Rev Owusu Bempah Pledges ¢5000 To Psalm Adjetefio For His Heart Issues
by BB JonesReverend Owusu Bempah has donated an of ¢5000 to the ailing Psalm Adjeteyfio who is currently battling a condition of the heart which demands surgery to correct it.
The Kumasi-based pastor heard the actor’s condition on Peace FM’s Entertainment Review program after which he pledged the amount.
It was announced that the money will be ready by Monday for it to be delivered to Psalm Adjetefio.
The actor had previously disclosed his heart cannot pump efficiently enough for blood to circulate oxygen-rich blood throughout the body.
Mr Adjeteyfio claimed for about one and a half year now, the actor said he has taken more than 5000 different drugs.


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Amy McCormick, corporate affairs manager for Kroger, said in an email the Athens store was reorganized to integrate Nature’s Market products through the store and expand its variety to customers.
Store resets happen periodically, Jayla Sanford, a courtesy clerk cashier and senior studying nutrition, said.
Despite the resets being part of a regular procedural process for Kroger, it’s still a frustrating encounter for customers when it first happens.
Whenever they do it, everybody gets all upset,” Terry Smith, an Athens resident who has been shopping at Kroger since 1986, said. “But then, in three years when they do it again, everybody is mad because the way that they're used to is no longer the way it is, even though that's the way that they complained about two years before. It's just human nature.”
Unlike a store reset during any other year, the most recent store reset occurred during the COVID-19 pandemic with customers who simply wanted to get in and get out.
“This time, it was a lot different because we're in the middle of a pandemic,” Smith said. “So, here, they do a reset during this time so that when you go shopping, you end up going up and down aisles searching for stuff. They don't enforce the mask policy so, a lot of times, you're in an aisle with a couple of people standing around looking for stuff, and they're not wearing masks.”
Shannon Arnett, an Athens resident and a mom, said she felt an extra level of anxiety when shopping for groceries during the rearrangement process.
“As a newer mom who has taken this pandemic very seriously, the only time I go to Kroger is at 6 or 6:30 in the morning once a month to get our WIC qualified foods (WIC cannot be used with grocery pickup),” Arnett said in a message. “When I went in for my monthly trip last month, I nearly broke down in tears.”
Arnett said it does not seem like Kroger has a special time for customers who are at a higher risk of getting sick with COVID-19, and people are not wearing masks in the store.
“I try to get in and out as quick as possible, I (used) to know where everything I needed was, [and] I didn’t get half the stuff I usually do. And it’s the absolute worst time to force their shoppers to be indoors for a longer period of time during a huge spike in the pandemic, and not enforcing masks. It’s infuriating!” -Shannon Arnett, Athens resident and mom
When it comes to enforcing mask wearing, Sanford said she was not instructed to do so but is sympathetic to frustrations customers have.
“'I’ve never been in a position where I need to tell someone to put a mask on because I've been told by my superiors it is not my job,” Sanford said. “That also just creates a whole other direction and conversation with the customer, which is usually an argument.”
Despite this, Sanford is sympathetic to the frustrations customers have.
“I can see why that would be very annoying and frustrating that people do not comply, especially considering if you're in a store for 30 minutes to an hour, and then you have workers who have to wear their masks for eight plus hours,” Sanford said.
Grayson Schultz, an Athens resident, is immunocompromised and felt he was not able to successfully limit possible exposures to COVID-19 due to the layout change. Schultz also expressed frustration about what the Kroger brand is doing to protect its customers.
Because he is immunocompromised, Schultz tries to limit the amount of time he spends in Kroger.
 That's something that in the last several months of living here I have been able to figure out,” Schultz said. “Walking into the store the other day … I went for groceries last week, and seeing the entire layout change essentially made it a lot more difficult to be able to do that.”
Schultz echoed Arnett’s concern over the lack of mask-wearing and mask enforcement.
“I think even in the pandemic, if Kroger was actually enforcing masking rules or even with their staff, then it would be less irksome to walk in and see the layout change because I wouldn't necessarily feel as worried about spending more time in the store.” -Grayson Schultz, Athens resident
Others had issues with how specific foods were distributed. Angela Myers, an Athens resident, is unhappy with the way the organic, vegetarian and vegan options were organized throughout the store along with the lack of mask enforcement.
“The distribution of organic, vegetarian and vegan choices throughout the store are an unwelcome change for me,” Myers said in a message. “Along with Kroger’s unwillingness to enforce the city mask mandate (which makes me want to spend less time inside anyway) I have decided to spend more of my money at Kindred.”
Sue Morrow, an Athens resident, and Schultz said they would have liked a warning about the changes. Sanford said, unfortunately, a warning would not make much of a difference when things get swapped around.
“Honestly, a warning may have been nice for people who are not well with change, so then they can mentally prepare themselves to spend an extra 10 to 15 minutes in the store finding the couple items that they need,” Sanford said. “But, overall, I don't think it would have made a difference because, either way, you just have to adapt to the store changing. Corporate was going to do it anyway.”
As a result, some shoppers have made decisions to shop at other local grocers, such as Seaman’s Cardinal Supermarket, 305 W. Union St.
“Everybody's had enough change in their lives his last two years,” Morrow said. “But why add to that? Why add to the stress of that now?”


