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The design and development of supported catalysts for the oxygen evolution reaction (OER) is a promising pathway to reducing iridium loading in proton exchange membrane water electrolysers. However, supported catalysts often suffer from poor activity and durability, particularly when deployed in membrane electrode assemblies. In this work, we deploy iridium coated hollow titanium dioxide particles as OER catalysts to achieve higher Ir mass activities than the leading commercial catalysts. Critically, we demonstrate state-of-the-art durabilities for supported iridium catalysts when compared against the previously reported values for analogous device architectures, operating conditions and accelerated stress test profiles. Through extensive materials characterisations alongside rotating disk electrode measurements, we investigate the role of conductivity, morphology, oxidation state and crystallinity on the OER electrochemical performance. Our work highlights a new supported catalyst design that unlocks high-performance OER activity and durability in commercially relevant testing configurations.

We present Gecko, a compact and versatile text embedding model. Gecko achieves strong retrieval performance by leveraging a key idea: distilling knowledge from large language models (LLMs) into a retriever. Our two-step distillation process begins with generating diverse, synthetic paired data using an LLM. Next, we further refine the data quality by retrieving a set of candidate passages for each query, and relabeling the positive and hard negative passages using the same LLM. The effectiveness of our approach is demonstrated by the compactness of the Gecko. On the Massive Text Embedding Benchmark (MTEB), Gecko with 256 embedding dimensions outperforms all existing entries with 768 embedding size. Gecko with 768 embedding dimensions achieves an average score of 66.31, competing with 7x larger models and 5x higher dimensional embeddings., Comment: 18 pages

Model observers are computational tools to evaluate and optimize task-based medical image quality. Linear model observers, such as the Channelized Hotelling Observer (CHO), predict human accuracy in detection tasks with a few possible signal locations in clinical phantoms or real anatomic backgrounds. In recent years, Convolutional Neural Networks (CNNs) have been proposed as a new type of model observer. What is not well understood is what CNNs add over the more common linear model observer approaches. We compare the CHO and CNN detection accuracy to the radiologist's accuracy in searching for two types of signals (mass and microcalcification) embedded in 2D/3D breast tomosynthesis phantoms (DBT). We show that the CHO model's accuracy is comparable to the CNN's performance for a location-known-exactly detection task. However, for the search task with 2D/3D DBT phantoms, the CHO's detection accuracy was significantly lower than the CNN accuracy. A comparison to the radiologist's accuracy showed that the CNN but not the CHO could match or exceed the radiologist's accuracy in the 2D microcalcification and 3D mass search conditions. An analysis of the eye position showed that radiologists fixated more often and longer at the locations corresponding to CNN false positives. Most CHO false positives were the phantom's normal anatomy and were not fixated by radiologists. In conclusion, we show that CNNs can be used as an anthropomorphic model observer for the search task for which traditional linear model observers fail due to their inability to discount false positives arising from the anatomical backgrounds., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

This research addresses the pressing challenge of enhancing processing times and detection capabilities in Unmanned Aerial Vehicle (UAV)/drone imagery for global wildfire detection, despite limited datasets. Proposing a Segmented Neural Network (SegNet) selection approach, we focus on reducing feature maps to boost both time resolution and accuracy significantly advancing processing speeds and accuracy in real-time wildfire detection. This paper contributes to increased processing speeds enabling real-time detection capabilities for wildfire, increased detection accuracy of wildfire, and improved detection capabilities of early wildfire, through proposing a new direction for image classification of amorphous objects like fire, water, smoke, etc. Employing Convolutional Neural Networks (CNNs) for image classification, emphasizing on the reduction of irrelevant features vital for deep learning processes, especially in live feed data for fire detection. Amidst the complexity of live feed data in fire detection, our study emphasizes on image feed, highlighting the urgency to enhance real-time processing. Our proposed algorithm combats feature overload through segmentation, addressing challenges arising from diverse features like objects, colors, and textures. Notably, a delicate balance of feature map size and dataset adequacy is pivotal. Several research papers use smaller image sizes, compromising feature richness which necessitating a new approach. We illuminate the critical role of pixel density in retaining essential details, especially for early wildfire detection. By carefully selecting number of filters during training, we underscore the significance of higher pixel density for proper feature selection. The proposed SegNet approach is rigorously evaluated using real-world dataset obtained by a drone flight and compared to state-of-the-art literature.

Purpose: Radiologists are tasked with visually scrutinizing large amounts of data produced by 3D volumetric imaging modalities. Small signals can go unnoticed during the 3d search because they are hard to detect in the visual periphery. Recent advances in machine learning and computer vision have led to effective computer-aided detection (CADe) support systems with the potential to mitigate perceptual errors. Approach: Sixteen non-expert observers searched through digital breast tomosynthesis (DBT) phantoms and single cross-sectional slices of the DBT phantoms. The 3D/2D searches occurred with and without a convolutional neural network (CNN)-based CADe support system. The model provided observers with bounding boxes superimposed on the image stimuli while they looked for a small microcalcification signal and a large mass signal. Eye gaze positions were recorded and correlated with changes in the area under the ROC curve (AUC). Results: The CNN-CADe improved the 3D search for the small microcalcification signal (delta AUC = 0.098, p = 0.0002) and the 2D search for the large mass signal (delta AUC = 0.076, p = 0.002). The CNN-CADe benefit in 3D for the small signal was markedly greater than in 2D (delta delta AUC = 0.066, p = 0.035). Analysis of individual differences suggests that those who explored the least with eye movements benefited the most from the CNN-CADe (r = -0.528, p = 0.036). However, for the large signal, the 2D benefit was not significantly greater than the 3D benefit (delta delta AUC = 0.033, p = 0.133). Conclusion: The CNN-CADe brings unique performance benefits to the 3D (vs. 2D) search of small signals by reducing errors caused by the under-exploration of the volumetric data.

