of R. oligosporus WR and R. oligosporus RT produced the highest protease enzymes at an incubation time of 7 days which were 1.83 ± 0.014 U/mL and 1.51 ± 0.084. R. oligosporus WR and R. oligosporus RT isolates were able to produce the highest protease-specific enzymes at incubation time of day 7 which were 1.52 ± 0.03 U/mL and 1.20 ± 0.06 U/ml respectively
Isolation, Identification and characterization of phyllosphere Bacteria from vegetables

Diverse group of microorganism colonize phyllopshere and carry out different but specific ecological functions. The phyllosphere of five different vegetables plants; Common Okra)AbelmoschusesiculentusL. , (Fluted Pumpkin) Telfariaoccidentalis, (African Spinach)Amaranthuscruentus ,(Jew’s Mallow)Corchorusolitorius and (Lagos Spinach) Celosia argentea}, each from two different locations, (Student Union Building and the Fadama of Federal University of Agriculture, Abeokuta, Ogun State) were examined Microbiologically for bacterial growth using culture-dependent techniques. A total of 43 bacterial covering 11 genera were isolated and characterized as Citrobacter, Staphylococcus, Pseudomonas , Streptococcus, Salmonella, Proteus, Shigella, Escherichia, Enterobacter, Klebsiella, and Bacillus.
International Journal of Reconfigurable and Embedded Systems (IJRES)

Received Jan 3, 2022 Revised Feb 25, 2022 Accepted Mar 12, 2022 In this paper, we present current amplifier based transimpedance amplifier (TIA) for biosensor applications. Proposed design has low-noise, high Transimpedance gain that can be used for low current measurement applications. The current amplifier based TIA is implemented in order to resolve the fabrication issues related to high value feedback resistor. In this design, the input block to TIA is a low amplitude current amplifier. The designed amplifier is implemented in 90 nm complementary metal-oxide semiconductor (CMOS) technology. The design achieves transimpedance gain of 800 kΩ with a bandwidth of 5 kHz and input referred current noise is of 0.152 pA/√HZ for an input of 41 nA bypassed from current amplifier with input of 200 pA.
Putting Quantitative Trade Models to the Test: Evidence from the Trump Tariffs∗

An important goal of a large quantitative trade literature is to shed light on the economic consequences of changes in tariffs, from unilateral trade liberalization episodes to the formation of regional trade agreements and trade wars. To help assess and potentially strengthen the credibility of the predictions of quantitative trade models we propose a new testing procedure that is intuitive, easy to implement, and consistent with standard practices in the field. Critically, unlike standard goodness of fit tests, our test is applicable in the presence of unobserved shocks that may be larger in magnitude than tariff changes and rich enough to rationalize any dataset. The basic idea behind our test is to exploit tariff changes, or observable shifters of these, that are orthogonal to unobserved shocks, a standard exclusion restriction in the empirical trade literature. As an illustration of how our test can be combined with state-of-theart quantitative and empirical work, we test the welfare consequences of the Trump tariffs predicted by Fajgelbaum et al. (2020). ∗This version: June 2022. Author contacts: rodrigo.adao@chicagobooth.edu, costinot@mit.edu, and ddonald@mit.edu. We are grateful to Robin Li, Nimisha Gupta, John Sturm and Akash Thakkar for outstanding research assistance and to seminar audience at Berkeley, Chicago, CREI, Duke, and Zürich for helpful comments.
Ein Scoping Review zu Tätigkeitsfeldern am Beispiel der Versorgung von chronisch Erkrankten

Background. Internationally, community health nursing (CHN) is an established concept. In Germany, the implementation in primary care is currently being discussed. So far, a systematic description of which tasks and interventions CHNs conduct in health care practice is missing. Methods. As part of a scoping review, a literature analysis was conducted in international databases to obtain an overview of the literature on interventions and fields of activity of CHNs. Results. A total of 24 studies were included in the analysis. Different focuses of interventions could be identified and categorized: health promotion/prevention, evidence-based nursing, individual care, higher-level activities. Conclusion. The results suggest that CHN interventions can improve care for the chronically ill. The transferability of the results to the German health care system is currently limited due to the professional legal situation and the unclear situation regarding funding.
PRIMARY SCIENCE TEACHERS’ PERFORMANCE ASSESSMENT ABOUT STUDENTS’ COGNITIVE ACTIVATION

