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https://www.teachengineering.org/activities/view/umo-2941-bright-ideas-light-reflection-microbits-activity Students engage in a hands-on exploration of vision and light reflection by creating a program that simulates light intensity and how our eyes perceive images using the LED display on the micro: bits and its radio feature. After creating a model of an eye, students simulate the light intensity and reflection processes before they work in groups to identify and solve real-world problems related to sunlight and vision. Students utilize the engineering design process to research, imagine, plan, create, test, and improve their solutions, such as reminders for when to wear sunglasses or sunscreen, displays of current sunlight intensity, or determining which materials block light/UV rays. This engineering curriculum aligns to Next Generation Science Standards (NGSS). 

https://www.teachengineering.org/activities/view/umo-2942-mindful-messages-communication-solutions-activity Students explore how the brain enables communication through spoken and written language and how communication is essential for solving problems. Working in groups, students define a problem related to communication, design a solution using a micro:bit, build a prototype, and then test their designs. Possible communication challenges they might tackle are hearing loss, language barriers, or noisy environments. Students follow specific criteria and constraints as they design and build their prototype. After testing their designs and prototypes, students improve their designs as needed. To wrap up, students exchange prototypes with other groups and test each other’s solutions. This engineering curriculum aligns to Next Generation Science Standards (NGSS). 

The investigation of the coordination chemistry of rare-earth metal complexes with cyanide ligands led to the isolation and crystallographic characterization of the Ln III cyanotriphenylborate complexes dichlorido(cyanotriphenylborato-κ N )tetrakis(tetrahydrofuran-κ O )lanthanide(III), [ Ln Cl 2 (C 19 H 15 BN)(C 4 H 8 O) 4 ] [lanthanide ( Ln ) = dysprosium (Dy) and yttrium Y)] from reactions of LnCl 3 , KCN, and NaBPh 4 . Attempts to independently synthesize the tetraethylammonium salt of (NCBPh 3 ) − from BPh 3 and [NEt 4 ][CN] in THF yielded crystals of the phenyl-substituted cyclic borate, tetraethylazanium 2,2,4,6-tetraphenyl-1,3,5,2λ 4 ,4,6-trioxatriborinan-2-ide, C 8 H 20 N + ·C 24 H 20 B 3 O 3 − or [NEt 4 ][B 3 (μ-O) 3 (C 6 H 5 ) 4 ]. The mechanochemical reaction of BPh 3 and [NEt 4 ][CN] without solvent produced crystals of tetraethylazanium cyanodiphenyl-λ 4 -boranyl diphenylborinate, C 8 H 20 N + ·C 25 H 20 B 2 NO − or [NEt 4 ][NCBPh 2 (μ-O)BPh 2 ]. Reaction of BPh 3 and KCN in THF in the presence of 2.2.2-cryptand (crypt) led to a crystal of bis[(2.2.2-cryptand)potassium] 2,2,4,6-tetraphenyl-1,3,5,2λ 4 ,4,6-trioxatriborinan-2-ide cyanomethyldiphenylborate tetrahydrofuran disolvate, 2C 18 H 36 KN 2 O 6 + ·C 24 H 20 B 3 O 3 − ·C 14 H 13 BN − ·2C 4 H 8 O or [K(crypt)] 2 [B 3 (μ-O) 3 (C 6 H 5 ) 4 ][NCBPh 2 Me]·2THF. The [NCBPh 2 (μ-O)BPh 2 ] 1− and (NCBPh 2 Me) 1− anions have not been structurally characterized previously. The structure of 1-Y was refined as a two-component twin with occupancy factors 0.513 (1) and 0.487 (1). In 4 , one solvent molecule was disordered and included using multiple components with partial site-occupancy factors. 

The gap between chronological age (CA) and biological brain age, as estimated from magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging deviate from their typical trajectories. MRI-derived brain age (BA) estimates are often obtained using deep learning models that may perform relatively poorly on new data or that lack neuroanatomic interpretability. This study introduces a convolutional neural network (CNN) to estimate BA after training on the MRIs of 4,681 cognitively normal (CN) participants and testing on 1,170 CN participants from an independent sample. BA estimation errors are notably lower than those of previous studies. At both individual and cohort levels, the CNN provides detailed anatomic maps of brain aging patterns that reveal sex dimorphisms and neurocognitive trajectories in adults with mild cognitive impairment (MCI, N  = 351) and Alzheimer’s disease (AD, N  = 359). In individuals with MCI (54% of whom were diagnosed with dementia within 10.9 y from MRI acquisition), BA is significantly better than CA in capturing dementia symptom severity, functional disability, and executive function. Profiles of sex dimorphism and lateralization in brain aging also map onto patterns of neuroanatomic change that reflect cognitive decline. Significant associations between BA and neurocognitive measures suggest that the proposed framework can map, systematically, the relationship between aging-related neuroanatomy changes in CN individuals and in participants with MCI or AD. Early identification of such neuroanatomy changes can help to screen individuals according to their AD risk.