Sparse Availability Research Articles

An Open Access Resource for Marmoset Neuroscientific Apparatus.

The use of the common marmoset ( Callithrix jacchus ) for neuroscientific inquiry has grown precipitously over the past two decades. Despite windfalls of grant support from funding initiatives in North America, Europe, and Asia to model human brain diseases in the marmoset, marmoset- specific apparatus are of sparse availability from commercial vendors and thus are often developed and reside within individual laboratories. Through our collective research efforts, we have designed and vetted myriad designs for awake or anesthetized magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), as well as focused ultrasound (FUS), electrophysiology, optical imaging, surgery, and behavior in marmosets across the age- span. This resource makes these designs openly available, reducing the burden of de novo development across the marmoset field. The computer-aided-design (CAD) files are publicly available through the Marmoset Brain Connectome (MBC) resource ( https://www.marmosetbrainconnectome.org/apparatus/ ) and include dozens of downloadable CAD assemblies, software and online calculators for marmoset neuroscience. In addition, we make available a variety of vetted touchscreen and task-based fMRI code and stimuli. Here, we highlight the online interface and the development and validation of a few yet unpublished resources: Software to automatically extract the head morphology of a marmoset from a CT and produce a 3D printable helmet for awake neuroimaging, and the design and validation of 8-channel and 14- channel receive arrays for imaging deep structures during anatomical and functional MRI.

A single-center retrospective chart review of percutaneous PNS for treatment of chronic shoulder pain

ObjectiveThe present IRB-approved retrospective chart review describes the use of a 60-day PNS treatment for shoulder pain at a single center in 60 total consecutive patients. BackgroundChronic shoulder pain affects an increasing number of patients per year and is especially prevalent in elderly populations. Percutaneous peripheral nerve stimulation (PNS) treatment targeting the nerves of the shoulder has been shown to reduce pain in prospective clinical studies and in analysis of real-world data. MethodsData were extracted from the electronic medical records of patients who had previously undergone percutaneous PNS treatment for chronic shoulder pain. Demographic data and treatment characteristics were summarized alongside treatment outcomes. ResultsOverall, 84 % (49/58) of patients reported substantial (≥50 %) pain relief at the end-of-treatment. The records for 2 patients did not include patient-reported percent pain relief. The average indwelling period for leads (i.e., treatment period) was 57 days. Findings on treatment effectiveness were consistent when the patient population was stratified by cause of pain, duration living with pain, and presence of pain-modifying comorbidities. Stimulation paradigms were identified and categorized by the nerve target and stimulation frequency (e.g., motor stimulation, sensory stimulation, or bimodal stimulation). ConclusionsThese results indicate percutaneous PNS is an effective treatment for patients with various shoulder pain histories, and while all stimulation paradigms were effective at reducing pain, patients who received bimodal PNS reported the greatest pain relief. Key limitations of the study included heterogeneous shoulder pain etiologies among patients and sparse availability of long-term follow-up data. These data support existing real-world and prospective clinical evidence on the efficacy of 60-day PNS treatment at treating chronic pain and provide valuable insights into its use in clinical practice.

Enhancing predictions of protein stability changes induced by single mutations using MSA-based Language Models.

Protein Language Models offer a new perspective for addressing challenges in structural biology, while relying solely on sequence information. Recent studies have investigated their effectiveness in forecasting shifts in thermodynamic stability caused by single amino acid mutations, a task known for its complexity due to the sparse availability of data, constrained by experimental limitations. To tackle this problem, we introduce two key novelties: leveraging a Protein Language Model that incorporates Multiple Sequence Alignments to capture evolutionary information, and using a recently released mega-scale dataset with rigorous data pre-processing to mitigate overfitting. We ensure comprehensive comparisons by fine-tuning various pre-trained models, taking advantage of analyses such as ablation studies and baselines evaluation. Our methodology introduces a stringent policy to reduce the widespread issue of data leakage, rigorously removing sequences from the training set when they exhibit significant similarity with the test set. The MSA Transformer emerges as the most accurate among the models under investigation, given its capability to leverage co-evolution signals encoded in aligned homologous sequences. Moreover, the optimized MSA Transformer outperforms existing methods and exhibits enhanced generalization power, leading to a notable improvement in predicting changes in protein stability resulting from point mutations. Code and data at https://github.com/RitAreaSciencePark/PLM4Muts. Supplementary Information is available at Bioinformatics online.