The research focuses on primary science teacher performance according to chosen criteria (cognitive activation, basic skills) to distinguish actual versus desired teaching performance accordingly to undergoing educational reform in Latvia. The purpose in this study is to identify personalized teacher professional development needs based on performance in observed lessons. The framework of teacher performance assessment to support teaching 21 century skills was used to get data about teacher performance in observed lessons (49 teachers). The data was analyzed and compared against the desired teacher performance level descriptors. As a result, the study identifies 4 groups of teachers with varied actual and desired performance differences to suggest the best personalized needs for further professional development, which are crucial to implement undergoing reform.
1 In-life range modularity for electric vehicles : the 2 environmental impact of a range-extender trailer 3 system 4

15 Purpose: The range of an electric vehicle (EV) remains an important hurdle for a wide-spread 16 consumer adoption. Opting for an EV with an over-dimensioned battery not only significantly 17 increases the capital expenditure, it also increases the vehicle’s impact on climate change and 18 diminishes the EV’s inherent benefit concerning local air quality levels. The concept of in-life 19 modularity by means of a range-extender trailer is investigated as an alternative for high battery 20 capacities. Both a generator as a battery based range-extender are discussed. 21 Method: A life cycle assessment (LCA) is performed for comparing the combination of 40 kWh EV 22 and the trailer with a range of conventional cars and EVs, differentiated per battery capacity. An 23 application factor of 5% is assumed for the range-extender. In addition, environmental breakeven 24 distances are calculated for either replacing an existing ICE-based vehicle or for a one-on-one 25 comparison between EVs, the EV + generator combination and ICE-based vehicles. 26 Results: While offering the same electric range, the 40 kWh EV + generator trailer contributes 30% 27 to climate change, compared to a 90 kWh EV. In case of a 50 kWh battery trailer, this reduction 28 increased to 40%. This indicates in-life modularity has a positive impact on climate change. 29 Breakeven distances indicate that replacing an ICE-car with another one is no solution, when climate 30 change is considered. The range-extended 40 kWh EV becomes a better solution after approximately 31 45.000 km in case of replacing an existing car, while this distance is reduced to less than 10.000 km 32 when it is compared to a new PHEV. 33
CÔNG NGHỆ HÓA SINH VÀ PROTEIN PURIFICATION AND BIOLOGICAL ACTIVITY OF A RECOMBINANT BOVINE LACTOFERRIN FROM PICHIA PASTORIS KM71-3 STRAIN

Lactoferrin is a member of the transferrin protein family with function of iron transport in blood. However, lactoferrin also plays an important role in the mammalian innate immune system, showing protective effects against several microorganisms such as viruses, bacteria, fungi and parasites, and displaying anticancer activities. In the present study, some suitable conditions for affinity purification of a recombinant bovine lactoferrin (rbLF) from intracellular Pichia pastoris KM71-3 strain were investigated. The Ni -chelate resin was better than the Cu -chelate resin for affinity purification of rbLF protein. The rbLF protein was bound to Ni -chelate resin for 18 hours in 1X PBS buffer. Antimicrobial effect of rbLF against Staphylococcus aureus, Escherichia coli, Micrococcus luteus, Bacillus subtilis and Candida albicans was measured. The rbLF showed growth inhibition with Micrococcus luteus, Bacillus subtilis at concentration of 1 mg/ml. The rbLF also exhibited inhibition effect on the proliferation of cancer cell lines, Hep2-C and FL.
Physical Processes Controlling the Vertical and Longitudinal Distributions of Relative Humidity in the Tropical Tropopause Layer Over the Pacific

The vertical distribution of relative humidity with respect to ice (RHI) in the Boreal wintertime Tropical Tropopause Layer (TTL, ≃14–18 km) over the Pacific is examined with the extensive dataset of measurements from the NASA Airborne Tropical TRopopause EXperiment (ATTREX). Multiple deployments of the Global Hawk during ATTREX provided hundreds of vertical profiles spanning the longitudinal extent of the Pacific with accurate measurements of temperature, pressure, water vapor concentration, ozone concentration, and cloud properties. We also compare the measured RHI distributions with results from a transport and microphysical model driven by meteorological analysis fields. Notable features in the distribution of RHI versus temperature and longitude include (1) the common occurrence of RHI values near ice saturation over the western Pacific in the lower-middle TTL (temperatures greater than 195 K); (2) low RHI values in the lower TTL over the central and eastern Pacific; (3) common occurrence of RHI values following a constant mixing ratio in the middle-to-upper TTL (temperatures between about 190 and 200 K), particularly for samples with ozone greater than about 50–100 ppbv indicating mixtures of tropospheric and stratospheric air; (4) RHI values typically near ice saturation in the coldest airmasses sampled (temperatures less than about 190 K); and (5) common occurrence of RHI values near 100% across the TTL temperature range in air parcels with low ozone mixing ratio (O3 < 50 ppbv) indicative of recent uplift by deep convection. We suggest that the typically saturated air in the lower TTL over the western Pacific is likely driven by a combination of the frequent occurrence of deep convection and the predominance of radiative heating (rising motion) in this region. The low relative humidities in the central/eastern Pacific lower TTL result from the lack of convective influence, the predominance of subsidence, and the relatively warm temperatures in the region. The nearly-constant water vapor mixing ratios in the middle-to-upper TTL likely result from the combination of slow ascent (resulting in long residence times) and wave driven temperature variability on a range of time scales (resulting in most air parcels having experienced low temperature and dehydration). The numerical simulations generally reproduce the observed RHI distribution features and sensitivity tests further emphasize the strong sensitivities of TTL relative humidity to convective input and vertical motions.
A $q$-analogue of Catalan Hankel determinants (New Trends in Theory)

