Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors inﬂuencing technology adoption among smallholder farmers: a systematic review in Africa

Smallholder agriculture has been identiﬁed to be critical in the creation of employment, improving food security and improving the economy. However, smallholder agriculture in Africa is characterised by a low production level which has been linked to the limited use of technologies. Several factors inﬂuence the adoption of technologies among smallholder farmers in Africa. This systematic literature review focuses on the factors inﬂuencing technology adoption among smallholder farmers in Africa and identiﬁed 128 peer-reviewed papers in English between January 2000 to December 2019. The majority were carried out in Kenya, Uganda, and Malawi, with the major crops being maize, legumes and rice. This review identiﬁed 29 factors that were broadly classiﬁed into ﬁve main categories: (i) farmers’ characteristics; (ii) farm characteristics; (iii) technology characteristics; (iv) institutional factors; and (v) ﬁnance. Of these, ﬁnance (81 articles), gender of household head (71 articles), age (68 articles), education (64 articles), farm size (62 articles) and extension access (59 articles) are the most prominent factors mentioned. The factors identiﬁed in this review were then related to existing technology adoption theories, and it was concluded that ﬁnance does not adequately feature in any of these extant theories. As illustrated by the relatively high occurrence of ﬁnance, this review puts forward a comprehensive framework for technology adoption and also provides critical recommendations to improve technology adoption among smallholder farmers in Africa.
PERCEPTIONS OF COVID-19, INFORMATION SEEKING BEHAVIOR, AND POLITICAL ORIENTATION

COVID-19 was declared an international pandemic in March 2020 and infected millions of people globally in less than six months. Research suggests that a large amount of both accurate and misinformation exists on the pandemic, and it would be expected that an individual’s political orientation would influence their perception of the virus and the information that they endorse. Based on past research, it would be expected that both liberals and conservatives would be equally concerned about the COVID-19 pandemic and endorse similar measures. However, Republicans downplayed the pandemic and were more likely to consider it a hoax, while Democrats exaggerated the pandemic and were more likely to advocate for excessive measures. I asked participants to complete various measures related to their political ideology and beliefs about the COVID-19 pandemic. 3 variables were tested as potential mediators and moderators that could explain this relationship. The results suggest that selective exposure to attitude consistent information mediated the relationship between political ideology and perceptions of the pandemic. Behavioral immune system sensitivity and disgust reappraisal where also tested as potential pathways, but the results were not significant. These results suggest that selective exposure is a major factor in determining an individual’s perception of the COVID-19 pandemic.
Assessing Team’s Back ‘4’ for Predicting Match Draw

Many researches have tried to predict soccer outcomes using different methods such as supervised learning and unsupervised learning approaches. Many factors and features have been used to carry out this prediction. However, none so far has predicted the outcome of match results with emphasis and information on critical position of play in the entire team. Most teams lose by a slim margin, and this is vivid in the fact that 81.57% of matches have a goal difference per match that is less than two goals. This research critically considered the back '4' of teams, and was able to predict whether the match will be won, lost or end in stalemate with much emphasis on deadlock. Support Vector Machine was used to predict the result of matches using only the back '4' information of the team. The result was evaluated by predicting the whole of 2018/2019 season of the English Premier League. The prediction results give a 76.8% accuracy and error rate of 0.23. (FMS) two FMS individual and overall scores and physical performance variables of lower-limb power (jumps), repeated sprint ability and shot speed. Twenty-two under 16 (U16) and twenty-six under 19 (U19) national competitive soccer players in study. All participants were evaluated according to jump instep kick speed and anaerobic performance. There were no significant differences in significant negative between and had a significant negative correlation to squat jump Rotary stability had a significant negative correlation to RAST The results suggest that individual scores may be better discriminants of performance than FMS total score and established minimal association between FMS scores and physical variables. Based on that, FMS may be suitable for the purposes of determining physical function but not for discriminating physical performance.
Analysis of influencing factors of initial public offering underpricing in Indonesia stock exchange

This article aims to analyze influence factors underpricing of IPO in Indonesian Stock Exchange. Independent variable for which tested in this research is company age, company size, profitability, financial leverage, underwriter reputation, and auditors’ reputation. Dependent variable is proxied use initial return. Population in this research is a company that experienced underpricing for years 2012-2017 in BEI. The technique of collection sample using a purposive sampling technique and the criteria which had been determined and produce 91 companies that become the sample. This research is quantitative research based hypothesis test (explanatory research). The method of analysis that used in this research was descriptive and multiple Linear regression analysis. Based on descriptive analysis, the average initial return obtained investors when ipo during the period observations on the 2012-2017 of 43.5%. The results of the analysis regression showed that the company size and underwriter reputation have an influence negative significant impact on initial return. While company age, profitability, financial leverage, and auditors reputations do not affect in significant impact on initial return.
Evaluating the Effects of Cooperative Perception on Avoiding Pedestrian Crashes for Connected and Automated Vehicles - Using Virtual Simulator to Evaluate the Automated Emergency Braking System for Avoiding Pedestrian Crash at Intersections under the Occluded