Obtaining Robust Density Functional Tight-Binding Parameters for Solids across the Periodic Table.

The density functional tight-binding (DFTB) approach allows electronic structure-based simulations at length and time scales far beyond what is possible with first-principles methods. This is achieved by using minimal basis sets and empirical approximations. Unfortunately, the sparse availability of parameters across the periodic table is a significant barrier to the use of DFTB in many cases. We therefore propose a workflow that allows the robust and consistent parametrization of DFTB across the periodic table. Importantly, our approach requires no element-pairwise parameters so that the parameters can be used for all element combinations and are readily extendable. This is achieved by parametrizing all elements on a consistent set of artificial homoelemental crystals, spanning a wide range of coordination environments. The transferability of the resulting periodic table baseline parameters to multielement systems and unknown structures is explored and the model is extensively benchmarked against previous specialized and general DFTB parametrizations.

Integrating national accounting and macroeconomic approaches to estimate the underground, informal, and illegal economy in European countries

AbstractThis article proposes a hybrid national accounts (NA)-macroeconometric approach to fill the gap between the demand for reliable and internationally comparable estimates and the sparse availability of official statistics based on the NA approach. The proposed method combines data from Eurostat’s Tabular approach for the exhaustiveness of NA with estimates based on theoretical hypotheses on the drivers of non-observed production. We estimate underground, informal, and illegal economies for 22 European countries over the period 2000–2020.

Performance Analysis of Handwritten Text Augmentation on Style-Based Dating of Historical Documents

One of the main questions paleographers aim to answer while studying historical manuscripts is when they were produced. Automatized methods provide tools that can aid in a more accurate and objective date estimation. Many of these methods are based on the hypothesis that handwriting styles change over periods. However, the sparse availability of digitized historical manuscripts poses a challenge in obtaining robust systems. The presented research extends previous research that explored the effects of data augmentation by elastic morphing on the dating of historical manuscripts. Linear support vector machines were trained on k-fold cross-validation on textural and grapheme-based features extracted from the Medieval Paleographical Scale, early Aramaic manuscripts, the Dead Sea Scrolls, and volumes of the French Royal Chancery collection. Results indicate training models with augmented data can improve the performance of historical manuscript dating by 1–3% in cumulative scores, but also diminish it. Data augmentation using elastic morphing can both improve and decrease date prediction of historical manuscripts and should be carefully considered. Moreover, further enhancements are possible by considering models tuned to the features and documents’ scripts.

Perceptions of provider awareness of traditional and cultural treatments among Indigenous people who use unregulated drugs in Vancouver, Canada

IntroductionIndigenous people who use unregulated drugs (IPWUD) face significant barriers to care, including sparse availability of culturally safe health services. Integrating Indigenous traditional and cultural treatments (TCT) into health service delivery is one way to enhance culturally safe care. In a Canadian setting that implemented cultural safety reforms, we sought to examine the prevalence and correlates of client perceptions of primary care provider awareness of TCT among IPWUD.MethodsData were derived from two prospective cohort studies of PWUD in Vancouver, Canada between December 2017 and March 2020. A generalized linear mixed model with logit-link function was used to identify longitudinal factors associated with perceived provider awareness of TCT.ResultsAmong a sample of 507 IPWUD who provided 1200 survey responses, a majority (n = 285, 56%) reported their primary care provider was aware of TCT. In multiple regression analyses, involvement in treatment decisions always (Adjusted Odds Ratio [AOR] = 3.6; 95% confidence interval [CI]: 1.6–7.8), involvement in treatment decisions most or some of the time (AOR = 3.3; 95% CI: 1.4–7.7), comfort with provider or clinic (AOR = 2.7; 95% CI: 1.5–5.0), and receiving care from a social support worker (AOR = 1.5; 95% CI: 1.0–2.1) were positively associated with provider awareness of TCT.ConclusionWe found high levels of perceived provider awareness of TCT and other domains of culturally safe care within a cohort of urban IPWUD. However, targeted initiatives that advance culturally safe care are required to improve healthcare and health outcomes for IPWUD, who continue to bear a disproportionate burden of substance use harms.

