Miracle-dz/UniFAR-FTUs huggingface dataset:
The Unmaking of the Cocoa Farmer: Analysis of Benefits and Challenges of third-party audited Certification Schemes for Cocoa Producers and Laborers in Ghana

Problem statement There are two important factors that raise the current demand for certified cocoa. On the one hand, it is the globally rising demand for cocoa, which also triggers the demand for certified cocoa (Hütz-Adams and Fountain 2012). Potts et al. (2010) report a growth rate for cocoa under a sustainability certification of 248% in five years between 2005 and 2010. On the other hand, chocolate companies worry for the long-term supply of cocoa, as productivity in many producing countries is low and the farms as well as the cocoa farmers are ageing (Barrientos 2011, KPMG 2012). In Ghana, which accounts for the second largest cocoa production in the world (ICCO 2012), a veritable competition for sourcing with certified cocoa has emerged. The market has doubled from 3% in 2009 to 6% in 2010 (KPMG 2012). Potts et al. 2014 estimate the cocoa production in Ghana under third-party audited certification already at 16% in 2012, when corrected for multiple certification. On the ground, this is visible in the labels such as Rainforest Alliance, UTZ Certified, Organic and Fairtrade competing to build up farmers’ groups, which are trained in sustainable cocoa production according to their respective standards. Some private sector actors rather promote own sustainability programs. But in contrast to the third-party audited certifications, their standards are not open to the public. As the marketing of certified products is based on the enhanced social, economic and ecological sustainability in the producing communities, questions are raised about the effective changes at the producer level. Therefore, many studies currently focus on the impact of certification schemes. Some authors observe that many of them rather describe outputs and outcomes than impacts on the level of broad economic development (CeVal 2012, Paschall 2013). According to Paschall (2013), many questions remain about how certification works in practice. Moreover, impact studies often refer to “farmers”, but the rural structure is more complex and consists of more categories, including shortand long-term laborers. It has also been observed that there is a lack of studies on hired work in the context of certification (Cramer et al. 2014, Vagneron and Roquigny 2010). In Ghana, a considerable amount of small-holder producers of cocoa rely on hired work during specific peak labor times. Although the certification standards refer to rights of laborers, not much is known about the amount and costs of hired work in cocoa production, and about the working conditions of laborers. In addition, as the certification bodies refer to “farmers”, the complexity of the sharing of monetary and non-monetary benefits from certification among all kinds of producers is sometimes overlooked.
Ethnic Networks and the Employment of Asylum Seekers: Evidence from Germany

Using novel registry data on the population of asylum seekers in Germany for the period from 2010 to 2016, and quasi-experimental variation induced by German allocation policies, we identify causal effects of the size and composition of local co-national networks on formal labor market access of asylum seekers. While the individual employment probability is not linked to network size, it increases with the number of employed local co-national asylum seekers and decreases with the number of non-employed network members, thereby underlining the central importance of network quality.
The Relationship Between Human And Moral Values Toward Business Blessing Of Muslim Customers Islamic Banking In Kendari City

The dynamics of growth and development of Islamic banking have found an ambivalence to the concept of sharia applied and on the other hand Muslim customers who utilize Islamic finance continue to grow over time. This phenomenon, interestingly analyzed about the motivation of a Muslim customer from aspects of humanity and moral values in relation to the blessings of the business obtained. The number of samples in this study were 110 people from 152 respondents who were determined by random sampling. Data were collected using questionnaires and interview guidelines, validity and reliability tests, transformation of ordinal data into intervals using MSI, linearity test and t test. Data is processed using IBM SPSS Statistics 23. The results of the study show that indicators of human values, moral values and business blessings are valid and reliable, the response of Muslim customers to the indicators of each variable is included in the good category. Humanity and moral values correlate with business blessings of 0.463 and 0.367, with the t test showing a positive and significant relationship.
Intrinsic and Extrinsic Risk Factors for Lateral Ankle Sprain: A Literature Review

