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Current human papilloma virus (HPV) vaccines provide substantial protection against the most common HPV types responsible for oral and anogenital cancers, but many circulating cancer-causing types remain that lack vaccine coverage. The novel RG1-VLP (virus-like particle) vaccine candidate utilizes the HPV16-L1 subunit as a backbone to display an inserted HPV16-L2 17–36 a.a. “RG1” epitope; the L2 RG1 epitope is conserved across many HPV types and the generation of cross-neutralizing antibodies (Abs) against which has been demonstrated. In an effort to heighten the immunogenicity of the RG1-VLP vaccine, we compared in BALB/c mice adjuvant formulations consisting of novel bacterial enzymatic combinatorial chemistry (BECC)-derived toll-like receptor 4 (TLR4) agonists and the aluminum hydroxide adjuvant Alhydrogel. In the presence of BECC molecules, consistent improvements in the magnitude of Ab responses to both HPV16-L1 and the L2 RG1 epitope were observed compared to Alhydrogel alone. Furthermore, neutralizing titers to HPV16 as well as cross-neutralization of pseudovirion (PsV) types HPV18 and HPV39 were augmented in the presence of BECC agonists as well. Levels of L1 and L2-specific Abs were achieved after two vaccinations with BECC/Alhydrogel adjuvant that were equivalent to or greater than levels achieved with 3 vaccinations with Alhydrogel alone, indicating that the presence of BECC molecules resulted in accelerated immune responses that could allow for a decreased dose schedule for VLP-based HPV vaccines. In addition, dose-sparing studies indicated that adjuvantation with BECC/Alhydrogel allowed for a 75% reduction in antigen dose while still retaining equivalent magnitudes of responses to the full VLP dose with Alhydrogel. These data suggest that adjuvant optimization of HPV VLP-based vaccines can lead to rapid immunity requiring fewer boosts, dose-sparing of VLPs expensive to produce, and the establishment of a longer-lasting humoral immunity.

The high-performance fiber-reinforced polymer (FRP) composites have been extensively preferred as a replacement to the conventional materials. These composites have impressive mechanical properties. This study involves the fabrication and investigation of the flexural strength of the hybrid FRPs material made from three distinct laminates. The hybrid FRPs have been prepared using hand lay-up technique. The fabricated specimens have been tested under three-point bending following ASTM D790 standards. From the results, it has been observed that the specimen having Kevlar at the topmost has the highest value of flexural strength. This feature of hybrid FRP makes it a better alternative to conventional materials used for leaf springs.

Shigella ssp cause bacillary dysentery (shigellosis) which has high global morbidity in young children and the elderly. The virulence of Shigella relies upon a type III secretion system (T3SS) which injects host altering effector proteins into targeted intestinal cells. The Shigella T3SS contains two components, invasion plasmid antigen D (IpaD) and invasion plasmid antigen B (IpaB), that were previously identified as broadly protective antigens. When IpaD and IpaB were co-expressed to give the DB fusion (DBF) protein, vaccine efficacy was further improved. Biophysical characterization under various pH conditions showed that DBF is most stable at pH 7 and 8 and loses its conformational integrity at 48 and 50 °C respectively. Forced degradation studies revealed significant effects on the secondary structure, tertiary structure and conformational stability of DBF. In the presence of phosphate buffers as well as other anionic excipients, DBF demonstrated a concentration dependent conformational stabilization. Molecular docking revealed potential polyanion binding sites in DBF that may interact with phytic acid. These sites can be exploited to stabilize the DBF protein. This work highlights potential destabilizing and stabilizing factors, which not only improves our understanding of the DBF protein but helps in future development of a stable Shigella vaccine.

Introduction Injectable semaglutide is a glucagon-like peptide-1 receptor agonist (GLP-1 RA) that was previously shown to be superior to liraglutide and dulaglutide in head-to-head comparisons in GLP-1 RA-naïve individuals. It is hypothesized that semaglutide will cause further reductions in glycated hemoglobin A1c (HbA1c) and weight in type 2 diabetes mellitus (T2DM) patients previously treated with liraglutide or dulaglutide. The REALISE-DM study provides the first real-world evidence of the effectiveness and tolerability of semaglutide in patients switching from another GLP-1 RA. Methods This retrospective real-world effectiveness analysis included T2DM adults who were on a stable dose of liraglutide or dulaglutide prior to switching to semaglutide. The primary outcome was change in HbA1c. Secondary outcomes were the changes in weight and body mass index (BMI), the occurrence of gastrointestinal side effects (GSEs), and discontinuations. Linear mixed models were used to estimate changes in HbA1c, weight, and BMI, and logistic regression was employed to analyze GSEs and discontinuations. Results Six months after the 164 patients in this study had switched to semaglutide, their mean HbA1c had decreased by 0.65% (7.1 mmol/mol) (95% prediction interval [PI]: 0.48, 0.81% [5.2, 8.9 mmol/mol]) from a baseline of 7.9% (interquartile range [IQR]: 7.3, 8.8) (62.8 mmol/mol [IQR: 56.3, 72.7]), while their weight and BMI had reduced by 1.69 kg (95% PI: 1.01, 2.37) and 0.59 kg/m2 (95% PI: 0.34, 0.84), respectively. Nineteen patients (11.6%) developed GSEs after switching. Conclusions This study supports switching T2DM patients on liraglutide or dulaglutide to injectable semaglutide to achieve further reductions in HbA1c and weight. Although a small number of GSEs occurred, semaglutide was well tolerated by the majority of the patients. Supplementary Information The online version contains supplementary material available at 10.1007/s13300-020-00984-x.

