Shadows of quantum machine learning.

Quantum machine learning is often highlighted as one of the most promising practical applications for which quantum computers could provide a computational advantage. However, a major obstacle to the widespread use of quantum machine learning models in practice is that these models, even once trained, still require access to a quantum computer in order to be evaluated on new data. To solve this issue, we introduce a class of quantum models where quantum resources are only required during training, while the deployment of the trained model is classical.

Preoperative anxiety and postoperative pain associated with cataract surgery under local anesthesia.

Introduction: Although cataract surgery is a routine outpatient surgery, anxiety and pain remain two significant concerns seen in patients.

Aim: To describe preoperative anxiety and postoperative pain related to cataract surgery under local anesthesia and identify the factors determining their occurrence.

Methods: This is a cross-sectional, descriptive and analytical, study which included patients who underwent cataract surgery for the first eye in the ophthalmology department of Habib Bourguiba University Hospital in Sfax-Tunisia.

Post-traumatic fracture-dislocation of the humeral head with intrathoracic migration: A case report.

Introduction: Severe trauma is a frequent condition encountered in Emergency department (ED) in which vital prognosis can easily be engaged. This condition could be responsible for unusual injuries occurrence. Emergency physician must be aware of these situations where adequate management is urgently required.

Hyoid Bone Fracture Secondary to a Blunt Neck Trauma: A Report of 2 Cases.

Hyoid bone fracture unrelated to strangulation is a rare occurrence characterized by a subtle presentation. However, it may manifest as a fatal respiratory distress due to airway obstruction. We present 2 cases of hyoid bone fractures that occurred following a traffic accident in 2 male patients.

Reinforcement learning assisted recursive QAOA.

In recent years, variational quantum algorithms such as the Quantum Approximation Optimization Algorithm (QAOA) have gained popularity as they provide the hope of using NISQ devices to tackle hard combinatorial optimization problems. It is, however, known that at low depth, certain locality constraints of QAOA limit its performance. To go beyond these limitations, a non-local variant of QAOA, namely recursive QAOA (RQAOA), was proposed to improve the quality of approximate solutions.