Many animals and humans process the visual field with varying spatial resolution (foveated vision) and use peripheral processing to make intelligent eye movements and point the fovea to acquire high-resolution information about objects of interest. A foveated architecture results in computationally efficient rapid scene exploration and can result in energy savings for computer vision. A foveated model can also serve as a proxy to identify circumstances in which humans might make an error and as a tool to understand human vision. Foveated architectures have been implemented into previous computer vision models. However, they have not been explored with the latest computer vision architecture transformer networks, which result in better robustness against adversarial attacks and better representation of spatial relationships across the entire image. We propose foveated computational module for object classification (FoveaTer) and object detection (FST) integrated into the vision transformer architecture. We evaluate FoveaTer’s computational savings and gains in robustness to adversarial attacks relative to a full-resolution model. We used the self-attention weights to optimize the guidance of the model eye movements. We have also investigated using FoveaTer to predict the various behavioral effects of humans. We performed a psychophysics experiment for the scene categorization task and predicted the human categorization performance using the FoveaTer model. Using two additional psychophysics experiments, a forced-fixation mouse recognition experiment to detect mouse in the visual periphery and a visual search experiment to detect mouse using a limited number of fixations, We have also evaluated how the FST model uses contextual information to guide eye movements like humans. In addition, we trained anthropomorphic CNN models to detect simulated tumors in simulated 3D Digital Breast Tomosynthesis phantoms and compare their performance and errors against that of radiolo

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at . G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at . G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at . G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.16177. G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at . G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.

Motility of pathogenic protozoa depends on flagella (synonymous with cilia) with axonemes containing nine doublet microtubules (DMTs) and two singlet microtubules. Microtubule inner proteins (MIPs) within DMTs influence axoneme stability and motility and provide lineage-specific adaptations, but individual MIP functions and assembly mechanisms are mostly unknown. Here, we show in the sleeping sickness parasite Trypanosoma brucei, that FAP106, a conserved MIP at the DMT inner junction, is required for trypanosome motility and functions as a critical interaction hub, directing assembly of several conserved and lineage-specific MIPs. We use comparative cryogenic electron tomography (cryoET) and quantitative proteomics to identify MIP candidates. Using RNAi knockdown together with fitting of AlphaFold models into cryoET maps, we demonstrate that one of these candidates, MC8, is a trypanosome-specific MIP required for parasite motility. Our work advances understanding of MIP assembly mechanisms and identifies lineage-specific motility proteins that are attractive targets to consider for therapeutic intervention.

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at . G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.

TU Tau (= HD 38218 = HIP 27135) is a binary system consisting of a C-N carbon star primary and an A-type secondary. We report on new photometry and spectroscopy which tracked the recent disappearance of the A-star secondary. The dimming of the A-star was gradual and irregular, with one or more brief brightenings, implying the presence of nonhomogeneities in the carbon star outflow. We also present evidence that the A-star is actively accreting s-process enriched material from the carbon star and suggest that it will therefore eventually evolve into a Barium giant. This is an important system as well because the A-type star can serve as a probe of the outer atmosphere of the carbon star., Comment: 9 pages, 9 figures, 4 tables, a number of amateur observatories made significant contributions to this research. Paper accepted for publication in The Astronomical Journal

Quadruped robots are currently used in industrial robotics as mechanical aid to automate several routine tasks. However, presently, the usage of such a robot in a domestic setting is still very much a part of the research. This paper discusses the understanding and virtual simulation of such a robot capable of detecting and understanding human emotions, generating its gait, and responding via sounds and expression on a screen. To this end, we use a combination of reinforcement learning and software engineering concepts to simulate a quadruped robot that can understand emotions, navigate through various terrains and detect sound sources, and respond to emotions using audio-visual feedback. This paper aims to establish the framework of simulating a quadruped robot that is emotionally intelligent and can primarily respond to audio-visual stimuli using motor or audio response. The emotion detection from the speech was not as performant as ERANNs or Zeta Policy learning, still managing an accuracy of 63.5%. The video emotion detection system produced results that are almost at par with the state of the art, with an accuracy of 99.66%. Due to its "on-policy" learning process, the PPO algorithm was extremely rapid to learn, allowing the simulated dog to demonstrate a remarkably seamless gait across the different cadences and variations. This enabled the quadruped robot to respond to generated stimuli, allowing us to conclude that it functions as predicted and satisfies the aim of this work.

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.16177. G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.

Polyunsaturated fatty acids (PUFAs) are essential FAs for human health. Cytochrome P450 oxygenates PUFAs to produce anti-inflammatory and pain-resolving epoxy fatty acids (EpFAs) and other oxylipins whose epoxide ring is opened by the soluble epoxide hydrolase (sEH/Ephx2), resulting in the formation of toxic and pro-inflammatory vicinal diols (dihydroxy-FAs). Pharmacological inhibition of sEH is a promising strategy for the treatment of pain, inflammation, cardiovascular diseases, and other conditions. We tested the efficacy of a potent, selective sEH inhibitor, 1-trifluoromethoxyphenyl-3-(1-propionylpiperidin-4-yl) urea (TPPU), in an animal model of multiple sclerosis (MS), experimental autoimmune encephalomyelitis (EAE). Prophylactic TPPU treatment significantly ameliorated EAE without affecting circulating white blood cell counts. TPPU accumulated in the spinal cords (SCs), which was correlated with plasma TPPU concentration. Targeted lipidomics in EAE SCs and plasma identified that TPPU blocked production of dihydroxy-FAs efficiently and increased some EpFA species including 12(13)-epoxy-octadecenoic acid (12(13)-EpOME) and 17(18)-epoxy-eicosatrienoic acid (17(18)-EpETE). TPPU did not alter levels of cyclooxygenase (COX-1/2) metabolites, while it increased 12-hydroxyeicosatetraenoic acid (12-HETE) and other 12/15-lipoxygenase metabolites. These analytical results are consistent with sEH inhibitors that reduce neuroinflammation and accelerate anti-inflammatory responses, providing the possibility that sEH inhibitors could be used as a disease modifying therapy, as well as for MS-associated pain relief.