The serotype-specific early detection of dengue fever is very effective in predicting the pervasiveness of fatal infections such as dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS). This fever results from reinfection (secondary) with a serotype of the dengue virus, which is different from the serotype involved in primary infection. Hence, the present work was aimed to develop a multiplexed electrochemical paper-based analytical device (ePAD) consisting of graphene oxide-silicon dioxide (GO-SiO

Cabazitaxel, a novel tubulin inhibitor with poor affinity for P-glycoprotein, is a second-generation taxane holding great promise for the treatment of metastatic castration-resistant prostate cancer. However, its poor solubility and lack of target-ability limit its therapeutic applications. Herein, we develop a biodegradable, enzyme-responsive, and targeted polymeric micelle for cabazitaxel. The micelle is formed from two amphiphilic block copolymers. The first block copolymer consists of PEG, an enzyme-responsive peptide, and cholesterol; whereas the second block copolymer consists of a targeting ligand, PEG and cholesterol. The enzyme-responsive peptide is cleavable in the presence of matrixmetaloproteinase-2 (MMP-2), which is overexpressed in the tumor microenvironment of prostate cancer. The micelle showed a very low critical micelle concentration (CMC), high drug loading, and high entrapment efficiency. Release of cabazitaxel from the micelle is dependent on the cleavage of the enzyme-responsive peptide. Moreover, the micelle showed dramatically higher cellular uptake in prostate cancer cells compared to free cabazitaxel. Importantly, the ligand-coupled polymeric micelle demonstrated better inhibition of tumor growth in mice bearing prostate cancer xenografts compared to unmodified micelle and free cabazitaxel. Taken together, these findings suggest that the enzyme-responsive cabazitaxel micelle is a potent and promising drug delivery system for advanced prostate cancer therapy. STATEMENT OF SIGNIFICANCE: Herein, we develop a biodegradable, enzyme-responsive, and actively targeted polymer micelle for cabazitaxel, which is a novel tubulin inhibitor with poor affinity for P-glycoprotein. Despite cabazitaxel's great promise for metastatic castration-resistant prostate cancer, its poor solubility, lack of target-ability, and high systemic toxicity limit its therapeutic applications, and therefore a targeted delivery system is highly needed for cabazitaxel. Our results demonstrate the importance of active targeting in targeted prostate cancer therapy. Encapsulating cabazitaxel in the micelle increases its activity and is expected to reduce its systemic toxicity, which is a major hurdle in its clinical applications. Moreover, the polymeric micelle may servers as a promising nanoscale platform for the targeted delivery of other chemotherapeutic agents to prostate cancer.

The fluorine-19 nucleus was recognized early to harbor exceptional properties for NMR spectroscopy. With 100% natural abundance, a high gyromagnetic ratio (83% sensitivity compared to (1)H), a chemical shift that is extremely sensitive to its surroundings and near total absence in biological systems, it was destined to become a favored NMR probe, decorating small and large molecules. However, after early excitement, where uptake of fluorinated aromatic amino acids was explored in a series of animal studies, (19)F-NMR lost popularity, especially in large molecular weight systems, due to chemical shift anisotropy (CSA) induced line broadening at high magnetic fields. Recently, two orthogonal approaches, i) CF(3) labeling and ii) aromatic (19)F-(13)C labeling leveraging the TROSY (Transverse Relaxation Optimized Spectroscopy) effect have been successfully applied to study large biomolecular systems. In this perspective, we will discuss the fascinating early work with fluorinated aromatic amino acids, which reveals the enormous potential of these non-natural amino acids in biological NMR and the potential of (19)F-NMR to characterize protein and nucleic acid structure, function and dynamics in the light of recent developments. Finally, we explore how fluorine NMR might be exploited to implement small molecule or fragment screens that resemble physiological conditions and discuss the opportunity to follow the fate of small molecules in living cells.

Using alternative power sources to drive hydrogen production in microbial electrolysis cells (MECs) is important to implementation of MEC technology. Herein, thermoelectric generators (TEG) were to power MECs using simulated waste heat. With the MEC anolyte as a cold source for TEG, current generation of the MEC increased to 2.46 ± 0.06 mA and hydrogen production reached 0.14 m3 m−3 d-1, higher than those of the TEG-MEC system without hydraulic connection (1.16 ± 0.07 mA and 0.07 ± 0.01 m3 m−3 d-1). A high recirculation rate of 30 mL min-1 doubled both current generation and hydrogen production with 10 mL min-1, benefited from a stronger cooling effect that increased the TEG voltage output. However, the optimal recirculation rate was determined as 20 mL min-1 because of comparable performance but potentially less energy requirement. Reducing anolyte hydraulic retention time to 4 h has increased hydrogen production to 0.25 ± 0.05 m3 m−3 d-1 but decreased organic removal efficiency to 69 ± 2%. Adding three more TEG units that captured more heat energy further enhanced hydrogen production to 0.36 m3 m−3 d-1. Those results have demonstrated a successful integration of TEG with MEC through both electrical and hydraulic connections for simultaneous wastewater treatment and energy recovery.