Regardless of the field, data from 10 years ago is likely to be antiquated. The goal of this research note is to examine the current status of scholarships in women's Division I and Division II college golf by collecting data at the 2018 Women's Golf National Coaches Convention in Las Vegas Nevada. The survey, which was completed by 100 coaches, examined the current scholarship market for women's golf, as well as sought to dive deeper into the subject to help explore why the reasons scholarships might be going unclaimed.
Energy Efficiency and Improvement European countries: Data Envelopment Analysis approach

The challenge that all developed countries are facing is how to grow their economies in a sustainable way. To do this, energy efficiency is proposed as one of the keys solutions. In Europe, energy efficiency is one of the key elements; therefore; Europe the world's largest energy importer worldwide. Considering the core role of energy efficiency to Europe, the main objectives of this study are to measure energy efficiency and examine energy improvement of European countries during 2010-2017 by applying Data envelopment analysis (DEA) Slack-based measure model (SBM) and Malmquist Productivity Index (MPI). Findings of this study indicated France, Hungary, Greece, Italy, Netherland, Poland, Portugal, Switzerland and United Kingdom are efficient in terms of energy. Regarding energy improvement, only one country showed the improvement during observed period 2013-2017. This study provides important information of the current status of energy efficiency and improvement of European countries, which can help policymakers and strategy makers in deciding different energy strategies and policies.
Is Energy Consumption Responsible for Environmental Degradation in Ghana?

The quest to achieve greater expansion in the Ghanaian economy has culminated into consistent increase in economic activities which invariably entail ever-increasing energy consumption. Given the theoretical linkages between energy consumption and environmental degradation, then the continual increase in energy in the production, distribution and consumption of goods and services in Ghana could have stern implications on the quality of environment and in particular, on three major indicators of environmental degradation (namely, CO2 emissions, Biological Oxygen Density (BOD) and deforestation). Relying on recent annual dataset from the World Bank for the period 1980-2016 this study seeks to examine the environmental impact of energy consumption in Ghana within the standard Environmental Kuznets Curve (EKC) framework. Using the Autoregressive Distributed Lagged model estimation, the study reveals among other findings that energy consumption tends to increase air, water and land pollutions measured respectively by CO2 emissions, BOD and deforestation. This renders support to the assertion that the energy consumption could be blamed for a rise in environmental degradation in Ghana. Further, a robust EKC could not be established for any of the three environmental degradation indicators. This outcome is a major point of concern as the evidence does not support the view that Ghana can grow out of pollution problems with wealth within the context of energy consumption. Notwithstanding, FDI and the adoption of progressive technology are found to be necessary catalyst to enhance the quality of the environment by reducing CO2 emissions, water pollution as well as deforestation.
AssessIng the relAtIve ImportAnce of IntrAspecIfIc And InterspecIfIc InterActIons on the ecology of Anolis nebulosus lIzArds from An IslAnd vs . A mAInlAnd populAtIon

—Predation and competition are key ecological interactions that may drive island syndrome characteristics. However, the relative importance of these interactions in island and mainland environments is debated. We used Anolis nebulosus inhabiting a region lacking congeneric species on the coast of Jalisco, Mexico, as a model to elucidate the ecological role of intraspecific and interspecific competition for an insular population and a mainland population. We conducted surveys to determine densities of anole and other lizard species at both sites. We also carried out capture-mark-recapture of anoles to determine survival and frequency of caudal damage. In addition, we used video-recordings of focal anoles to determine rates of intraspecific and interspecific encounters and aggression, with higher rates suggesting greater competition, and determined direct predation when focal anoles were eaten. We found a significantly higher density of A. nebulosus on the island. Rates of intraspecific encounters and aggression were also significantly higher on the island. By comparison, interspecific encounters and aggression with other lizard species, as well as caudal autotomy, were higher on the mainland. We obtained few direct observations of predation, all of which were on the mainland, with no predation observed on the island, and survival was similar between populations. Although we were limited by the fact that we had only one island and one mainland population, our results on lizard density and encounter rates provide evidence for these populations lacking congeneric species that intraspecific competition is stronger on the island than on the mainland, whereas interspecific competition is stronger on the mainland.
Outbreak of highly pathogenic avian influenza subtype H5N8 in two multi-age chicken farms in Jos, Plateau State, Nigeria