Objective: MCT1-4 are involved in several diseases, particularly in cancer. [18F]FACH has recently been developed as a novel MCT-targeting imaging agent (1), which could be used for monitoring MCT-based treatment approaches. With the aim to develop a similar potent radiotracer with higher brain permeability for future brain tumor studies, we designed structurally modified analogs of FACH possessing increased lipophilicity. Methods: Two analogs of FACH (I and II) were synthesized by introduction of a 2-fluoropyridinyl moiety via Buchwald-Hartwig cross coupling reaction. Inhibition of MCT1 was measured by [14C]lactate uptake assay using rat brain endothelial cells and analog I with higher inhibition was selected to synthesize corresponding precursor used for radiofluorination by aromatic nucleophilic substitution. LogD7.4 of [18F]I was experimentally determined in the n-octanol-PBS system. In vitro autoradiography and dynamic PET studies of [18F]I were performed in CD-1 mice. Results: The analogs I and II showed a moderate MCT1 inhibition with IC50 values of 118 and 274 nM, respectively. [18F]I was obtained with radiochemical yields of 73±12% (n=4, non-isolated) and a high radiochemical purity of > 98%. A logD7.4 value of 0.816 was achieved for [18F]I, which was 2-fold higher than that for [18F]FACH. By in vitro autoradiography in cryosections of the mouse kidney, nearly complete displacement of [18F]I by 10-5 M CHC-Na was observed. In vivo, similar to [18F]FACH, a low uptake of [18F]I in the brain without significant washout was found with an almost constant SUV of 0.15 between 15 and 60 min p.i. Conclusion: Despite a higher lipophilicity of [18F]I compared to [18F]FACH, the brain uptake of [18F]I was in a similar low range. However, the high and specific uptake of the new radiotracer in the kidneys suggests suitability of [18F]I for detecting MCTs’ expression in vivo. References: (1) Sadeghzadeh M, et al. J Label Compd Radiopharm.2019; 62: 411-424.

Objective: MCT1-4 are involved in several diseases, particularly in cancer. [18F]FACH has recently been developed as a novel MCT-targeting imaging agent (1), which could be used for monitoring MCT-based treatment approaches. With the aim to develop a similar potent radiotracer with higher brain permeability for future brain tumor studies, we designed structurally modified analogs of FACH possessing increased lipophilicity. Methods: Two analogs of FACH (I and II) were synthesized by introduction of a 2-fluoropyridinyl moiety via Buchwald-Hartwig cross coupling reaction. Inhibition of MCT1 was measured by [14C]lactate uptake assay using rat brain endothelial cells and analog I with higher inhibition was selected to synthesize corresponding precursor used for radiofluorination by aromatic nucleophilic substitution. LogD7.4 of [18F]I was experimentally determined in the n-octanol-PBS system. In vitro autoradiography and dynamic PET studies of [18F]I were performed in CD-1 mice. Results: The analogs I and II showed a moderate MCT1 inhibition with IC50 values of 118 and 274 nM, respectively. [18F]I was obtained with radiochemical yields of 73±12% (n=4, non-isolated) and a high radiochemical purity of > 98%. A logD7.4 value of 0.816 was achieved for [18F]I, which was 2-fold higher than that for [18F]FACH. By in vitro autoradiography in cryosections of the mouse kidney, nearly complete displacement of [18F]I by 10-5 M CHC-Na was observed. In vivo, similar to [18F]FACH, a low uptake of [18F]I in the brain without significant washout was found with an almost constant SUV of 0.15 between 15 and 60 min p.i. Conclusion: Despite a higher lipophilicity of [18F]I compared to [18F]FACH, the brain uptake of [18F]I was in a similar low range. However, the high and specific uptake of the new radiotracer in the kidneys suggests suitability of [18F]I for detecting MCTs’ expression in vivo. References: (1) Sadeghzadeh M, et al. J Label Compd Radiopharm.2019; 62: 411-424.

As human beings, we come across situations where our reasons, experience, or guidance from adults can be contradictory. A teacher also experiences these contradictory situations in the educational setting. In such cases, what should be the teacher's philosophy is my main idea or research question of this paper. To address this question, I started my exploration with the Philosophy of the Teacher by Nigel Tubbs, which states that contradictions exist as part of the teaching process and narrates the experience of the teacher as master, servant, and/or spiritual teacher. As part of this reading, I understood that the central contradiction is how the teacher can communicate the truth to the student in an educational practice where freedom for the child is given importance. On the other hand, Sankara from Indian Advaita Vedanta Philosophy states that teaching is defect free with no contradictions in teaching Brahma Vidya (Inquiry of Brahman). This view of Sankara made me explore more of Advaita Vedanta philosophy. In this exploration process, I learned from Sankara's Dakshinamoorthy stotram that interpretation of truth or reality as Brahman and further to the question why teaching is free from contradictions, I explore Brahma Sutra Bhashyam with the aid of Ahdyasa Bhashyam (error analysis) of Sankara. Adhyasa Bhashyam employed the method of superimposition and elimination (neti-neti or negation) along with methods like questioning, illustration of examples, and story.

A heterogenous Palladium anchored Resorcinol-formaldehyde-hyperbranched PEI mesoporous catalyst, made by one-pot synthesis, was used successfully for in situ Suzuki-Miyaura cross coupling synthesis of anticancer prodrug PP-121 from iodoprazole and boronic ester precursors. The mesoporous catalyst with the non-cytotoxic precursors were tested in 2D in vitro model with excellent cytocompatibility and a strong suppression of PC3 cancer cell proliferation, underscored by 50% reduction in PC3 cells viability and 55% reduction in cell metabolism activity and an enhanced rate of early and late apoptosis in flow cytometry, that was induced only by successful in situ pro drug PP121 synthesis from the precursors. The 3D gelatin methacrylate hydrogel encapsulated in vitro cell models underscored the results with a 52% reduction in cell metabolism and underscored apoptosis of PC3 cells when the Pd anchored catalyst was combined with the precursors. In situ application of Suzuki-Miyaura cross coupling of non-cytotoxic precursors to cancer drug, along with their successful encapsulation in an injectable hydrogel could be applied for tumor point drug delivery strategies that can circumvent deleterious side effects and poor bioavailability chemotherapy routes with concomitant enhanced efficacy.

As human beings, we come across situations where our reasons, experience, or guidance from adults can be contradictory. A teacher also experiences these contradictory situations in the educational setting. In such cases, what should be the teacher's philosophy is my main idea or research question of this paper. To address this question, I started my exploration with the Philosophy of the Teacher by Nigel Tubbs, which states that contradictions exist as part of the teaching process and narrates the experience of the teacher as master, servant, and/or spiritual teacher. As part of this reading, I understood that the central contradiction is how the teacher can communicate the truth to the student in an educational practice where freedom for the child is given importance. On the other hand, Sankara from Indian Advaita Vedanta Philosophy states that teaching is defect free with no contradictions in teaching Brahma Vidya (Inquiry of Brahman). This view of Sankara made me explore more of Advaita Vedanta philosophy. In this exploration process, I learned from Sankara's Dakshinamoorthy stotram that interpretation of truth or reality as Brahman and further to the question why teaching is free from contradictions, I explore Brahma Sutra Bhashyam with the aid of Ahdyasa Bhashyam (error analysis) of Sankara. Adhyasa Bhashyam employed the method of superimposition and elimination (neti-neti or negation) along with methods like questioning, illustration of examples, and story.