Convolutional Neural Networks (CNNs) are popular models that have been successfully applied to diverse domains like vision, speech, and text. To reduce inference-time latency, it is common to employ hardware accelerators, which often require a model compression step. Contrary to most compression algorithms that are agnostic of the underlying hardware acceleration strategy, this paper introduces a novel Symmetric $k$ -means based compression algorithm that is specifically designed to support a new FPGA-based hardware acceleration scheme by reducing the number of inference-time multiply-accumulate (MAC) operations by up to 98%. First, a simple $k$ -means based training approach is presented and then as an extension, Symmetric $k$ -means is proposed which yields twice the reduction in MAC operations for the same bit-depth as the simple $k$ -means approach. A comparative analysis is conducted on popular CNN architectures for tasks including classification, object detection and end-to-end stereo matching on various datasets. For all tasks, the model compression down to 3 bits is presented, while no loss is observed in accuracy for the 5-bits quantization.

Waste heat from anaerobic digesters can be converted to electricity by using thermoelectric generators (TEG). Herein, such energy was employed to power a microbial electrolysis cell (MEC) for producing hydrogen gas. Four TEG units could deliver a voltage of ~0.5 V, sufficient to drive the MEC that achieved a hydrogen production rate of 0.48 ± 0.13 m3 m−3 d−1. This rate was further improved to 0.75 ± 0.05 m3 m−3 d−1 when the temperature difference for TEG was increased from 18 to 28 °C. There was no significant difference between the TEG-powered MEC and power supply-supported MEC (at 0.6 V), in terms of current generation, hydrogen production, and organic removal. Ambient air was also studied as a cold-side source for TEG, although some challenges were encountered to maintain a large temperature difference. Those results will encourage further exploration of using TEG as a feasible power supply for sustainable MEC operation.

In the present work, basalt and glass layered hybrid composite has been fabricated and thereafter its various mechanical properties have been tested. It has been observed that this hybrid fiber composite has better mechanical properties as compared to basalt fiber reinforced plastic (BFRP) and glass fiber reinforced plastic (GFRP). Conventional machining methods have various limitations viz. fiber pullout, burr formation, etc., which results in poor cut surface quality and degraded mechanical performance. Laser beam machining can be one of the alternatives because it requires low specific energy and supports non-contact machining. However, in order to achieve better cut quality with high precision and accuracy during laser beam machining, selection of favourable range and levels of cutting parameters is quite pertinent. In the present study, Response surface methodology has been used to develop the mathematical models of kerf deviations in terms of input cutting viz. lamp current, pulse frequency, cutting speed, pulse width and compressed air pressure. Well correlation between the predicted and experimental values validates the proposed methodology of ascertaining favourable process parameters during laser machining of basalt – glass hybrid composite. Validation experimental results shows the lowest Top Kerf Deviation (TKD) and Bottom Kerf Deviation (BKD) have been achieved.

Type 2 diabetes has been a long-standing concern worldwide and in Singapore. Having one of the highest diabetes prevalence rates in Southeast Asia, Singapore has explored various ways of enhancing the management of chronic illnesses, one of which is to treat diabetic patients in primary care settings rather than speciality facilities. Primary care physicians are tasked to manage their diabetic patients’ glycated haemoglobin levels, along with a myriad of related complications including hypoglycaemia, cardiovascular risk, and body weight issues. With the ever-increasing complexity of population health demands, oral semaglutide can be a strategic weapon utilised by primary care doctors to treat type 2 diabetic patients. In terms of glycaemic control and body weight reduction, oral semaglutide has outperformed several other oral anti-diabetic medicines. Moreover, oral semaglutide has a proven cardiovascular safety profile with potential benefits. The development of oral semaglutide, rather than the injectable type, has made it simpler for patients to benefit from semaglutide treatment. Oral semaglutide is a feasible and effective strategy in type 2 diabetes management, for both initiation and intensification needs, and is well positioned to be a game changer in primary care.

The basic purpose of a vaccine is to simulate certain structural features of a pathogen or other target entities. Initially, successful vaccines consisted of live, attenuated, or inactivated organisms. It was later found that components of such organisms could be used as vaccines, although additional immunological stimulation by adjuvants is often required. The successful use of crude preparations of toxins such as those of diphtheria, tetanus, and pertussis was especially encouraging. The advent of recombinant DNA technology raised the hope that it would now be possible to create safe vaccines for virtually any disease by synthesizing chemically well-defined proteins such as those on the surface of viruses and bacteria that could induce a strong, neutralizing immune response. Since therapeutic proteins have a well-established history of formulation development and use in humans, it was assumed that their transformation to vaccines would be relatively straightforward. This has turned out not be the case, however. While initial success with vaccines for hepatitis B and human papilloma virus was striking, their virus-like particle nature (self-assembled virus surface proteins) proved to be a major reason for their success. This no doubt reflects their highly similar nature to the actual target pathogen. Very recent success with a recombinant protein-based vaccine for serogroup B-induced meningitis and shingles again suggests the potential utility of such vaccines. We are still left, however, with the quandary of the failure of the vast majority of recombinant vaccines to provide protective immune responses. In this chapter, we will consider the challenges associated with the development and use of recombinant protein-based vaccines and then provide five examples of such vaccines undergoing clinical evaluation. We will then discuss challenges for future protein-based vaccine development.