A Bayesian approach to estimate annual bilateral migration flows for South America using census data

Abstract Censuses are an important source of international migration flow data. However, their use is limited since they indirectly reflect migration, capturing migrant transitions over long intervals rather than migration events, whilst also underestimating the number of infants and deaths. Censuses also neglect migration of those who are native-born when they only include questions on country of birth, and have sparse temporal availability. We propose a Bayesian hierarchical model to overcome these limitations and produce a set of robust annual migration flow estimates for South American countries. Our model translates five-year transition data from censuses into annual series, corrects biases that arise due to differences in measurement and census data quality across countries, and is grounded in migration theory to impute missing migration data between censuses.

Current Practice in Counseling about Sickle Cell Disease-Modifying Therapy and Sexual and Reproductive Health

Background: Sickle cell disease (SCD) is a genetic hematologic condition affecting individuals worldwide. Advances in therapy and management, including hydroxyurea, have reduced mortality. Clinicians who care for individuals with SCD face challenges in advising patients specifically about the impacts of hydroxyurea, a disease-modifying therapy (DMT), on sexual and reproductive health (SRH). There are currently no standard guidelines for clinicians on the risks and benefits of DMT regarding SRH. This study aims to characterize clinicians' current attitudes, practices, and barriers/facilitators to initiating and counseling around hydroxyurea use and SRH. Methods: In a cross-sectional qualitative study, we recruited clinicians caring for people with SCD from a national sample of American Society of Pediatric Hematology and Oncology members. Participants completed in-depth semi-structured interviews. Interviewers collected background information about the clinician and the nature of sickle cell care provided at their center. Topics included questions about clinicians' current practice in prescribing hydroxyurea and the counseling currently offered or the counseling they would like to provide regarding hydroxyurea and SRH. Interviews were transcribed verbatim and systematically coded using applied thematic analysis in NVivo. Results: 20 clinicians completed the interview (72% women, 78% White, 61% pediatrics-trained). Participants agreed that the benefits of decreased vaso-occlusive crises and mortality outweigh the risks of hydroxyurea to fertility. Participants also noted reduced morbidity, including decreased priapism frequency, which can lead to impotence and infertility, and reduced symptoms of dysmenorrhea. Participants concurred that counseling around hydroxyurea use varies by age, and no standard guidelines exist. When starting hydroxyurea in infants at nine months of age or at any time throughout childhood, clinicians noted that families are often hesitant at this stage to make decisions about their children that may affect their future. Families may not initiate discussions about their child's future fertility, but participants agreed that addressing the benefit and risks is essential. In contrast, clinicians reported that adolescents and young adults with SCD often direct the conversation themselves. The current practice for several participants is to continue hydroxyurea in most males or consider fertility assessment before recommending cessation of therapy, and only if they have had trouble conceiving. All participants agreed that the current practice is to take patients off hydroxyurea if they become pregnant, primarily based on teratogenicity risk and best practices from oncology. Some discussed restarting it later in pregnancy for disease control. Barriers to counseling were time constraints, limited data on whether fertility risks are related to the disease and/or the DMT, lack of standard guidelines on counseling, and sparse resource availability, including multi-disciplinary OB/GYN and genetic counseling support. Conclusion: Clinicians caring for people with SCD agree that hydroxyurea is a necessary DMT. However, clinicians also recognize the limited data and knowledge regarding the impacts of hydroxyurea on critical topics for individuals with SCD, including fertility and pregnancy. Healthcare providers who treat individuals with SCD should be aware of the unique SRH needs of this population. Further study is needed to identify patient attitudes regarding hydroxyurea and fertility risk and characterize current SRH counseling and practice in emerging disease-modifying therapies, gene therapy, and transplant.