In this article we shall survey the various methods of evaluating Hankel determinants and as an illustration we evaluate some Hankel determinants of a q ‐analogue of Catalan numbers. Here we consider \displaystyle \frac{(aq;q)_{n}}{(abq^{2};q)_{n}} as a q ‐analogue of Catalan numbers C_{n}=\displaystyle \frac{1}{n+1}\left(\begin{array}{l} 2n\\ n \end{array}\right) , which is known as the moments of the little q ‐Jacobi polynomials. We also give several proofs of this q ‐analogue, in which we use lattice paths, the orthogonal polynomials, or the basic hypergeometric series. We also consider a q ‐analogue of Schröder Hankel determinants, and give a new proof of Moztkin Hankel determinants using an addition formula for {}_{2}F_{1}.
. 0 0 . 1 0 . 2 0 . 3 0 . 4 TPP FD

Sorted `1 regularization has been incorporated into many methods for solving high-dimensional statistical estimation problems, including the SLOPE estimator in linear regression. In this paper, we study how this relatively new regularization technique improves variable selection by characterizing the optimal SLOPE trade-off between the false discovery proportion (FDP) and true positive proportion (TPP) or, equivalently, between measures of type I error and power. Assuming a regime of linear sparsity and working under Gaussian random designs, we obtain an upper bound on the optimal trade-off for SLOPE, showing its capability of breaking the Donoho–Tanner power limit. To put it into perspective, this limit is the highest possible power that the Lasso, which is perhaps the most popular `1-based method, can achieve even with arbitrarily strong effect sizes. Next, we derive a tight lower bound that delineates the fundamental limit of sorted `1 regularization in optimally trading the FDP off for the TPP. Finally, we show that on any problem instance, SLOPE with a certain regularization sequence outperforms the Lasso, in the sense of having a smaller FDP, larger TPP and smaller `2 estimation risk simultaneously. Our proofs are based on a novel technique that reduces a calculus of variations problem to a class of infinite-dimensional convex optimization problems and a very recent result from approximate message passing theory.
International Journal of Management Sciences and Business Research, May-2022 ISSN (2226-8235) Vol-11, Issue 5

The study investigates the association between family business and the performance of the firms. To underscore this relationship, the case of nonfinancial companies is analysed between 2012 and 2017. The generalised method of moments (GMM) is employed as the econometric method that effectively controls all categories of endogeneity. The study finds that family firms outperform their nonfamily counterparts in terms of firm performance. The result is positively significant for both the financial performance measure, ROA, and the market measure, Tobin‟s Q. The outcome of this research suggests that policymakers should initiate the necessary governance mechanisms to control the actions of the family firms that might jeopardise the interests of the minority shareholders.
Learning Domain-Independent Policies for Open List Selection

Since its proposal over a decade ago, LAMA has been considered one of the best-performing satisficing classical planners. Its key component is heuristic search with multiple open lists, each using a different heuristic function to order states. Even with a very simple, ad-hoc policy for open list selection, LAMA achieves state-of-the-art results. In this paper, we propose to use dynamic algorithm configuration to learn such policies in a principled and data-driven manner. On the learning side, we show how to train a reinforcement learning agent over several heterogeneous environments, aiming at zero-shot generalization to new related domains. On the planning side, our experimental results show that the trained policies often reach the performance of LAMA, and sometimes even perform better. Furthermore, our analysis of different policies shows that prioritizing states reached via preferred operators is crucial, explaining the strong performance of LAMA.