Immunotherapy using monoclonal antibodies targeting the PD-1/PD-L1 interaction has shown enormous success for various cancers. Despite their encouraging results in clinics, antibody-based checkpoint inhibitors have several limitations, such as poor tumor penetration. To address these limitations of monoclonal antibodies, there is a growing interest in developing low-molecular-weight checkpoint inhibitors, such as antibody fragments. Several antibody fragments targeting PD-1/PD-L1 were recently discovered using phage libraries from camel or alpaca. However, animal-derived antibody fragments may elicit unwanted immune responses, which limit their therapeutic applications. For the first time, we used a human domain antibody phage library and discovered anti-human PD-L1 human single-domain antibodies (dAbs) that block the PD-1/PD-L1 interaction. Among them, the CLV3 dAb shows the highest affinity to PD-L1. The CLV3 dAb also exhibits the highest blocking efficacy of the PD-1/PD-L1 interaction. Moreover, the CLV3 dAb significantly inhibits tumor growth in mice implanted with CT26 colon carcinoma cells. These results suggest that CLV3 dAb can be potentially used as an anti-PD-L1 inhibitor for cancer immunotherapy.

Conjoined twins represent a very rare congenital anomaly, and the dicephalic dibrachius dipus (DDD) type of conjoined twinning is so rare that the exact prevalence is unknown. Only a few published case studies have mentioned this anomaly. Not enough data are available where antenatal ultrasonography (USG) and MRI have been employed in the workup of such cases. This study describes the case of a 24-year-old woman who came to our department for an anomaly scan at 25 weeks of gestation and was diagnosed with a dicephalic type of conjoined twinning with multiple anomalies. However, USG could not differentiate between DDD twinning and craniopagus parasiticus; hence, the patient was referred for fetal MRI. On MRI, the diagnosis of DDD was confirmed. In craniopagus parasiticus twinning, the surgical removal of the parasitic head can allow an everyday life. However, DDD twinning with multiple anomalies is not compatible with life, and the mother was thoroughly explained the grave prognosis. In such doubtful cases, fetal MRI should always be employed to ascertain the diagnosis for proper management and counseling.

Supracondylar process of the humerus is a congenital bone projection seen on the distal humerus on the anteromedial surface. A fibrous band called ligament of Struthers’ connects the supracondylar process of humerus with medial epicondyle. It is mainly asymptomatic but rarely can present as supracondylar process syndrome due to neurovascular compression. Although isolated median nerve injuries are most common they can also present with fractures and vascular complications. The ulnar nerve is rarely involved. The median nerve can be trapped at several sites proximal to the carpal tunnel. Potential sites where the median nerve can be trapped are bicipital aponeurosis, two heads of pronator teres, flexor digitorum superficialis, aponeurotic arch and Gantzer muscle.[1] Supracondylar process of the humerus is a hook-like bony process seen about 5 cm proximal to the medial epicondyle and has a pointed apex. It is curved downwards and forwards and is commonly seen in climbing mammals. Vinilla et al. published a comparison of measurements of the supracondylar process of the humerus in different studies. The length of the process varied from 0.3 cm to 1.6 cm, breadth 1cm to 1.5 cm and distance from the medial epicondyle varied from 4.4 cm to 6.5 cm. They concluded that the supracondylar process had to be differentiated from osteochondroma and myositis ossificans.[2]

In this article, an approach has been introduced for detecting cancerous cells. Image processing techniques have been used, based on cancer cell area using CNNs. A very intriguing aspect of this experiment was that from a very small image dataset, a large number of images were generated using information augmentation which was then taken as the training set data. The suggested scheme detects cancer behaviors through a convolutional neural network in images of celled samples. Previously, the same attempts failed to stay away from the database dependencies, which were somewhat proportional to the number of images in datasets, so we used a method called data augmentation on smaller sets of images. The scheme preprocesses the input image by grayscale, binarization, inversion, median filtering, and flood-fill procedures. Depending on the sort of feature to be identified, the preprocessed image is then cancerous cell detected. This methodology was used for several sets of pictures, and the system was optimized with the feedback from those tests. For independent cancer cell detection with narrower datasets, the suggested technique can be efficiently used, which will greatly accelerate the study of cancer and open greater dimensions.