In recent years, large pretrained models have been used in dialogue systems to improve successful task completion rates. However, lack of reasoning capabilities of dialogue platforms make it difficult to provide relevant and fluent responses, unless the designers of a conversational experience spend a considerable amount of time implementing these capabilities in external rule based modules. In this work, we propose a novel method to fine-tune pretrained transformer models such as Roberta and T5. to reason over a set of facts in a given dialogue context. Our method includes a synthetic data generation mechanism which helps the model learn logical relations, such as comparison between list of numerical values, inverse relations (and negation), inclusion and exclusion for categorical attributes, and application of a combination of attributes over both numerical and categorical values, and spoken form for numerical values, without need for additional training dataset. We show that the transformer based model can perform logical reasoning to answer questions when the dialogue context contains all the required information, otherwise it is able to extract appropriate constraints to pass to downstream components (e.g. a knowledge base) when partial information is available. We observe that transformer based models such as UnifiedQA-T5 can be fine-tuned to perform logical reasoning (such as numerical and categorical attributes' comparison) over attributes that been seen in training time (e.g., accuracy of 90\%+ for comparison of smaller than $k_{\max}$=5 values over heldout test dataset).

Sustainable rural drinking water is a widespread aim in India, and globally, from the household to district, state, and national scales. Sustainability issues in the rural drinking water sector range from increasing water demand to declining groundwater levels, premature deterioration of village schemes and services, inadequate revenues for operations and maintenance, weak capacity of water operators, frequently changing state and national policies, and destabilizing effects of climate change. This paper focuses on the special role of district-scale drinking water planning, which operates at the intersection between bottom-up water demand and top-down water programs. After surveying the challenges associated with bottom-up and top-down planning approaches, we present recent efforts to strengthen district and block drinking water planning in the state of Maharashtra. A combination of district interviews, institutional history, village surveys, GIS visualization, and planning workshops were used to advance district planning goals and methods. Results assess bottom-up processes of water demand; top-down water programs and finance; and intermediate-level planning at the district and block scales. Discussion focuses on potential improvements in district planning methods in Maharashtra.

Ribonucleotide reductases (RNRs) use radical-based chemistry to catalyze the conversion of all four ribonucleotides to deoxyribonucleotides. The ubiquitous nature of RNRs necessitates multiple RNR classes that differ from each other in terms of the phosphorylation state of the ribonucleotide substrates, oxygen tolerance, and the nature of both the metallocofactor employed and the reducing systems. Although these differences allow RNRs to produce deoxyribonucleotides needed for DNA biosynthesis under a wide range of environmental conditions, they also present a challenge for establishment of a universal activity assay. Additionally, many current RNR assays are limited in that they only follow the conversion of one ribonucleotide substrate at a time, but in the cell, all four ribonucleotides are actively being converted into deoxyribonucleotide products as dictated by the cellular concentrations of allosteric specificity effectors. Here, we present a liquid chromatography with tandem mass spectrometry (LC-MS/MS)-based assay that can determine the activity of both aerobic and anaerobic RNRs on any combination of substrates using any combination of allosteric effectors. We demonstrate that this assay generates activity data similar to past published results with the canonical Escherichia coli aerobic class Ia RNR. We also show that this assay can be used for an anaerobic class III RNR that employs formate as the reductant, i.e. Streptococcus thermophilus RNR. We further show that this class III RNR is allosterically regulated by dATP and ATP. Lastly, we present activity data for the simultaneous reduction of all four ribonucleotide substrates by the E. coli class Ia RNR under various combinations of allosteric specificity effectors. This validated LC-MS/MS assay is higher throughput and more versatile than the historically established radioactive activity

Districts across India are progressing toward the national Jal Jeevan Mission goal of piped water supply and 100% Functional Household Tap Connections (FHTC) for all by 2024. While state and national data monitor progress toward tap water connection coverage, the functionality and sustainability of those piped water supplies are less clear. This study presents a Sustainability Planning Framework to assess rural drinking water conditions and needs at the village, block, and district scales. It employs a mobile app to survey five key aspects of sustainability: source water sustainability, water service sustainability, operations and maintenance financial sustainability, village institutional capacity, and asset management. Ordinal scores for these sustainability variables are analyzed and interpreted though GIS mapping to identify locations and types of village support needed. Scores are aggregated to create an overall village drinking water sustainability index. Important hydroclimatic, geomorphological, and socio-economic correlates of the drinking water sustainability index are also examined. This framework and methods can help districts in Maharashtra and other states analyze drinking water services, plan future investments, and make policy adjustments to ensure sustainability.

Natural Language Processing (NLP) deals with understanding and processing human text by any computer software. There are several network architectures in the fields of deep learning and artificial intelligence that are used for NLP. Deep learning techniques like recurrent neural networks and feed-forward neural networks are used to develop language models that perform several NLP tasks. Over the years, researchers have worked on developing state-of-the-art language models that achieve high accuracy and performance for NLP applications. With the development of deep neural network language models, the computational resources requirements and the energy costs for training and running language models increased. This led to research to compress the language models, thereby reducing the computational complexity of the language models. One of the methods used for this is tensor decomposition, like the tensor-train (TT) decomposition. During this thesis work, the application of the TT-decomposition method for compressing the embedding layer in a long-short-term memory model was investigated. Specifically, the effect of factorization and the order of factors in the embedding layer when it is represented in the TT-matrix format on the maximum test accuracy of the long- short term memory model for the NLP task of sentiment analysis was investigated. This was done by considering three different factorizations of the embedding layer in the model. Further, the effect of change in TT-ranks (hyperparameters of the model when the embedding layer is represented in the TT-matrix format) on the maximum test accuracy was also investigated. Based on the investigation and empirical results obtained, this thesis concludes that by having a larger number of factors in the factorization of the embedding layer, the maximum test accuracy of the model increases. Further, in a particular factorization, when the factors were arranged in such a way that the maximum values of the TT-ranks had a smal, Mechanical Engineering | Systems and Control