Calibration of groundwater seepage against the spatial distribution of the stream network to assess catchment-scale hydraulic properties

Abstract. The assessment of effective hydraulic properties at the catchment scale, i.e., hydraulic conductivity (K) and transmissivity (T), is particularly challenging due to the sparse availability of hydrological monitoring systems through stream gauges and boreholes. To overcome this challenge, we propose a calibration methodology which only considers information from a digital elevation model (DEM) and the spatial distribution of the stream network. The methodology is built on the assumption that the groundwater system is the main driver controlling the stream density and extension, where the perennial stream network reflects the intersection of the groundwater table with the topography. Indeed, the groundwater seepage at the surface is primarily controlled by the topography, the aquifer thickness and the dimensionless parameter K/R, where R is the average recharge rate. Here, we use a process-based and parsimonious 3D groundwater flow model to calibrate K/R by minimizing the relative distances between the observed and the simulated stream network generated from groundwater seepage zones. By deploying the methodology in 24 selected headwater catchments located in northwestern France, we demonstrate that the method successfully predicts the stream network extent for 80 % of the cases. Results show a high sensitivity of K/R to the extension of the low-order streams and limited impacts of the DEM resolution as long the DEM remains consistent with the stream network observations. By assuming an average recharge rate, we found that effective K values vary between 1.0×10-5 and 1.1×10-4 m s−1, in agreement with local estimates derived from hydraulic tests and independent calibrated groundwater model. With the emergence of global remote-sensing databases compiling information on high-resolution DEM and stream networks, this approach provides new opportunities to assess hydraulic properties of unconfined aquifers in ungauged basins.

Training in Data Processing using Smart PLS Software

officers' limitations in their analysis of data at the population and civil registry service in Bandung. The majority of these issues are brought on by the apparatus's lack of knowledge and skill as well as the sparse availability of computers. The sub-district office does not have adequate data storage, and data management and display are not supported by technology. Implementation strategy using coaching and training. The instruction offered takes the form of fundamental knowledge on how to show district population data using Smart PLS. Its operations include instruction and support for using the Smart PLS application in the Cipadung Village to present and process data. To determine how well the trainees understood how to use the Smart PLS program, interviews and questionnaires were administered as part of the service. The customer assistance team provides clear and comprehensive explanations of the data display. The use of this Smart PLS software aids Kelurahan staff in comprehending and processing data. It is beneficial to sub-district authorities in their work with the taught apps.

HydroWidth: A small‐scale approach to calculate river width and its variability

AbstractDigital map processing techniques have enabled new computational methods to extract geographic features from scanned map sources. These are mainly historical maps and are rich in spatiotemporal information which can be derived by descriptive metrics. River channel width is such a typical ecological metric used to calculate properties such as water discharge rates and, generally, often applied in hydrological and ecological monitoring. Measures of river channel width in previous ecological work have successfully measured width based on in situ measurements or remote sensing efforts, but poorly captured the variability in river width due to simplifications of the river network or due to sparse availability of in situ measurements. As river width can greatly vary and change over space and time, capturing its variability with modern geospatial processing techniques is a key interest in interdisciplinary fields studying spatiotemporal changes of riverine properties. This article proposes HydroWidth, a small‐scale approach to measure river width continuously along a channel, capable of capturing the variability in width in simple as well as complex river structures without the use of river masks. The small‐scale approach is compared to two conventional vector‐based discrete river width measurement techniques to test the robustness of the methods in terms of measuring river width and its variability. Furthermore, this article evaluates the adaptability of HydroWidth by performing three experiments measuring river width variability at rivers of different structure, length, and complexity. The methods are applied on rivers of historical map sources, allowing a novel perspective of applying algorithms measuring river width on non‐airborne data sources. Lastly, the computational performance results of the conventional and HydroWidth methods at each experimental site are presented and discussed.

Developing an Artificial Intelligence-Guided Signal Detection in the Food and Drug Administration Adverse Event Reporting System (FAERS): A Proof-of-Concept Study Using Galcanezumab and Simulated Data.

