Discerning a post-Covid future

No abstract available

Fathers: making known God’s faithfulness to their children (Is 38:19)

No abstract available

A time to choose what matters

This article takes up a challenge from Pope Francis and asks whether a harmonious and mutually reinforcing home-school-parish partnership could become a legacy of Covid-19. Stephen Reilly is Co-ordinator of Spiritual and Pastoral Formation at the University of Glasgow and a priest of the Diocese of Motherwell

Preparation and nucleophilic substitution of hexafluorophthalazine

Not availabl

Rediscovering and modernising the digital Old Minster of Winchester

The models and animations of the Old Minster, Winchester were remarkable in 1984–6 for producing the earliest animated tour of a virtual archaeological monument. Thought to be lost, thirty years on the original model files were rediscovered buried under layers of now unsupported code and recovered. This paper describes how the models were initially developed in the 1980s and then subsequently retrieved, restored and re-purposed in 2015. The original project is re-evaluated in the light of contemporary best practice. In modernising the digital Old Minster this virtual model has also been translated into a material one in the form of a 3D-print. This physical instantiation of the model challenges conventional understandings of, and blurs the boundary between, real and virtual heritage. We contend that left unaddressed this lack of clarity is set to radically disrupt current best practice in the discipline

Motor control of locomotor hindlimb posture in the American alligator (Alligator mississippiensis)

Crocodilians are unusual among quadrupedal tetrapods in their frequent use of a wide variety of hindlimb postures, ranging from sprawling to a more erect high walk. In this study, we use synchronized kinematic videos and electromyographic recordings to test how the activity patterns of hindlimb muscles in American alligators (Alligator mississippiensis Daudin) differ between sprawling and more upright postures. Previous force platform analyses suggested that upright posture in alligators would require greater activation by hindlimb extensors to counter increases in the flexor moments exerted about joints by the ground reaction force during upright stance. Consistent with these predictions, ankle extensors (gastrocnemius) and knee extensors (femorotibialis internus and iliotibialis 2) exhibit increases in signal intensity during the use of more upright stance. Bone loading data also predicted that activation patterns for hip adductors spanning the length of the femur would not differ between sprawling and more upright posture. Correspondingly, motor patterns of the adductor femoris were not altered as posture became more upright. However, the adductor puboischiofemoralis externus 3, which inserts far proximally on the femur, displays significant increases in burst intensity that could contribute to the greater femoral adduction that is integral to upright posture. In contrast to patterns in alligators, in mammals EMG burst intensity typically decreases during the use of upright posture. This difference in the motor control of limb posture between these taxa may be related to differences in the relative sizes of their feet. Alligator feet are large relative to the hindlimb and, as a result, the ground reaction force shifts farther from the limb joints during upright steps than in mammals, increasing flexor moments at joints and requiring alligator extensor muscles to exert greater forces to keep the limb in equilibrium. However, several alligator hindlimb muscles show no differences in motor pattern between sprawling and upright posture. The wide range of motor pattern modulations between different postures in alligators suggests considerable independence of neural control among the muscles of the alligator hindlimb

Robustness of Image-Based Malware Classification Models Trained with Generative Adversarial Networks

As malware continues to evolve, deep learning models are increasingly used for malware detection and classification, including image based classification. However, adversarial attacks can be used to perturb images so as to evade detection by these models. This study investigates the effectiveness of training deep learning models with Generative Adversarial Network-generated data to improve their robustness against such attacks. Two image conversion methods, byte plot and space-filling curves, were used to represent the malware samples, and a ResNet-50 architecture was used to train models on the image datasets. The models were then tested against a projected gradient descent attack. It was found that without GAN generated data, the models’ prediction performance drastically decreased from 93-95% to 4.5% accuracy. However, the addition of adversarial images to the training data almost doubled the accuracy of the models. This study highlights the potential benefits of incorporating GAN-generated data in the training of deep learning models to improve their robustness against adversarial attacks

Parish renewal in the image of Barnabas and Paul, sons of encouragement

In this article, a parish priest finds a rich template for the parishes of today in the example of Paul and Barnabas from the Acts of the Apostles

Catholic schools: Catholic high school liturgy: a “faithful presence within”

No abstract available

Comparing labor markets across recessions: a focus on the age composition of the population

Simply looking at unadjusted versions of traditional statistics may not be the best way to compare the state of the current economy to previous periods. When comparing recessions, it is important to account for demographic changes.Labor market ; Demography