An outbreak of highly pathogenic avian influenza (HPAI) subtype H5N8 in two multi-age chicken flocks in Jos, Plateau State, Nigeria, is described. Diagnosis was made using tissue samples from the affected farms that were submitted to the Regional Lab for Animal Influenza and other Transboundary Animal Diseases, National Veterinary Research Institute, Vom. Pullets with broilers of 9 and 4 weeks of age respectively, from farm A (fA) and broilers, 4 weeks of age from farm B (fB) were submitted from flocks experiencing a drastic increase in mortality. The February 2019 outbreak resulted in10 – 60 % and 60 % mortality on fA and fB respectively. Clinical signs included anorexia, depression, hock sitting and sudden onset of increasing mortality. Gross lesions included edema of the head with cyanosis of comb and wattle; swollen abdomen due to ascites; generalized congestion of visceral organs with frank blood in the abdomen; congested mesenteric vessels with haemorrhages in the mucosa of small and large intestines; congested and frothy lungs with severe hemorrhagic tracheitis among others. In view of the clinical and gross pathology, HPAI was considered as the tentative diagnosis. Diagnosis of HPAI subtype H5N8 was confirmed by reverse transcriptase polymerase chain reaction and viral isolation in embryonated chicken eggs. The current outbreak has shown the presence of HPAI H5N8 in the country different from the H5N1 subtype that was introduced since 2006 in Nigeria. The co-circulation of these two subtypes if the current wave of infection is left unchecked will have adverse effects on poultry production, international trade and human health. Hence, the need for the re-evaluation and strengthening of the Government control policy to save the poultry industry from perennial economic loses.Keywords: Broilers, Highly pathogenic avian influenza (HPAI H5N8), Jos, Nigeria, Outbreaks, Pullets
Reward Prediction Error and Declarative Memory

Learning based on reward prediction error (RPE) was originally proposed in the context of nondeclarative memory. We postulate that RPE may support declarative memory as well. Indeed, recent years have witnessed a number of independent empirical studies reporting effects of RPE on declarative memory. We provide a brief overview of these studies, identify emerging patterns, and discuss open issues such as the role of signed versus unsigned RPEs in declarative learning.
FORMULATION AND DETAILED CHARACTERIZATION OF VORICONAZOLE LOADED IN SITU GELS FOR OCULAR APPLICATION

Objective: This study was aimed to prepare, characterize and evaluate in situ gel formulation for a sustained ocular delivery of voriconazole. Material and Method: In situ gels were prepared with three different hydrophilic co-polymers: Poloxamer 188, 407 and 388. The formulations were characterized in terms of their clarity, pH, viscosity drug content uniformity and mechanical/rheological properties. Moreover, in vitro drug release and stabilitystudies were performed. Result and Discussion: The results showed that the optimized in situ gel formulation had desired in vitro properties and a good stability over the period of 3 months. Texture profile analysis presented that formulations offered suitable adhesive and mechanical properties. P2-V formulation exhibited pseudo-plastic flow and typical gel-type mechanical spectra (G′ > G″) at different frequecy values and at different temperatures. Moreover, all formulations showed a sustained drug release for 24 hours. In conclusion, voriconazole loaded in situ gel could be offered as an encouraging strategy as ocular systems for ocular infections treatment.
Spectroscopically Confirmed Lyα Emitters from Redshift 5 to 7 behind 10 Galaxy Cluster Lenses