Explanations for police misconduct often center on a narrow notion of “problem officers,” the proverbial “bad apples.” Such an individualistic approach not only ignores the larger systemic problems of policing but also takes for granted the group-based nature of police work. Nearly all of police work is group-based and officers’ formal and informal networks can impact behavior, including misconduct. In extreme cases, groups of officers (what we refer to as, “crews”) have even been observed to coordinate their abusive and even criminal behaviors. This study adopts a social network and machine learning approach to empirically investigate the presence and impact of officer crews engaging in alleged misconduct in a major U.S. city: Chicago, IL. Using data on Chicago police officers between 1971 and 2018, we identify potential crews and analyze their impact on alleged misconduct and violence. Results detected approximately 160 possible crews, comprised of less than 4% of all Chicago police officers. Officers in these crews were involved in an outsized amount of alleged and actual misconduct, accounting for approximately 25% of all use of force complaints, city payouts for civil and criminal litigations, and police-involved shootings. The detected crews also contributed to racial disparities in arrests and civilian complaints, generating nearly 18% of all complaints filed by Black Chicagoans and 14% of complaints filed by Hispanic Chicagoans.

Desmoplasia plays a pivotal role in promoting pancreatic cancer progression and is associated with poor clinical outcome. Targeting the desmoplastic tumor microenvironment in combination with chemotherapy is therefore a promising strategy for pancreatic cancer therapy. Here, we report a novel biodegradable copolymer to codeliver LY2109761 (a TGF-β receptor I/II inhibitor) and CPI-613 (a novel chemotherapy agent) to desmoplastic stroma and tumor cells, respectively, in the tumor microenvironment. Hydrophobic CPI-613 is conjugated to the hydrophilic copolymer via a newly designed MMP-2-responsive linker to form a trigger-responsive nanopolyplex. LY2109761 is hydrophobic and encapsulated into the hydrophobic core of the nanopolyplex. The resulting nanopolyplex is modified with a plectin-1-targeting peptide to enhance the accumulation of the nanopolyplex in pancreatic tumors. The nanopolyplex aims to normalize the stroma by blocking the interaction between tumor cells and pancreatic stellate cells to inhibit the activation of pancreatic stellate cells and subsequently reduce the dense extracellular matrix. Normalized stroma increases the penetration of the nanopolyplex into the tumor. The nanopolyplex shows enhanced accumulation in xenograft pancreatic tumors in a biodistribution study. Moreover, the targeted nanopolyplex markedly inhibits tumor growth in an orthotopic pancreatic cancer mouse model by dual-targeting tumor cells and stroma. Overall, the multifunctional nanopolyplex is a promising platform for pancreatic cancer therapy.

In the present work, laser beam drilling of a fabricated basalt–glass hybrid composite has been done. From the experimental results, a safe machining zone pertaining to high drill quality with minimum heat affected zone and maximum hole-circularity has been predicted. The prediction of the zone has been done by mathematical modeling and optimization using artificial neural network merged with multi-objective genetic algorithm. The acquired zone has been confirmed by performing validation experiments. From the results, it is evident that the predicted range is capable of minimizing the heat affected zone with acceptable hole-circularity. Moreover, the variation in hole-circularity and heat affected zone with respect to the input drilling parameters has also been explored.

In the present work, basalt–glass hybrid composite has been fabricated and machined using laser beam drilling, to predict a safe machining zone pertaining to high drill quality with minimum heat-affected zone and maximum hole circularity. The prediction of the zone has been done by mathematical modeling using response surface methodology. The obtained zone has also been validated by performing more experiments. Moreover, the dependency of hole circularity and heat-affected zone on input parameters has also been discussed. From the results, it is evident that the obtained zone is capable of minimizing the heat-affected zone with acceptable hole circularity. Moreover, the behavior of input parameters is non-monotonic in nature.

This report presents a novel lab-on-a-paper (LoP)-based device coupled with a molybdenum disulfide nanosheet (MoS2NS)-modified electrochemical genosensor for detecting Salmonella-specific DNA. Conductive electrodes were grafted on a paper-based substrate employing a stencil printing technique, and MoS2NS was decorated on the working electrode. MoS2NS has strong affinity toward nucleo bases, which made it a best sensing interface for the immobilization of DNA. Morphological, optical, and structural characterizations were accomplished using X-ray diffraction (XRD), high-resolution transmission electron microscopy (HR-TEM), UV–vis spectroscopy (UV–vis), and Raman spectroscopy, repectively. The current studies of an electrochemical genosensor demonstrated a good linear detection range from 100–20 nM and a low limit of detection of 20 nM toward Salmonella DNA with R2 = 0.991. The proposed LoP-based genosensor confirmed as a better sensing podium and an effectual immobilization matrix for DNA.

Liver fibrosis is caused by excessive accumulation of extracellular matrix during chronic liver injuries. Although clinical evidence suggests that liver fibrosis can be reversed, there is no standard therapy for liver fibrosis. Moreover, there is a lack of diagnostic tools to detect early-stage liver fibrosis. Activation of hepatic stellate cells (HSCs) is the key step during liver fibrogenesis, and its mechanism has been extensively studied by various cell culture and animal models. Targeted delivery of therapeutic agents to activated HSCs is therefore critical for the successful treatment of liver fibrosis. A number of protein markers have been found to be overexpressed in activated HSCs, and their ligands have been used to specifically deliver various antifibrotic agents. In this review, we summarize these HSC-specific protein markers and their ligands for targeted delivery of antifibrotic agents.