At an intersection, a crash between a pedestrian and a vehicle may occur under the occluded condition. An automated emergency braking (AEB) system could be utilized to actively detect pedestrians and react to avoid potential conflicts. This study contribution is evaluating the effectiveness of the AEB system under occlusion conditions. The braking algorithm was developed in the virtual simulator CARLA to control the ego vehicle. Three occlusion scenarios in which the sensor of the AEB system could not detect the pedestrian if the pedestrian is occluded by a stopping vehicle. The evaluation experiments were conducted at a typical 4-leg intersection considering different motion statuses of the ego vehicle and pedestrian. The effects of field of view (FoV) of the sensor and activation threshold of the AEB system were also explored. The study indicated that the effectiveness of the AEB system could be reduced by the occlusion time. A longer activation threshold is recommended if the pedestrian is potentially occluded for a long time. The effects of other factors such as the speed of the ego vehicle and pedestrian and scenarios were also identified.
Surgical Management of a Giant Compound Odontoma with 52 Denticles and Impacted Canine in the Maxilla of a Nonsyndromic Child: A Case Report

particularly in the palatal region. Amongst them, 80% are single tooth, with over 75% of the ST are impacted. 4 Based on the orientation, over 50% are normally oriented and 34% are inverted. 4 Based on the size and composition, supernumerary teeth can be classified as complex, compound or mixed odontoma. 5 The complications of ST include delayed or failure of eruption of permanent teeth, malocclusion, and ectopic eruption. When ST is in close proximity to permanent teeth, in some cases, loss of vitality and abnormal dental development have been reported. 6 The diagnosis of ST is made during routine radiographic examination and mostly as an incidental finding. Majority of the ST remains innocuous in the primary dentition, and in some cases, throughout the life period. 7 The severity of ST depends on its proximity to the normal set of dentition, anatomical structures, and complexity including the form and number. 8 Genetic predisposition has been attributed as main reason for formation of ST with higher prevalence in Chinese ethnic populations. 3 ST has been associated with several syndromes including Cleidocranial dysplasia, Gardner's syndrome, Ehler Danlos syndrome, Crouzon's syndrome, Down syndrome, and Ectodermal dysplasia. 9,10 In non-syndromic patients, ST most commonly occurs as a single entity; however, presence of multiple ST has been reported in the literature.
Dealing with ignorance: universal discrimination, learning and quantum correlations

The problem of discriminating the state of a quantum system among a number of hypothetical states is usually addressed under the assumption that one has perfect knowledge of the possible states of the system. In this thesis, I analyze the role of the prior information available in facing such problems, and consider scenarios where the information regarding the possible states is incomplete. In front of a complete ignorance of the possible states' identity, I discuss a quantum "programmable" discrimination machine for qubit states that accepts this information as input programs using a quantum encoding, rather than as a classical description. The optimal performance of these machines is studied for general qubit states when several copies are provided, in the schemes of unambiguous, minimum-error, and error-margin discrimination. Then, this type of automation in discrimination tasks is taken further. By realizing a programmable machine as a device that is trained through quantum information to perform a specific task, I propose a quantum "learning" machine for classifying qubit states that does not require a quantum memory to store the qubit programs and, nevertheless, performs as good as quantum mechanics permits. Such learning machine thus allows for several optimal uses with no need for retraining. A similar learning scheme is also discussed for coherent states of light. I present it in the context of the readout of a classical memory by means of classically correlated coherent signals, when these are produced by an imperfect source. I show that, in this case, the retrieval of information stored in the memory can be carried out more accurately when fully general quantum measurements are used. Finally, as a transversal topic, I propose an efficient algorithmic way of decomposing any quantum measurement into convex combinations of simpler (extremal) measurements.
OP-SWRJ200015 1..12

Digital dating abuse (DDA), which is the use of social media and mobile phones to abuse a dating partner, is a common and harmful form of dating violence among youths. To date, this issue has not been studied among Latinx youths. The current study examined DDA among a sample of 70 Latinx youths with dating experience, using survey data on participants’ experiences with traditional forms of offline dating violence, DDA victimization and perpetration, healthy relationship knowledge, and self-reported conflict resolution skills. Results showed that Latinx youths experienced DDA and that there was a strong link between DDA and offline forms of dating abuse. Most participants reported high levels of healthy relationship knowledge and conflict resolution skills, but results indicated a link between DDA experience and fewer positive conflict resolution behaviors. The study has implications for the assessment and prevention of DDA among diverse populations of youths, supports the incorporation of conflict resolution skills in dating violence prevention efforts, and calls for future research on the cultural context of DDA among Latinx youths.
A study of land use and Fairtrade coffee farming in Costa Rica