We present 36 spectroscopically confirmed intrinsically UV-faint Lyα-emitting galaxies from follow-up observations with Keck/DEep Imaging Multi-Object Spectrograph of gravitationally lensed high-redshift candidates. Candidates were selected to be between 5 ≲ z ≲ 7 from photometric data using Hubble Space Telescope and Spitzer imaging surveys. We performed an integrated photometric redshift probability cut >1% between 5 < z < 7 to construct a sample of 198 high-redshift objects. Our sample spans intrinsic UV luminosities from a few L* down to 0.001L*. We identified 19 high-confidence detections and 17 likely detections of Lyα. We divided our sample into lower-redshift (z ∼ 5.5) and higher-redshift (z ∼ 6.5) bins and ran Monte Carlo trials, incorporating the strengths of the Lyα emission and the photometric redshifts of the nondetections. Considering only objects where Lyα could be detected at EW(Lyα) > 25 Å at 3σ at the fiducial depth of our survey, and only those galaxies with EW(Lyα) > 25 Å, and only objects with mAB < 26.8, we found the Lyα emitter (LAE) fraction to be flat or modestly increase from 0.26 ± 0.04 to 0.30 ± 0.04. These values are consistent with a rising LAE fraction with redshift out to z ∼ 6, but at z ∼ 6.5, there is some tension between our results and results from surveys at intrinsically brighter luminosities. We conclude that intrinsically fainter galaxies have Lyα emission, and there is a steep drop in the LAE fraction from our high-redshift sample at z ∼ 6.5 and from similar galaxies at z ∼ 7.5. This likely indicates we are witnessing the tail end of the epoch of reionization, as such a drop is not expected due to changes of intrinsic galaxy properties between these redshifts.
Lifting the dust veil from the globular cluster Palomar 2

This work employs high-quality {\em Hubble Space Telescope} ({\em HST}) Advanced Camera for Surveys (ACS) F606W and F814W photometry to correct for the differential reddening affecting the colour-magnitude diagram (CMD) of the poorly-studied globular cluster (GC) Palomar\,2. Differential reddening is taken into account by assuming that morphological differences among CMDs extracted across the field of view of Palomar\,2 correspond essentially to shifts (quantified in terms of $\delta E(B-V)$) along the reddening vector due to a non-uniform dust distribution. The average reddening difference over all partial CMDs is $\overline{\delta E(B-V)}=0.24\pm0.08$, with the highest reaching $\delta E(B-V) =0.52$. The corrected CMD displays well-defined and relatively narrow evolutionary sequences, especially for the evolved stars, i.e. the red-giant, horizontal and asymptotic giant branches (RGB, HB and AGB, respectively). The average width of the upper main sequence and RGB profiles of the corrected CMD corresponds to 56\% of the original one. Parameters measured on this CMD show that Palomar\,2 is $\approx13.25$\,Gyr old, has the mass $M\sim1.4\times10^5\,m_\odot$ stored in stars, is affected by the foreground $E(B-V)\approx0.93$, is located at $d_\odot\approx26$\,Kpc from the Sun, and is characterized by the global metallicity $Z/Zo\approx0.03$, which corresponds to the range $-1.9\leq [Fe/H] \leq-1.6$ (for $0.0\leq[\alpha/Fe]\leq+0.4$), quite consistent with other outer halo GCs. Additional parameters are the absolute magnitude $M_V\approx-7.8$, and the core and half-light radii $r_C\approx2.6$\,pc and $R_{HL}\approx4.7$\,pc, respectively.
On the turbulence driving mode of expanding H ii regions

We investigate the turbulence driving mode of ionizing radiation from massive stars on the surrounding interstellar medium (ISM). We run hydrodynamical simulations of a turbulent cloud impinged by a plane-parallel ionization front. We find that the ionizing radiation forms pillars of neutral gas reminiscent of those seen in observations. We quantify the driving mode of the turbulence in the neutral gas by calculating the driving parameter $b$, which is characterised by the relation $\sigma_s^2 = \ln({1+b^2\mathcal{M}^2})$ between the variance of the logarithmic density contrast $\sigma_s^2$ (where $s = \ln({\rho/\rho_0})$ with the gas density $\rho$ and its average $\rho_0$), and the turbulent Mach number $\mathcal{M}$. Previous works have shown that $b\sim1/3$ indicates solenoidal (divergence-free) driving and $b\sim1$ indicates compressive (curl-free) driving, with $b\sim1$ producing up to ten times higher star formation rates than $b\sim1/3$. The time variation of $b$ in our study allows us to infer that ionizing radiation is inherently a compressive turbulence driving source, with a time-averaged $b\sim 0.76 \pm 0.08$. We also investigate the value of $b$ of the pillars, where star formation is expected to occur, and find that the pillars are characterised by a natural mixture of both solenoidal and compressive turbulent modes ($b\sim0.4$) when they form, and later evolve into a more compressive turbulent state with $b\sim0.5$--$0.6$. A virial parameter analysis of the pillar regions supports this conclusion. This indicates that ionizing radiation from massive stars may be able to trigger star formation by producing predominately compressive turbulent gas in the pillars.
Deep Neural Networks Carve the Brain at its Joints