How different measures of adiposity are similarly or differentially related to mobility limitation and mortality is not clear. In total, 5849 community-dwelling men aged ≥65 years (mean age: 72 years) were followed mortality over 10 years and self-reported mobility limitations (any difficulty walking 2-3 blocks or with climbing 10 steps) at six contacts over 14 years. Baseline measures of adiposity included weight, BMI and percent fat by DXA. Appendicular lean mass (ALM, by DXA) was analyzed as ALM/ht2. Proportional hazards models estimated the risk of mortality, and repeated measures generalized estimating equations estimated the likelihood of mobility limitation. Over 10 years, 27.9% of men died; over 14 years, 48.0% of men reported at least one mobility limitation. We observed U-shaped relationships between weight, BMI, percent fat and ALM/ht2 with mortality. There was a clear log-linear relationship between weight, BMI and percent fat with incident mobility limitation, with higher values associated with a greater likelihood of mobility limitation. In contrast, there was a U-shaped relationship between ALM/ht2 and incident mobility limitation. These observational data suggest that no single measure of adiposity or body composition reflects both the lowest risk of mortality and the lowest likelihood for developing mobility limitation in older men.

Biology has changed radically in the past two decades, growing from a purely descriptive science into also a design science. The availability of tools that enable the precise modification of cells, as well as the ability to collect large amounts of multimodal data, open the possibility of sophisticated bioengineering to produce fuels, specialty and commodity chemicals, materials, and other renewable bioproducts. However, despite new tools and exponentially increasing data volumes, synthetic biology cannot yet fulfill its true potential due to our inability to predict the behavior of biological systems. Here, we showcase a set of computational tools that, combined, provide the ability to store, visualize, and leverage multiomics data to predict the outcome of bioengineering efforts. We show how to upload, visualize, and output multiomics data, as well as strain information, into online repositories for several isoprenol-producing strain designs. We then use these data to train machine learning algorithms that recommend new strain designs that are correctly predicted to improve isoprenol production by 23%. This demonstration is done by using synthetic data, as provided by a novel library, that can produce credible multiomics data for testing algorithms and computational tools. In short, this paper provides a step-by-step tutorial to leverage these computational tools to improve production in bioengineered strains.

Machine learning provides researchers a unique opportunity to make metabolic engineering more predictable. In this review, we offer an introduction to this discipline in terms that are relatable to metabolic engineers, as well as providing in-depth illustrative examples leveraging omics data and improving production. We also include practical advice for the practitioner in terms of data management, algorithm libraries, computational resources, and important non-technical issues. A variety of applications ranging from pathway construction and optimization, to genetic editing optimization, cell factory testing, and production scale-up are discussed. Moreover, the promising relationship between machine learning and mechanistic models is thoroughly reviewed. Finally, the future perspectives and most promising directions for this combination of disciplines are examined.

The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15538. G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.

How different measures of adiposity are similarly or differentially related to mobility limitation and mortality is not clear. In total, 5849 community-dwelling men aged ≥65 years (mean age: 72 years) were followed mortality over 10 years and self-reported mobility limitations (any difficulty walking 2-3 blocks or with climbing 10 steps) at six contacts over 14 years. Baseline measures of adiposity included weight, BMI and percent fat by DXA. Appendicular lean mass (ALM, by DXA) was analyzed as ALM/ht2. Proportional hazards models estimated the risk of mortality, and repeated measures generalized estimating equations estimated the likelihood of mobility limitation. Over 10 years, 27.9% of men died; over 14 years, 48.0% of men reported at least one mobility limitation. We observed U-shaped relationships between weight, BMI, percent fat and ALM/ht2 with mortality. There was a clear log-linear relationship between weight, BMI and percent fat with incident mobility limitation, with higher values associated with a greater likelihood of mobility limitation. In contrast, there was a U-shaped relationship between ALM/ht2 and incident mobility limitation. These observational data suggest that no single measure of adiposity or body composition reflects both the lowest risk of mortality and the lowest likelihood for developing mobility limitation in older men.

Biology has changed radically in the past two decades, growing from a purely descriptive science into also a design science. The availability of tools that enable the precise modification of cells, as well as the ability to collect large amounts of multimodal data, open the possibility of sophisticated bioengineering to produce fuels, specialty and commodity chemicals, materials, and other renewable bioproducts. However, despite new tools and exponentially increasing data volumes, synthetic biology cannot yet fulfill its true potential due to our inability to predict the behavior of biological systems. Here, we showcase a set of computational tools that, combined, provide the ability to store, visualize, and leverage multiomics data to predict the outcome of bioengineering efforts. We show how to upload, visualize, and output multiomics data, as well as strain information, into online repositories for several isoprenol-producing strain designs. We then use these data to train machine learning algorithms that recommend new strain designs that are correctly predicted to improve isoprenol production by 23%. This demonstration is done by using synthetic data, as provided by a novel library, that can produce credible multiomics data for testing algorithms and computational tools. In short, this paper provides a step-by-step tutorial to leverage these computational tools to improve production in bioengineered strains.

Machine learning provides researchers a unique opportunity to make metabolic engineering more predictable. In this review, we offer an introduction to this discipline in terms that are relatable to metabolic engineers, as well as providing in-depth illustrative examples leveraging omics data and improving production. We also include practical advice for the practitioner in terms of data management, algorithm libraries, computational resources, and important non-technical issues. A variety of applications ranging from pathway construction and optimization, to genetic editing optimization, cell factory testing, and production scale-up are discussed. Moreover, the promising relationship between machine learning and mechanistic models is thoroughly reviewed. Finally, the future perspectives and most promising directions for this combination of disciplines are examined.