This thesis is a comparative study of three coffee producers in the San José region of Costa Rica, who either are or have been Fairtrade certified. The purpose is to examine the land use models of the coffee farmers and to analyse what impact Fairtrade certification has had on the choice of these. The theoretical framework was based on the concept of land sharing and land sparing as a way to understand the existence and function of non-commercial plants within the farmland on the one hand and the relationship between agriculture and nature on the other. Participatory mapping and semi-structured interviews were conducted among farmers in the Santa Elena community, together with interviews with representatives from the cooperatives, the department of agriculture and more. The results show that most farmers don’t identify their land use as belonging to any particular strategy but nevertheless use intensive cultivation with chemical fertilisers and pesticides. Monoculture and polyculture exists and non-commercial trees could be found on both types of farms, with the main purpose of providing shade for the coffee. A dichotomy between agriculture and nature appears to be common, which would mean that a more land sparing philosophy is prevalent. Only one organic farmer showed clear signs of land sharing practices with an emphasised synergetic approach with focus on ecosystem services. In conclusion, it seems like Fairtrade certification affects these types of land use mostly in an indirect manner, working mainly with the cooperatives who then primarily work with aspects like regulated chemical use. It also appears that the producers who seek out certification are either those who high altitude farmers who can live up the quality standards and/or those who already share common principles with Fairtrade, leading to marginal changes in land use after certification
Risk perception and preparedness of backcountry visitors in Australia’s 2 Snowy Mountains 3

24 Effective management of National Parks requires an understanding of visitors to provide safe and 25 enjoyable visitor experiences. Risk and preparedness of snow-based recreation is not well 26 understood outside of the context of avalanches. This study investigated risk perception and 27 preparedness of snow-based backcountry visitors in the Snowy Mountains of Australia through the 28 theoretical lens of recreation specialisation. The recreation specialisation index was an appropriate 29 tool for segmenting snow-based backcountry visitors into intermediates and experts along 30 behavioural, cognitive and affective dimensions. We identified an overall low perception of risk and 31 discuss the reasons and implications of this. In contrast, level of preparedness was of a high standard 32 among both intermediate and expert snow-based recreationists. This pertained to pre-trip planning 33 and the carrying/use of safety equipment and trip notification behaviour. The findings provide 34 insights for land managers to enhance visitor safety and risk management for snow-based 35 backcountry recreationists.
EFFECT OF PARTICLE SIZE AND FAT LEVELS ON THE PHYSICO-CHEMICAL, TEXTURAL AND SENSORY CHARACTERISTICS OF LOW-FAT GROUND PORK PATTIES

Dietary fat and cholesterol content are considered to be controllable factors in multifactorial etiology of heart diseases and obesity. Meat and meat products are maligned with a fact of highfat, high cholesterol and high calorie diet. This has lead to increase in demand of low-fat meat products. Pork patties generally contain 30-40% fat and warrants reduction in fat contents. However rheological, structural, processing, nutritional and sensory characteristics of comminuted meat products are directed by the fat content in the formulation and particle size of ground meat system (Kregel et al, 1986; Manish Kumar and Sharma, 2003)
Inhibition of APOE potentiates immune checkpoint therapy for cancer

Checkpoint immunotherapy is capable of unleashing T cells for controlling tumor, whereas it is destroyed by immunosuppressive myeloid cell. Apoprotein E (APOE) refers to a ligand in terms of the members of low-density lipoprotein (LDL) receptor family for mediating Apoprotein B-involving atherogenic lipoprotein clearance. Besides, tumor-infiltration macrophage can express APOE. The present study reported Apoe-/- mice to exhibit higher resistance toward the development of three types of carcinomas as compared with mice with wild type and to have greater responses to αPD-1 (anti-PD-1) immunotherapy. Moreover, treatment by exploiting APOE inhibitor (COG 133TFA, αAPOE) was capable of curbing tumor development and fostering regression if in combination of αPD-1. According to single-cell RNA sequencing (scRNA-seq), Apoe deletion was correlated with the decline of C1QC+ and CCR2+ macrophage within tumor infiltration, and mass spectrometry results noticeably showed down-regulated the number of M2 macrophages as well. Furthermore, APOE expression in cancer patients resistant to αPD-1 treatment significantly exceeded that in the sensitive group. For this reason, APOE is likely to be targeted for modifying tumor macrophage infiltrate and augmenting checkpoint immunotherapy.
N EURAL N ETWORK E XTRAPOLATIONS WITH G-INVARIANCES FROM A S INGLE E NVIRONMENT