How an individual’s unique brain connectivity determines that individual’s cognition, behavior, and risk for pathology is a fundamental question in basic and clinical neuroscience. In seeking answers, many have turned to machine learning, with some noting the particular promise of deep neural networks in modelling complex non-linear functions. However, it is not clear that complex functions actually exist between brain connectivity and behavior, and thus if deep neural networks necessarily outperform simpler linear models, or if their results would be interpretable. Here we show that, across 52 subject measures of cognition and behavior, deep neural networks fit to each brain region’s connectivity outperform linear regression, particularly for the brain’s connector hubs—regions with diverse brain connectivity—whereas the two approaches perform similarly when fit to brain systems. Critically, averaging deep neural network predictions across brain regions results in the most accurate predictions, demonstrating the ability of deep neural networks to easily model the various functions that exists between regional brain connectivity and behavior, carving the brain at its joints. Finally, we shine light into the black box of deep neural networks using multislice network models. We determined that the relationship between connector hubs and behavior is best captured by modular deep neural networks. Our results demonstrate that both simple and complex relationships exist between brain connectivity and behavior, and that deep neural networks can fit both. Moreover, deep neural networks are particularly powerful when they are first fit to the various functions of a system independently and then combined. Finally, deep neural networks are interpretable when their architectures are structurally characterized using multislice network models.
Distributed Task Replication for Vehicular Edge Computing: Performance Analysis and Learning-Based Algorithm

In a vehicular edge computing (VEC) system, vehicles can share their surplus computation resources to provide cloud computing services. The highly dynamic environment of the vehicular network makes it challenging to guarantee the task offloading delay. To this end, we introduce task replication to the VEC system, where the replicas of a task are offloaded to multiple vehicles at the same time, and the task is completed upon the first response among replicas. First, the impact of the number of task replicas on the offloading delay is characterized, and the optimal number of task replicas is approximated in closed-form. Based on the analytical result, we design a learning-based task replication algorithm (LTRA) with combinatorial multi-armed bandit theory, which works in a distributed manner and can automatically adapt itself to the dynamics of the VEC system. A realistic traffic scenario is used to evaluate the delay performance of the proposed algorithm. Results show that, under our simulation settings, LTRA with an optimized number of task replicas can reduce the average offloading delay by over 30% compared to the benchmark without task replication, and at the same time can improve the task completion ratio from 97% to 99.6%.
Imputer: Sequence Modelling via Imputation and Dynamic Programming

This paper presents the Imputer, a neural sequence model that generates output sequences iteratively via imputations. The Imputer is an iterative generative model, requiring only a constant number of generation steps independent of the number of input or output tokens. The Imputer can be trained to approximately marginalize over all possible alignments between the input and output sequences, and all possible generation orders. We present a tractable dynamic programming training algorithm, which yields a lower bound on the log marginal likelihood. When applied to end-to-end speech recognition, the Imputer outperforms prior non-autoregressive models and achieves competitive results to autoregressive models. On LibriSpeech test-other, the Imputer achieves 11.1 WER, outperforming CTC at 13.0 WER and seq2seq at 12.5 WER.
Ancestral lines under recombination

Solving the recombination equation has been a long-standing challenge of \emph{deterministic} population genetics. We review recent progress obtained by introducing ancestral processes, as traditionally used in the context of \emph{stochastic} models of population genetics, into the deterministic setting. With the help of an ancestral partitioning process, which is obtained by letting population size tend to infinity (without rescaling parameters or time) in an ancestral recombination graph, we obtain the solution to the recombination equation in a transparent form.