Purpose: The purpose of this article is to investigate automated segmentation measurements of the outer nuclear layer to differentiate patients with hydroxychloroquine toxicity from healthy individuals. Methods: A 5-year retrospective, case-controlled, interventional study of hydroxychloroquine toxicity patients was conducted. Measurements of the outer nuclear layer were obtained with use of commercially available segmentation software and compared with controls. Results: Seven participants (13 eyes) with toxicity and 16 controls (16 eyes) were included. The data comparing the parafoveal, perifoveal, foveal, and overall regions were significant both in thickness ( P < .0001, P < .0001, P = .0029, and P < .0001, respectively) and volume ( P < .0001, P < .0001, P < .0001, and P < .0001, respectively). The CI indicates there is 95% confidence that toxicity patients have between 147 μm and 201 μm less thickness (average 174 μm) and between 0.39 mm3 and 0.55 mm3 less volume (average 0.47 mm3). Conclusions: The automated segmentation function can correctly differentiate thinner outer nuclear layer measurements in patients with toxicity. This study is the first to establish the ranges of thickness and volume of the outer nuclear layer with commercially available segmentation. These results provide the first step in determining whether automated segmentation measurements of the outer nuclear layer can be used as an objective screening tool for hydroxychloroquine toxicity.

Future wireless networks are expected to be ultra-dense and heterogeneous not just in terms of the number and type of base stations but also in terms of the number of users and the application types they access. Such a network architecture will require mobility management mechanisms that adapt rapidly to these highly dynamic network characteristics. In particular, the optimality of the handover signaling within these future network architectures will be extremely critical given their density and heterogeneity. In this paper, the optimality is relevant for both the total amount of signaling created and the total delay per handover process. In this paper, we first present a novel and optimized message mapping and signaling mechanism for the handover preparation and failure phases. We also develop a novel handover failure aware preparation signaling methodology, which accounts for the possibility of a handover failure and grants additional enhancements to the handover preparation and failure signaling phases. Through the analytical framework provided in this paper, we conduct studies to quantify the performance gains promised by the proposed mechanisms. These studies cover myriad handover scenarios as identified by 3GPP and use the statistics from cellular network operators and vendors. We then develop the idea and analytical framework for network wide analysis, in which the network wide processing cost and network occupation time for various handover failure rates are computed. Finally, we propose an evolutionary network architecture that facilitates the proposed signaling mechanism as well as assists operators in maintaining a manageable capital expenditure. It combines the current day and 3GPP proposed 5G network architecture with the software-defined networking approach. As a result, we argue that the proposed mechanisms are viable and outperform the legacy handover signaling mechanisms in terms of latency incurred, total network occupation time, number of messages generated, and total bytes transferred.

Relational data present in real world graph representations demands for tools capable to study it accurately. In this regard Graph Neural Network (GNN) is a powerful tool, wherein various models for it have also been developed over the past decade. Recently, there has been a significant push towards creating accelerators that speed up the inference and training process of GNNs. These accelerators, however, do not delve into the impact of their dataflows on the overall data movement and, hence, on the communication requirements. In this paper, we formulate analytical models that capture the amount of data movement in the most recent GNN accelerator frameworks. Specifically, the proposed models capture the dataflows and hardware setup of these accelerator designs and expose their scalability characteristics for a set of hardware, GNN model and input graph parameters. Additionally, the proposed approach provides means for the comparative analysis of the vastly different GNN accelerators., Comment: ISCAS 2021

Hyaluronic acid (HA)-based prodrugs bearing double-responsive (acid pH or oxidation) boronates of catechol-containing drugs were used to treat xenografted human prostate tumours (LNCaP) in SCID mice. The HA prodrugs accumulated significantly only in tumours (impressively, up to 40% of the injected dose after 24 h) and in liver, with negligible – actually anti-inflammatory - consequences in the latter. A quercetin-HA prodrug significantly slowed down tumour growth, in a dose-dependent fashion and with a much higher efficacy (up to 4 times) than equivalent doses of free quercetin. In short, boronated HA appears to be a very promising platform for targeted chemotherapy.

Graph Neural Networks (GNNs) have garnered a lot of recent interest because of their success in learning representations from graph-structured data across several critical applications in cloud and HPC. Owing to their unique compute and memory characteristics that come from an interplay between dense and sparse phases of computations, the emergence of reconfigurable dataflow (aka spatial) accelerators offers promise for acceleration by mapping optimized dataflows (i.e., computation order and parallelism) for both phases. The goal of this work is to characterize and understand the design-space of dataflow choices for running GNNs on spatial accelerators in order for mappers or design-space exploration tools to optimize the dataflow based on the workload. Specifically, we propose a taxonomy to describe all possible choices for mapping the dense and sparse phases of GNN inference, spatially and temporally over a spatial accelerator, capturing both the intra-phase dataflow and the inter-phase (pipelined) dataflow. Using this taxonomy, we do deep-dives into the cost and benefits of several dataflows and perform case studies on implications of hardware parameters for dataflows and value of flexibility to support pipelined execution., Accepted for publication at the 36th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2022)

Recently, Graph Neural Networks (GNNs) have received a lot of interest because of their success in learning representations from graph structured data. However, GNNs exhibit different compute and memory characteristics compared to traditional Deep Neural Networks (DNNs). Graph convolutions require feature aggregations from neighboring nodes (known as the aggregation phase), which leads to highly irregular data accesses. GNNs also have a very regular compute phase that can be broken down to matrix multiplications (known as the combination phase). All recently proposed GNN accelerators utilize different dataflows and microarchitecture optimizations for these two phases. Different communication strategies between the two phases have been also used. However, as more custom GNN accelerators are proposed, the harder it is to qualitatively classify them and quantitatively contrast them. In this work, we present a taxonomy to describe several diverse dataflows for running GNN inference on accelerators. This provides a structured way to describe and compare the design-space of GNN accelerators.