Time- and resource-demanding activities related to processing individual case safety reports (ICSRs) include manual procedures to evaluate individual causality with the final goal of dismissing false-positive safety signals. Eminent experts and a representative from pharmaceutical industries and regulatory agencies have highlighted the need to automatize time- and resource-demanding procedures in signal detection and validation. However, to date there is a sparse availability of automatized tools for such purposes. ICSRs recorded in spontaneous reporting databases have been and continue to be the cornerstone and the most important data source in signal detection. Despite the richness of this data source, the incessantly increased amount of ICSRs recorded in spontaneous reporting databases has generated problems in signal detection and validation due to the increase in resources and time needed to process cases. This study aimed to develop a new artificial intelligence (AI)-based framework to automate resource- and time-consuming steps of signal detection and signal validation, such as (1) the selection of control groups in disproportionality analyses and (2) the identification of co-reported drugs serving as alternative causes, to look to dismiss false-positive disproportionality signals and therefore reduce the burden of case-by-case validation. The Summary of Product Characteristics (SmPC) and the Anatomical Therapeutic Chemical (ATC) classification system were used to automatically identify control groups within and outside the chemical subgroup of the proof-of-concept drug under investigation, galcanezumab. Machine learning, specifically conditional inference trees, has been used to identify alternative causes in disproportionality signals. By using conditional inference trees, the framework was able to dismiss 20.00% of erenumab, 14.29% of topiramate, and 13.33% of amitriptyline disproportionality signals on the basis of purely alternative causes identified in cases. Furthermore, of the disproportionality signals that could not be dismissed purely on the basis of the alternative causes identified, we estimated a 15.32%, 25.39%, and 26.41% reduction in the number of galcanezumab cases to undergo manual validation in comparison with erenumab, topiramate, and amitriptyline, respectively. AI could significantly ease some of the most time-consuming and labor-intensive steps of signal detection and validation. The AI-based approach showed promising results, however, future work is needed to validate the framework.

Abstract 1918: Reducing human papillomavirus associated cancers and disparities among Hispanics/Latinos through the adapted NCI NON CHE (National Outreach Network Community Health Education) program

Abstract While HPV vaccination has dramatically reduced HPV-related cancer incidences in certain demographic groups, it continues to disproportionately affect Hispanics/Latinos. The NON CHE program at (USC), (NCCC), aims to understand the gaps in Human Papillomavirus (HPV) knowledge and vaccination uptake, cervical cancer screenings, and addresses the barriers to participating in clinical trials (CT) by conducting culturally-sensitive educational workshops to the community. Methods: Materials such as a PowerPoint presentation and Human Papillomavirus Vaccination (HPV) infographics were adapted by the NCI to ensure the message can influence the target audience. Educational workshops were conducted via Zoom. Recruitment of participants were facilitated by partnering with community organizations across Los Angeles County (LAC) which is NCCC’s catchment area. The effectiveness of the workshops was assessed by delivery of pre and post surveys that captured demographics and a series of true and false questions that measured HPV knowledge. 3- and 6-month follow-up surveys are distributed among participants of those of age 18 - 26 and to parents of children 9 - 18 years of age to assess vaccination intake. Results: A total of 1,515 people have been reached during educational workshops, health fairs, and outreach events from October 2021 to September 2022. Our results demonstrate that the 236 participants, (55.6%) Spanish-speaking and (26.9%) English-speaking had not heard of HPV indicating the sparse availability and accessibility of information contributing to parents’ unfamiliarity of the HPV vaccine (79.5%) between the two groups. However, there was a positive distribution of likely to get vaccine (72.88%) and likely to vaccinate their children (47.88%.) Their lack of awareness stemmed from lack of provider motivation (44.2%) and limited health education (39.5%.) Conclusion: Conducting culturally tailored educational workshops to disseminate information on Human Papillomavirus (HPV) has helped Hispanics/Latinos understand what HPV is and reduce the stigma. Effective dissemination of HPV education requires it to be inclusive, concise, and engaging to motivate community members to seek preventive care. Citation Format: Alejandra Ramos, Carolina Aristizabal, Lourdes Baezconde-Garbanati. Reducing human papillomavirus associated cancers and disparities among Hispanics/Latinos through the adapted NCI NON CHE (National Outreach Network Community Health Education) program [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1918.