In this article, we present a two-point boundary value problem with separated boundary conditions for a finite nabla fractional difference equation. First, we construct an associated Green’s function as a series of functions with the help of spectral theory, and obtain some of its properties. Under suitable conditions on the nonlinear part of the nabla fractional difference equation, we deduce two existence results of the considered nonlinear problem by means of two Leray–Schauder fixed point theorems. We provide a couple of examples to illustrate the applicability of the established results

Conditional neural text generation models generate high-quality outputs, but often concentrate around a mode when what we really want is a diverse set of options. We present a search algorithm to construct lattices encoding a massive number of generation options. First, we restructure decoding as a best-first search, which explores the space differently than beam search and improves efficiency by avoiding pruning paths. Second, we revisit the idea of hypothesis recombination: we can identify pairs of similar generation candidates during search and merge them as an approximation. On both summarization and machine translation, we show that our algorithm encodes thousands of diverse options that remain grammatical and high-quality into one lattice. This algorithm provides a foundation for building downstream generation applications on top of massive-scale diverse outputs., Comment: NAACL 2022, see https://github.com/jiacheng-xu/lattice-generation for code

The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15538. G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.

The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15538. G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.

© 2019 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. For commercial protein therapeutics, Chinese hamster ovary (CHO) cells have an established history of safety, proven capability to express a wide range of therapeutic proteins and high volumetric productivities. Expanding global markets for therapeutic proteins and increasing concerns for broadened access of these medicines has catalyzed consideration of alternative approaches to this platform. Reaching these objectives likely will require an order of magnitude increase in volumetric productivity and a corresponding reduction in the costs of manufacture. For CHO-based manufacturing, achieving this combination of targeted improvements presents challenges. Based on a holistic analysis, the choice of host cells was identified as the single most influential factor for both increasing productivity and decreasing costs. Here we evaluated eight wild-type eukaryotic micro-organisms with prior histories of recombinant protein expression. The evaluation focused on assessing the potential of each host, and their corresponding phyla, with respect to key attributes relevant for manufacturing, namely (a) growth rates in industry-relevant media, (b) adaptability to modern techniques for genome editing, and (c) initial characterization of product quality. These characterizations showed that multiple organisms may be suitable for production with appropriate engineering and development and highlighted that yeast in general present advantages for rapid genome engineering and development cycles.

Sustainable rural drinking water is a widespread aim in India, and globally, from the household to district, state, and national scales. Sustainability issues in the rural drinking water sector range from increasing water demand to declining groundwater levels, premature deterioration of village schemes and services, inadequate revenues for operations and maintenance, weak capacity of water operators, frequently changing state and national policies, and destabilizing effects of climate change. This paper focuses on the special role of district-scale drinking water planning, which operates at the intersection between bottom-up water demand and top-down water programs. After surveying the challenges associated with bottom-up and top-down planning approaches, we present recent efforts to strengthen district and block drinking water planning in the state of Maharashtra. A combination of district interviews, institutional history, village surveys, GIS visualization, and planning workshops were used to advance district planning goals and methods. Results assess bottom-up processes of water demand; top-down water programs and finance; and intermediate-level planning at the district and block scales. Discussion focuses on potential improvements in district planning methods in Maharashtra.

Many animals and humans process the visual field with a varying spatial resolution (foveated vision) and use peripheral processing to make eye movements and point the fovea to acquire high-resolution information about objects of interest. This architecture results in computationally efficient rapid scene exploration. Recent progress in self-attention-based Vision Transformers, an alternative to the traditionally convolution-reliant computer vision systems. However, the Transformer models do not explicitly model the foveated properties of the visual system nor the interaction between eye movements and the classification task. We propose Foveated Transformer (FoveaTer) model, which uses pooling regions and eye movements to perform object classification tasks using a Vision Transformer architecture. Using square pooling regions or biologically-inspired radial-polar pooling regions, our proposed model pools the image features from the convolution backbone and uses the pooled features as an input to transformer layers. It decides on subsequent fixation location based on the attention assigned by the Transformer to various locations from past and present fixations. It dynamically allocates more fixation/computational resources to more challenging images before making the final image category decision. Using five ablation studies, we evaluate the contribution of different components of the Foveated model. We perform a psychophysics scene categorization task and use the experimental data to find a suitable radial-polar pooling region combination. We also show that the Foveated model better explains the human decisions in a scene categorization task than a Baseline model. We demonstrate our model's robustness against PGD adversarial attacks with both types of pooling regions, where we see the Foveated model outperform the Baseline model.

Game publishers and anti-cheat companies have been unsuccessful in blocking cheating in online gaming. We propose a novel, vision-based approach that captures the final state of the frame buffer and detects illicit overlays. To this aim, we train and evaluate a DNN detector on a new dataset, collected using two first-person shooter games and three cheating software. We study the advantages and disadvantages of different DNN architectures operating on a local or global scale. We use output confidence analysis to avoid unreliable detections and inform when network retraining is required. In an ablation study, we show how to use Interval Bound Propagation to build a detector that is also resistant to potential adversarial attacks and study its interaction with confidence analysis. Our results show that robust and effective anti-cheating through machine learning is practically feasible and can be used to guarantee fair play in online gaming., Comment: 17 pages, 4 figures

The South Asian subcontinent is characterized by a complex history of human migrations and population interactions. In this study, we used genome-wide data to provide novel insights on the demographic history and population relationships of six Indo-European populations from the Indian State of West Maharashtra. The samples correspond to two castes (Deshastha Brahmins and Kunbi Marathas) and four tribal groups (Kokana, Warli, Bhil and Pawara). We show that tribal groups have had much smaller effective population sizes than castes, and that genetic drift has had a higher impact in tribal populations. We also show clear affinities between the Bhil and Pawara tribes, and to a lesser extent, between the Warli and Kokana tribes. Our comparisons with available modern and ancient DNA datasets from South Asia indicate that the Brahmin caste has higher Ancient Iranian and Steppe pastoralist contributions than the Kunbi Marathas caste. Additionally, in contrast to the two castes, tribal groups have very high Ancient Ancestral South Indian (AASI) contributions. Indo-European tribal groups tend to have higher Steppe contributions than Dravidian tribal groups, providing further support for the hypothesis that Steppe pastoralists were the source of Indo-European languages in South Asia, as well as Europe.