VHF communication links are mostly used by defense personnel and amateur radio operator or commonly known as HAM radio operators. The HAM radio operators communicate in the frequency band ranging from 144 to 146 MHz. Hence, in this paper, the dipole and Moxon antennae are designed for 145 MHz and are resonating at 144 MHz and 144.44 MHz, respectively. Both the dipole and Moxon antennae are simulated on HFSS using copper material and an element radius of 1.5 mm. The antennae are majorly investigated based on gain, directivity and return loss, and other parameters. The observed gain for dipole antenna and Moxon antenna is 2.4 dB and 6.2 dB, respectively, whereas the return loss of dipole antenna is −16.78 dB, and for Moxon antenna, the return loss is −30.26 dB. The Moxon antenna is highly directive as compared to the dipole antenna. As a result, Moxon antenna provides a reliable solution for VHF communication.

This research work has been conducted on polypropylene (PP) material using Moldflow Adviser (MFA). Moldflow Adviser (MFA) has been used to contemplate and confirm the impact of procedure boundaries and advance the volumetric shrinkage and fill time. Streamlining of procedure boundaries is finished using L27 design of experiments (DOE). Further, analysis of variance (ANOVA) has been conducted. Ideal blend of procedure boundaries is represented by ANOVA. Two unique combinations of sprue and sprinter framework are utilized for simulation. Analysis of variance shows that packing pressure is most huge variable for volumetric shrinkage in both of the cases. Regression model conditions for volumetric shrinkage and fill time are likewise created in this investigation. It will assist little with micro industry in improving nature of an injection molded plastic parts.

In this paper, we provide a novel application aware user association and resource allocation framework, i.e., AURA-5G, which utilizes a joint optimization strategy to accomplish the same. Concretely, our methodology considers all the real network constraints that will be prevalent in the 5G networks as well as practical deployment scenarios. Furthermore, AURA-5G, being an application aware framework, considers the resource requirements of both eMBB and mMTC services whilst performing the optimization task. We have demonstrated that our strategy performs significantly better than the baseline algorithm, given any of the multiple combinations of network constraints explored in this paper. In addition, we have also presented a novel computational complexity analysis for the AURA-5G framework as well as a solvability and convergence time analysis. Such an analysis will be beneficial for both industry and academia in determining the applicability and performance of the AURA-5G framework, given the scenario and constraints. Lastly, we have also provisioned a short study on the aspect of network re-dimensioning, wherein we demonstrate the efficacy of the AURA-5G framework in providing insights to the operators with regards to their deployment and how they can utilize it to optimize the performance of their networks., Comment: Submitted to Elsevier Computer Networks

The present work involves the fabrication of hybrid Fibre-reinforced polymer (FRP) composites and investigation of the change in their flexural strength concerning the stacking sequence and fibre. The hybrid FRPs consists of bidirectional woven basalt, Kevlar, E-glass and carbon fibres, fabricated as per ASTM D790 standards using hand lay- up method. The fabricated hybrid composites have been tested under three point-loading and different evaluations been made. It has been observed that specimen having basalt at the skin, followed by accumulative stacking of carbon and glass laminates gives better flexural strength as compares to another fabricated specimen.

The reconfigurable intelligent surface is a promising technology for the manipulation and control of wireless electromagnetic signals. In particular, it has the potential to provide significant performance improvements for wireless networks. However, to do so, a proper reconfiguration of the reflection coefficients of unit cells is required, which often leads to complex and expensive devices. To amortize the cost, one may share the system resources among multiple transmitters and receivers. In this paper, we propose an efficient reconfiguration technique providing control over multiple beams independently. Compared to time-consuming optimization techniques, the proposed strategy utilizes an analytical method to configure the surface for multi-beam radiation. This method is easy to implement, effective and efficient since it only requires phase reconfiguration. We analyze the performance for indoor and outdoor scenarios, given the broadcast mode of operation. The aforesaid scenarios encompass some of the most challenging scenarios that wireless networks encounter. We show that our proposed technique provisions sufficient improvements in the observed channel capacity when the receivers are close to the surface in the indoor office environment scenario. Further, we report a considerable increase in the system throughput given the outdoor environment. The work of Gabriele Gradoni was supported by the Royal Society under Grant INF\R2\192066. This work was supported in part by the European Commission through the H2020 RISE-6G Project under Grant 101017011 and in part by the EPSRC under Grant EP/V048937/1.