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- Protocol that defines that the entity that conforms it contains a sort descriptor
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public protocol NSSortDescriptorConvertible
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public protocol NSPredicateConvertible
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public protocol Context
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- Proxy protocol for store entities
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public protocol Entity {}


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Deep learning models are increasingly being used to make decisions in critical domains such as loan applications, crime risk-assessments and human resources. The decisions made by these data‐driven models can have wide‐ranging impacts and consequences on individuals and society as a whole. Recent studies, however, found that these models and datasets can be biased, resulting in discrimination based on factors such as race or gender.
In order to ensure that similar individuals are treated similarly in their paper Latent Space Smoothing for Individually Fair Representations, Peychev et al. introduce a novel representation learning method called LASSI, that is able to certify individual fairness on high-dimensional data. This is done by using recent advances in generative modelling and the scalable certification of deep models.
In this work, we aim to study the reproducibility of the work executed by the Peychev et al., and we attempt to verify the three main claims in their paper: (1) LASSI increases certified individual fairness, while keeping prediction accuracies high, (2) LASSI can handle various sensitive attributes and attribute vectors and (3) LASSI representations can achieve high certified individual fairness even when downstream tasks are not known. In addition, we aim to extend their research by performing additional experiments to validate the robustness of their claims and investigate the encountered outliers.
On this project page we present a brief summary of the project, including a short theoretical background, the results and the discussion. In the GitHub repository the code can be found, alongside a detailed description on how to reproduce the original and additional experiments.
Generative modelling (GLOW) - In order to ensure fairness, similar individuals that only differ in one or more sensitive attributes such as race or age, need to be treated similar by the LASSI model. To do this, we want to ignore these sensitive attributes in the classification process. This is achieved by using the generative model GLOW, which allows us to alter the input data in the latent space along a specific attribute vector, as shown in the figures above. When the different variations of these faces are treated similarly in the classification process, we can state that we have achieved certified individual fairness.
LASSI - By treating all the variations of an image generated by the GLOW model in the same manner, the LASSI model learns a fair representation of a specific task. It is ensured that the model learns to discriminate only based on features other than the sensitive attribute, which the GLOW model attempts to alter as little as possible. This adversarial training is performed by uniformly selecting points on the sensitive attribute vector with a maximum perturbation level, and train the model based on these images, to ensure fair treatment.
The training process involves balancing fairness, accuracy, and transferability to unknown tasks by finding the optimal value of different loss functions. Once the fair representation of the data is learned, it can be used to train a classifier for any downstream task. The method is compared to a fairness‐unaware (naive) baseline model for evaluation. For a more detailed explanation description, we would like to redirect you to our paper.
In the following sections we summarize the main results of the reproducibility studies. In our dedicated GitHub repository a detailed description is given of how the original experiments are reproduced and how our own additional experiments can be executed.
Below we demonstrate the results of three sensitive attributes on two tasks: smiling and wearing earings. In blue the accuracy and the fairness of the naive model is displayed, and in red those of the proposed LASSI model. Our results indicate that LASSI indeed increases certified individual fairness, while keeping prediction accuracies high.
The gifs are constructed by us and are examples of output generated by the GLOW model on a specific sensitive attribute. Keep in mind that the CelebA dataset consists of images of 64x64 pixels and the quality is therefore not very high.
In this section we present the results of the additional experiments executed to test the robustness of the claims made by the original authors. LASSI was tested on four additional sensitive attributes and tasks. The performance of LASSI shows that the model increases fairness for all attributes and tasks significantly, while keeping the prediction accuracy comparable to that of the baseline naive model.
When LASSI is trained on the 'attractive' task, using 'bald' or 'chubby' as sensitive attribute the model does not achieve a high fairness. We study these two outliers and find two possible explanations: (1) a high bias between certain tasks and sensitive attributes and (2) the possibly corrupted inputdata generated by the GLOW model for certain attributes. A detailed study into these outliers is reported in Appendix Section C.
Despite compromises made due to resource limitations, we find very similar results in all reproduced and additional experiments conducted. We find that: (1) LASSI increases certified fairness on (2) various sensitive attributes and attribute vectors, while keeping prediction accuracies high. The results also indicate that (3) LASSI achieves high certified individual fairness even when the downstream tasks are not known. In addition, the additional experiments conducted demonstrate that the claims are robust.