A Novel Operational Rice Mapping Method Based on Multi-Source Satellite Images and Object-Oriented Classification

Combining optical and synthetic aperture radar (SAR) data for crop mapping has become a crucial way to improve classification accuracy, especially in cloudy and rainy areas. However, the acquisition of optical images is significantly unstable due to the influence of cloudy and rainy weather, which seriously restricts the application of this method in practice. To solve this problem, this study proposed an optical-SAR imagery-based rice mapping method which has the advantages of less dependence on optical images, easy operation and high classification accuracy. To account for the trait of sparse availability of optical images, this method only needs one clear sky optical image in the rice growth period and combined it with multi-temporal SAR images to achieve a high accuracy rice mapping result. Meanwhile, this paper also proposed a comprehensively multi-scale segmentation parameter optimization algorithm, which considers the area consistency, shape error and location difference between the segmented object and reference object, and adopts an orthogonal experiment approach. Based on the optical image, the boundaries of the parcel objects can be segmented, which were subsequently used to perform the object-oriented classification. The results show that the overall accuracy of the proposed method in Yangzhou City is 94.64%. Moreover, according to a random pick test, it is encouraging that the proposed method has strong robustness in response to the instability of the acquisition time of SAR images. A relatively high overall accuracy of 90.09% suggested that the proposed method can provide a reliable rice mapping result in cloudy and rainy areas.

Marker-free characterization of full-length transcriptomes of single live circulating tumor cells.

The identification and characterization of circulating tumor cells (CTCs) are important for gaining insights into the biology of metastatic cancers, monitoring disease progression, and medical management of the disease. The limiting factor in the enrichment of purified CTC populations is their sparse availability, heterogeneity, and altered phenotypes relative to the primary tumor. Intensive research both at the technical and molecular fronts led to the development of assays that ease CTC detection and identification from peripheral blood. Most CTC detection methods based on single-cell RNA sequencing (scRNA-seq) use a mix of size selection, marker-based white blood cell (WBC) depletion, and antibodies targeting tumor-associated antigens. However, the majority of these methods either miss out on atypical CTCs or suffer from WBC contamination. We present unCTC, an R package for unbiased identification and characterization of CTCs from single-cell transcriptomic data. unCTC features many standard and novel computational and statistical modules for various analyses. These include a novel method of scRNA-seq clustering, named deep dictionary learning using k-means clustering cost (DDLK), expression-based copy number variation (CNV) inference, and combinatorial, marker-based verification of the malignant phenotypes. DDLK enables robust segregation of CTCs and WBCs in the pathway space, as opposed to the gene expression space. We validated the utility of unCTC on scRNA-seq profiles of breast CTCs from six patients, captured and profiled using an integrated ClearCell FX and Polaris workflow that works by the principles of size-based separation of CTCs and marker-based WBC depletion.

Acoustic Signals of a Meteoroid Recorded on a Large-NSeismic Network and Fiber-Optic Cables

AbstractA common challenge in acoustic meteoroid signal analyses is to discriminate whether the observed wavefield can be better described by line-source or point-source models. This challenge typically arises from a sparse availability of observations. In this work, we present an outstanding record of ground-coupled waves from local large-N seismic and distributed acoustic sensing (DAS) observations of a meteoroid in Iceland. Our complete data set includes additional regional stations located within 300 km of the meteoroid’s trajectory. The dense large-N and DAS data allow identification of acoustic phases that are almost impossible to discriminate on sparser networks, including a weak late arrival resolved mostly only by DAS. Using this data set with a new Bayesian inversion model, we estimate the trajectory parameters of one fragment from the meteoroid. With these results we investigate its orbit in the solar system and propose a classification of the Icelandic event as a slow meteoroid of asteroidal origin with an energy on the order of 4–40 GJ, a probable size on the order of centimeters, and an orbit range consistent with the main asteroid belt.

