Despite remarkable progress in large language models, Urdu-a language spoken by over 230 million people-remains critically underrepresented in modern NLP systems. Existing multilingual models demonstrate poor performance on Urdu-specific tasks, struggling with the language's complex morphology, right-to-left Nastaliq script, and rich literary traditions. Even the base LLaMA-3.1 8B-Instruct model shows limited capability in generating fluent, contextually appropriate Urdu text. We introduce Qalb, an Urdu language model developed through a two-stage approach: continued pre-training followed by supervised fine-tuning. Starting from LLaMA 3.1 8B, we perform continued pre-training on a dataset of 1.97 billion tokens. This corpus comprises 1.84 billion tokens of diverse Urdu text-spanning news archives, classical and contemporary literature, government documents, and social media-combined with 140 million tokens of English Wikipedia data to prevent catastrophic forgetting. We then fine-tune the resulting model on the Alif Urdu-instruct dataset. Through extensive evaluation on Urdu-specific benchmarks, Qalb demonstrates substantial improvements, achieving a weighted average score of 90.34 and outperforming the previous state-of-the-art Alif-1.0-Instruct model (87.1) by 3.24 points, while also surpassing the base LLaMA-3.1 8B-Instruct model by 44.64 points. Qalb achieves state-of-the-art performance with comprehensive evaluation across seven diverse tasks including Classification, Sentiment Analysis, and Reasoning. Our results demonstrate that continued pre-training on diverse, high-quality language data, combined with targeted instruction fine-tuning, effectively adapts foundation models to low-resource languages.
Conventional hard-bait lure prototyping relies on manual shaping, full-body additive manufacturing or early-stage injection moulding, each associated with limitations in geometric repeatability, development time or tooling cost. This paper evaluates a hybrid approach combining thermoformed PETG outer shells with additively manufactured internal frames to produce batches of geometrically consistent lure bodies with tuneable internal mass layouts. Across several educational development projects, the process enabled fast replication of outer form, systematic variation of ballast and harness configuration, and prototype assembly suitable for qualitative hydrodynamic observation. Compared with full additive manufacturing or manual crafting, the method reduced fabrication effort for multi-variant batches and delivered mould-like surface quality. Joining reliability of shell halves emerged as the dominant limitation, with elastic polyurethane adhesives outperforming brittle cyanoacrylate and poorly controllable low-energy fusion. The results position thermoforming as a methodologically valuable prototyping tool where external geometry is stable but internal behaviour requires iterative adjustment. Future work should address seam design, cage-shell tolerances and sealing repeatability to support quantitative hydrodynamic testing and assess whether the process has potential beyond prototyping applications.
Beading has been used in metal construction for decades to reinforce and stabilize thin sheets of metal. In aircraft, washing machine and car manufacturing, this allows for cost-effective, lightweight and material-saving designs to be realized. These indentations are embossed into thin metal sheets to increase their rigidity and stability, thereby preventing fluttering or deformation. The bending stiffness is significantly increased by reshaping the material. The increased stability allows thinner sheets to be used, which reduces the overall weight of the structures and components. Beading is often used on larger surfaces to prevent fluttering or vibrations and to ensure greater dimensional stability. The combination of two old production processes, beading and steam bending for wood is examined in this paper. The use of beads to reinforce thin wooden panels saves material, resources and weight, thereby making production more sustainable. The investigations carried out examined the possibilities of introducing beads into thin panels made from different types of wood. The temperature, water content, water vapour content, soaking time and pressing pressure were varied. In a first step, a test specimen was produced that serves as a mould for the surround. This shape was pressed into the thin wooden panels when varying the processing parameters shown above. In a next step, the indentation depths achieved were measured. The deflection of the thin wooden panels was then measured under different loads and compared with the calculated results.