Despite —or maybe because of— their astonishing capacity to fit data, neural networks are believed to have difficulties extrapolating beyond training data distribution. This work shows that, for extrapolations based on finite transformation groups, a model’s inability to extrapolate is unrelated to its capacity. Rather, the shortcoming is inherited from a learning hypothesis: Examples not explicitly observed with infinitely many training examples have underspecified outcomes in the learner’s model. In order to endow neural networks with the ability to extrapolate over group transformations, we introduce a learning framework counterfactually-guided by the learning hypothesis that any group invariance to (known) transformation groups is mandatory even without evidence, unless the learner deems it inconsistent with the training data. Unlike existing invariance-driven methods for (counterfactual) extrapolations, this framework allows extrapolations from a single environment. Finally, we introduce sequence and image extrapolation tasks that validate our framework and showcase the shortcomings of traditional approaches.
Hydrogenation of graphene in view of odd electrons correlation

The paper presents evidence of a rather strong correlation of odd electrons in the singlet state of graphene. Due to the correlation, the chemical modification of graphene can be considered following a certain algorithmic computational procedure. Originated due to the correlation and distributed over the carbon atoms of graphene membrane with fraction numbers NDA, effectively unpaired electrons lay the algorithm foundation. The highest NDA value points to the target atom that enters a chemical reaction at the considered step. Following the pointers, a stepwise design of polyderivatives can be performed. Applied to the hydrogenation, the algorithmic design has exhibited that graphene hydrogenation should be attributed to a highly complicated event, whose final hydride products depend on a number of factors such as: 1) the manner of the graphene membrane fixation; 2) the accessibility of the membrane both sides to hydrogen; 3) the composition (molecular or atomic) of the hydrogen. In general, the hydride formation is multimode in regards composition and structure. Thus, the formation of 100% hydride with regular chairlike hexagonal packing of CH units which can be attributed to graphane is possible if only the graphene membrane is fixed over perimeter while its basal plane is accessible to hydrogen atoms from both sides.
A uniﬁed approach for action recognition on various data modalities

We present a uniﬁed approach for action recognition on various sensor data modalities. Motion is represented in an image, a EfﬁcientNet 2D-CNN is used for training an action recognition model on the common image representation. Our uniﬁed approach handles different sensor modalities in a common way. That distinguishes our approach to many previous proposed approaches that propose different methods per modality. Therefore, it remains simple to evaluate which sensor ﬁts a certain action recognition problem. We show that our approaches generalizes well across 5 different data modalities (pose sequences transformed from videos, skeleton sequences, motion capture data, inertial measurements, Wi-Fi CSI ﬁngerprints) and achieves comparable results on 4 public available datasets and the MMAct challenge dataset.
SYSTEMATICS OF THE LEPTAUCHENIINE OREODONTS (MAMMALIA: ARTIODACTYLA) FROM THE OLIGOCENE AND EARLIEST MIOCENE OF NORTH AMERICA

—The Leptaucheniinae was a subfamily of oreodonts that had eyes and ears high on their skulls, a large nasal-facial vacuity, large auditory bullae, and very hypsodont teeth. They were very common in the Whitneyan and early Arikareean of the High Plains and western Montana, yet vanished in the late Arikareean. Their taxonomy has long been confused by post-mortem deformation and lack of statistical analysis, culminating with oversplitting into the 7 genera and 31 species recognized by Schultz and Falkenbach (1968). CoBabe (1996) employed multivariate analysis and recognized only two genera, Sespia and Leptauchenia , the latter only containing two species. She did not group her specimens by stratigraphic level, nor address the issue of how much variability is reasonable within a single population. We reanalyzed the problem using both bivariate and multivariate statistics, and compared samples within stratigraphic levels. There seem to be only three species that are statistically supported and diagnosable: the smaller taxon Leptauchenia decora (early Orellan to early Arikareean), the intermediate-sized L. major (late Whitneyan to late Arikareean), and the large, robust L. lullianus (restricted to the early and middle Arikareean). Contrary to previous hypotheses that leptaucheniines were hippo-like aquatic forms or hyrax-like rock dwellers, all the evidence seems to suggest that they lived near the eolian deposits in which they were buried. Their taphonomy is unusual in that very few postcranials are known, and virtually all specimens are isolated skulls found in eolian sands and silts. Leptauchenia was restricted to the High Plains and western Montana during the Whitneyan and Arikareean, but is unknown from the similar-looking volcaniclastic deposits in central Oregon, California, and is also absent from the Gulf Coast of Florida or Texas at that time (despite the abundance of other non-leptaucheniine oreodonts in all these deposits).