The South Asian subcontinent is characterized by a complex history of human migrations and population interactions. In this study, we used genome-wide data to provide novel insights on the demographic history and population relationships of six Indo-European populations from the Indian State of West Maharashtra. The samples correspond to two castes (Deshastha Brahmins and Kunbi Marathas) and four tribal groups (Kokana, Warli, Bhil and Pawara). We show that tribal groups have had much smaller effective population sizes than castes, and that genetic drift has had a higher impact in tribal populations. We also show clear affinities between the Bhil and Pawara tribes, and to a lesser extent, between the Warli and Kokana tribes. Our comparisons with available modern and ancient DNA datasets from South Asia indicate that the Brahmin caste has higher Ancient Iranian and Steppe pastoralist contributions than the Kunbi Marathas caste. Additionally, in contrast to the two castes, tribal groups have very high Ancient Ancestral South Indian (AASI) contributions. Indo-European tribal groups tend to have higher Steppe contributions than Dravidian tribal groups, providing further support for the hypothesis that Steppe pastoralists were the source of Indo-European languages in South Asia, as well as Europe.

The South Asian subcontinent is characterized by a complex history of human migrations and population interactions. In this study, we used genome-wide data to provide novel insights on the demographic history and population relationships of six Indo-European populations from the Indian State of West Maharashtra. The samples correspond to two castes (Deshastha Brahmins and Kunbi Marathas) and four tribal groups (Kokana, Warli, Bhil and Pawara). We show that tribal groups have had much smaller effective population sizes than castes, and that genetic drift has had a higher impact in tribal populations. We also show clear affinities between the Bhil and Pawara tribes, and to a lesser extent, between the Warli and Kokana tribes. Our comparisons with available modern and ancient DNA datasets from South Asia indicate that the Brahmin caste has higher Ancient Iranian and Steppe pastoralist contributions than the Kunbi Marathas caste. Additionally, in contrast to the two castes, tribal groups have very high Ancient Ancestral South Indian (AASI) contributions. Indo-European tribal groups tend to have higher Steppe contributions than Dravidian tribal groups, providing further support for the hypothesis that Steppe pastoralists were the source of Indo-European languages in South Asia, as well as Europe.

ObjectivesOur aim was to determine the association between protein intake (overall and by source) and all-cause and cause-specific mortality among older men.DesignProspective cohort study.Setting5790 ambulatory community-dwelling older men from multicenter Osteoporotic Fractures in Men (MrOS) study.MeasurementsTotal energy and protein intake, and protein intake by source (dairy, non-dairy animal, plant) were assessed using a 69-item food frequency questionnaire. We included up to 10-year follow-up with adjudicated cardiovascular, cancer and other mortality outcomes. We used time-to-event analysis with protein exposures, mortality outcome, and adjusted for possible confounders including age, center, education, race, smoking, alcohol use, physical activity, weight, total energy intake (TEI), and comorbidities. Hazard ratios were expressed per each unit=2.9% TEI decrement for all protein intake variables.ResultsThe mean (SD) baseline age of 5790 men was 73.6 (5.8) y. There were 1611 deaths and 211 drop-outs prior to 10 years, and 3868 men who were alive at the 10-year follow-up. The mean (SD) total protein intake was 64.7 (25.8) g/d, while the mean (SD) intake expressed as percent of total energy intake (%TEI) was 16.1 (2.9) %TEI. Lower protein intake was associated with an increased risk of death, with unadjusted HR=1.11 (95% CI: 1.06, 1.17) and adjusted HR=1.09 (95% CI: 1.04, 1.14) and the associations for protein intake by source were similar. The adjusted HR for cancer mortality was HR=1.13 (95% CI: 1.03, 1.25) while the association for CVD mortality was HR=1.08 (95% CI: 0.99, 1.18).ConclusionsLow protein intake, irrespective of source, was associated with a modest increase in risk of all-cause and cause-specific mortality among older men. Special consideration should be given to level of protein intake among older adults.

ObjectivesOur aim was to determine the association between protein intake (overall and by source) and all-cause and cause-specific mortality among older men.DesignProspective cohort study.Setting5790 ambulatory community-dwelling older men from multicenter Osteoporotic Fractures in Men (MrOS) study.MeasurementsTotal energy and protein intake, and protein intake by source (dairy, non-dairy animal, plant) were assessed using a 69-item food frequency questionnaire. We included up to 10-year follow-up with adjudicated cardiovascular, cancer and other mortality outcomes. We used time-to-event analysis with protein exposures, mortality outcome, and adjusted for possible confounders including age, center, education, race, smoking, alcohol use, physical activity, weight, total energy intake (TEI), and comorbidities. Hazard ratios were expressed per each unit=2.9% TEI decrement for all protein intake variables.ResultsThe mean (SD) baseline age of 5790 men was 73.6 (5.8) y. There were 1611 deaths and 211 drop-outs prior to 10 years, and 3868 men who were alive at the 10-year follow-up. The mean (SD) total protein intake was 64.7 (25.8) g/d, while the mean (SD) intake expressed as percent of total energy intake (%TEI) was 16.1 (2.9) %TEI. Lower protein intake was associated with an increased risk of death, with unadjusted HR=1.11 (95% CI: 1.06, 1.17) and adjusted HR=1.09 (95% CI: 1.04, 1.14) and the associations for protein intake by source were similar. The adjusted HR for cancer mortality was HR=1.13 (95% CI: 1.03, 1.25) while the association for CVD mortality was HR=1.08 (95% CI: 0.99, 1.18).ConclusionsLow protein intake, irrespective of source, was associated with a modest increase in risk of all-cause and cause-specific mortality among older men. Special consideration should be given to level of protein intake among older adults.

A K M Nawshad Hossian,1 Seetharama D Jois,1 Subash C Jonnalagadda,2 George Mattheolabakis1 1School of Basic Pharmaceutical and Toxicological Sciences, College of Pharmacy, University of Louisiana Monroe, Monroe, LA, USA; 2Department of Chemistry and Biochemistry, Rowan University, Glassboro, NJ, USACorrespondence: George MattheolabakisSchool of Basic Pharmaceutical and Toxicological Sciences, College of Pharmacy, University of Louisiana Monroe, 1800 Bienville Dr, Monroe, LA 71201, USATel +1 318 342-7930Email matthaiolampakis@ulm.eduPurpose: Nucleic acid-based therapies are a promising therapeutic tool. The major obstacle in their clinical translation is their efficient delivery to the desired tissue. We developed a novel nanosized delivery system composed of conjugates of α-tocopherol, polyethyleneimine, and polyethylene glycol (TPP) to deliver nucleic acids.Methods: We synthesized a panel of TPP molecules using different molecular weights of PEG and PEI and analyzed with various analytical approaches. The optimized version of TPP (TPP111 - the 1:1:1 molecular ratio) was self-assembled in water to produce nanostructures and then evaluated in diversified in vitro and in vivo studies.Results: Through a panel of synthesized molecules, TPP111 conjugate components self-assembled in water, forming globular shaped nanostructures of ∼ 90 nm, with high nucleic acid entrapment efficiency. The polymer had low cytotoxicity in vitro and protected nucleic acids from nucleases. Using a luciferase-expressing plasmid, TPP111-plasmid nano-complexes were rapidly up-taken by cancer cells in vitro and induced strong transfection, comparable to PEI. Colocalization of the nano-complexes and endosomes/lysosomes suggested an endosome-mediated uptake. Using a subcutaneous tumor model, intravenously injected nano-complexes preferentially accumulated to the tumor area over 24 h.Conclusion: These results indicate that we successfully synthesized the TPP111 nanocarrier system