This paper presents the research directions pursued by the WiPLASH European project, pioneering on-chip wireless communications as a disruptive enabler towards next-generation computing systems for artificial intelligence (AI). We illustrate the holistic approach driving our research efforts, which encompass expertises and abstraction levels ranging from physical design of embedded graphene antennas to system-level evaluation of wirelessly-communicating heterogeneous systems. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 863337 (WiPLASH). Peer Reviewed Article signat per 22 autors/es: - Joshua Klein, Alexandre Levisse, Giovanni Ansaloni, David Atienza (EPFL, Lausanne, Switzerland) - Marina Zapater (HEIG-VD/HES-SO Yverdon-les-Bains, Switzerland / EPFL, Lausanne, Switzerland) - Martino Dazzi, Geethan Karunaratne, Irem Boybat, Abu Sebastian (IBM Research Europe, Zurich, Switzerland) - Davide Rossi, Francesco Conti (Università di Bologna, Bologna, Italy) - Elana Pereira de Santana, Peter Haring Bolívar (University of Siegen, Siegen, Germany) - Mohamed Saeed, Renato Negra (RWTH, Aachen, Germany) - Zhenxing Wang, Kun-Ta Wang (AMO GmbH, Aachen, Germany) - Max C. Lemme (RWTH, Aachen, Germany / AMO GmbH, Aachen, Germany) - Akshay Jain, Robert Guirado, Hamidreza Taghvaee, Sergi Abadal (Universitat Politècnica de Catalunya, Barcelona, Spain)

In this paper, an attempt has been made to understand the buying pattern of customer with the help of market basket analysis, which is an important tool in modern retailing industry. Retailing is defined as the timely delivery of goods and services demanded by end customers at prices that are competitive and affordable. Through association rule in data mining, we have tried to understand consumer behavior, brand importance, seasonality effect, buying pattern, product basket from the data. Data mining is the practice of analyzing database to gather and generate new information. Association rule mining is a process of finding rules that govern relation between sets of items. Market basket analysis is a modeling technique based upon the theory that explains the buying relation between certain groups of items. The transactional data is collected from the retail clothing store “Try Us” located in Indore, Madhya Pradesh, from the period November 26, 2017, to September 19, 2018, with the help of Point of Sale (POS) and bar code scanner. “Try Us” is a small retail store with multiple brands and is planning to upgrade store to a multilevel store. Data mining would benefit the overall store performance. Frontline Solver® Analytic Solver Data Mining (XLMiner) is used for simulations.

Structural, electronic, and magnetic properties of modified cubic spinel compound ${\mathrm{LiNi}}_{0.5}{\mathrm{Mn}}_{1.5}{\mathrm{O}}_{4}$ are studied via x-ray diffraction, resistivity, dc and ac magnetization, heat capacity, neutron diffraction, $^{7}\mathrm{Li}$ nuclear magnetic resonance, magnetocaloric effect, magnetic relaxation, and magnetic memory effect experiments. We stabilized this compound in a cubic structure with space group $P{4}_{3}32$. It exhibits semiconducting character with an electronic band gap of $\mathrm{\ensuremath{\Delta}}/{k}_{\mathrm{B}}\ensuremath{\simeq}0.4$ eV. The interaction within each ${\mathrm{Mn}}^{4+}$ and ${\mathrm{Ni}}^{2+}$ sublattice and between ${\mathrm{Mn}}^{4+}$ and ${\mathrm{Ni}}^{2+}$ sublattices is found to be ferromagnetic (FM) and antiferromagnetic (AFM), respectively. This leads to the onset of a ferrimagnetic transition at ${T}_{\mathrm{C}}\ensuremath{\simeq}125$ K. The reduced values of frustration parameter ($f$) and ordered moments reflect magnetic frustration due to competing FM and AFM interactions. From the $^{7}\mathrm{Li}$ nuclear magnetic resonance shift vs susceptibility plot, the average hyperfine coupling between $^{7}\mathrm{Li}$ nuclei and ${\mathrm{Ni}}^{2+}$ and ${\mathrm{Mn}}^{4+}$ spins is calculated to be $\ensuremath{\sim}672.4$ Oe/${\ensuremath{\mu}}_{\mathrm{B}}$. A detailed critical behavior study is done in the vicinity of ${T}_{\mathrm{C}}$ using modified-Arrott plot, Kouvel-Fisher plot, and universal scaling of magnetization isotherms. The magnetic phase transition is found to be second order in nature and the estimated critical exponents correspond to the three-dimensional XY universality class. A large magnetocaloric effect is observed with a maximum value of isothermal change in entropy $\mathrm{\ensuremath{\Delta}}{S}_{m}\ensuremath{\simeq}\ensuremath{-}11.3$ J/Kg K and a maximum relative cooling power of $\text{RCP}\ensuremath{\simeq}604$ J/Kg for 9 T magnetic field change. The imaginary part of the ac susceptibility depicts a strong frequency-dependent hump at $T={T}_{\mathrm{f}2}$ well below the blocking temperature ${T}_{\mathrm{b}}\ensuremath{\simeq}120$ K. The Arrhenius behavior of frequency dependent ${T}_{\mathrm{f}2}$ and the absence of zero-field-cooled memory confirm the existence of superparamagnetism in the ferrimagnetically ordered state.