ObjectivesOur aim was to determine the association between protein intake (overall and by source) and all-cause and cause-specific mortality among older men.DesignProspective cohort study.Setting5790 ambulatory community-dwelling older men from multicenter Osteoporotic Fractures in Men (MrOS) study.MeasurementsTotal energy and protein intake, and protein intake by source (dairy, non-dairy animal, plant) were assessed using a 69-item food frequency questionnaire. We included up to 10-year follow-up with adjudicated cardiovascular, cancer and other mortality outcomes. We used time-to-event analysis with protein exposures, mortality outcome, and adjusted for possible confounders including age, center, education, race, smoking, alcohol use, physical activity, weight, total energy intake (TEI), and comorbidities. Hazard ratios were expressed per each unit=2.9% TEI decrement for all protein intake variables.ResultsThe mean (SD) baseline age of 5790 men was 73.6 (5.8) y. There were 1611 deaths and 211 drop-outs prior to 10 years, and 3868 men who were alive at the 10-year follow-up. The mean (SD) total protein intake was 64.7 (25.8) g/d, while the mean (SD) intake expressed as percent of total energy intake (%TEI) was 16.1 (2.9) %TEI. Lower protein intake was associated with an increased risk of death, with unadjusted HR=1.11 (95% CI: 1.06, 1.17) and adjusted HR=1.09 (95% CI: 1.04, 1.14) and the associations for protein intake by source were similar. The adjusted HR for cancer mortality was HR=1.13 (95% CI: 1.03, 1.25) while the association for CVD mortality was HR=1.08 (95% CI: 0.99, 1.18).ConclusionsLow protein intake, irrespective of source, was associated with a modest increase in risk of all-cause and cause-specific mortality among older men. Special consideration should be given to level of protein intake among older adults.

A hydraulic damper plays an important role in tuning the handling and comfort characteristicsof a vehicle. Tuning and selecting a damper based on subjective evaluation, by considering theopinions of various users, would be an inefficient method since the comfort requirements of usersvary a lot. Instead, mathematical models of damper and simulation of these models in variousoperating conditions are preferred to standardize the tuning procedure, quantify the comfortlevels and reduce cost of testing. This would require a model, which is good enough to capture thebehaviour of damper in various operating and extreme conditions.The Force-Velocity (FV) curve is one of the most widely used model of a damper. This curve isimplemented either as an equation or as a look-up table. It is a plot between the maximum forceat each peak velocity point. There are certain dynamic phenomena like hysteresis and dependencyon the displacement of damper, which cannot be captured with a FV curve model, but are requiredfor better understanding of the vehicle behaviour.This thesis was conducted in cooperation with Volvo Cars with an aim to improve the existingdamper model which is a Force-Velocity curve. This work focuses on developing a damper model,which is complex enough to capture the phenomena discussed above and simple enough to beimplemented in real time simulations. Also, the thesis aims to establish a standard method toparameterise the damper model and generate the Force-Velocity curve from the tests performedon the damper test rig. A test matrix which includes the standard tests for parameterising andthe extreme test cases for the validation of the developed model will be developed. The final focusis to implement the damper model in a multi body simulation (MBS) software.The master thesis starts with an introduction, where the background for the project is described and then the thesis goals are set. It is followed by a literature review in which fewadvanced damper models are discuss, En hydraulisk stötdämpare spelar en viktig roll för att fordonets hantering och komfort. Attjustera och välja en stötdämpare baserat på subjektiv utvärdering, genom att beakta olika användares åsikter, skulle vara en ineffektiv metod eftersom användarnas komfortkrav varierarmycket. Istället föredras matematiska modeller av stötdämpare och simulering av dessa modellerunder olika driftsförhållanden för att standardisera inställningsförfarandet, kvantifiera komfortnivåerna och minska testkostnaden. Detta skulle kräva en modell som är tillräckligt bra för attfånga upp stötdämparens beteende under olika drifts- och extrema förhållanden.Force-Velocity (FV) -kurvan är en av de mest använda stötdämparmodellerna. Denna kurvaimplementeras antingen som en ekvation eller som en uppslagstabell. Det är ett diagram somredovisar den maximala kraften vid varje maxhastighetspunkt. Det finns vissa dynamiskafenomen som hysteres och beroende av stötdämparens förskjutning, som inte kan fångas med enFV-kurvmodell, men som krävs för att bättre förstå fordonets beteende.Denna avhandling genomfördes i samarbete med Volvo Cars i syfte att förbättra den befintligastötdämparmodellen som är en Force-Velocity-kurva. Detta arbete fokuserar på att utveckla enstötdämparmodell, som är tillräckligt komplex för att fånga upp de fenomen som diskuteratsovan och tillräckligt enkel för att implementeras i realtidssimuleringar. Avhandlingen syftarockså till att upprätta en standardmetod för att parametrisera spjällmodellen och generera ForceVelocity-kurvan från de test som utförts på stötdämpartestriggen. En testmatris som innehållerstandardtest för parametrisering och extrema testfall för validering av den utvecklade modellenkommer att utvecklas. Det sista fokuset är att implementera stötdämparmodellen i en multi-bodysimulation (MBS) programvara.Examensarbetet inleds med en introduktion, där bakgrunden för projektet beskrivs ochdärefter definieras målen med arbetet. Det följs av en litteraturöversikt där n