Going Back to Get the Stories

In the United States, children’s book publishing experienced significant shifts throughout the 20th century, starting with the establishment of dedicated children’s books departments in the 1920’s through to late century changes in printing technology leading to the cost-effective publication of full color non-fiction for youth. Each generation experienced children’s books differently.
 One constant was the sparse availability of books representing any child who was not white. As in Rudine Sims Bishop’s analogy, these youth easily found windows and sliding glass doors in their books but rarely found the self-affirming mirror. Conversely, white children had many mirrors but far fewer opportunities to view unfamiliar experiences nor enter new worlds to discover empathy for others.
 Today’s children are growing up with increasingly diverse representation in the available literature. To fully understand the significance of this moment, we must “go back and get” the experiences of the children who grew up in the 20th century. In this oral history project, we collect individual’s memories of reading and stories from their youngest years through adolescence. Participants are drawn from diverse backgrounds, with an emphasis on people who identify as Black, Latinx, Asian, and/or Indigenous. Findings illuminate the overlooked literacy experiences of people of color and the impact of childhood reading. This project provides insight into the historical impact of library services and the importance of contemporary libraries providing children with diverse literature.

Multiple transformation analysis for interference separation in TDCS

Various types of interference signals limit the practical application of transform domain communication systems (TDCSs) in the severe electromagnetic field, an orthogonal basis learning method of transformation analysis (OBL-TA) is proposed to effectively address the problem of obtaining an optimal transform domain based on sparse representation. Then, the sparse availability is utilized to obtain the optimal transformation analysis by the iterative methods, which yields the sparse representation for transform domain (SRTD) in unrestricted form. In addition, the iterative version of SRTD (I-SRTD) in unrestricted form is obtained by decomposing the SRTD problem into three sub-problems and each sub-problem is iteratively solved by learning the best orthogonal basis. Furthermore, orthogonal basis learning via cost function minimization process is conducted by stochastic descent, which is assured to converge to a local minimum at least. Finally, the optimal transformation analysis is developed by the effectiveness of different transform domains according to the accuracy of the sparse representation and an optimal transformation analysis separately (OPTAS) is applied to the synthesized signal forms with conic alternatives, dualization, and smoothing. Simulation results demonstrate that the superiorities of the proposed methods achieve the optimal recovery and separation more rapidly and accurately than conventional methods.

Traditional Architecture of Ikwerre Land. A Case Study of Emohua: Cradle to Post Modernism

The speedy exit of traditional values and culture is evident in all facets of human life and practice; architectural practice included. Due to the impacts of globalisation and industrialisation, certain negative effects have surfaced in every aspect of life. In Nigeria today, most people’s desire for “modern” cement homes built as opposed to the now archaic buildings of old, may render them stoic and uncompromising. As a result, many may prefer to go without a roof over their heads than make do with old-fashioned buildings of mud and clay. The report is more of picturesque ethnographical studies of the architecture of Rumuche Emohua. Through the study, basic characteristics are presented. Rumuche Emohua a town in Emohua local government area, Rivers State, Nigeria consists of indigenes who venture, largely, into occupations such as farming, fishing, and hunting as a result of the availability of land and such natural resources. In this report, the ethnological research approach was adopted so that the people’s architectural character is documented and presented in this report. In this report, the family lineage of a young man who is mature for family responsibility development is allowed a home in the style of I-home architecture. From this, the growth of his family causes the house to evolve into the family setting home structure called the courtyard dwelling. Both the single and courtyard homes have certain fizzled features that remain in spite of the change such as the family well, the kitchen, and the toilet/bathroom. Although, the kitchen is increased to carry activities posed by the expanded family size, the family well remains a fixed central place. Due to the impacts of industrialisation, the traditional construction method to has been eradicated, although some traces of the courtyard and single home settings are still existent. Part of the factors that impacted to this, is the sparse availability of land due to a rise in population. Also presented are basic construction methods and materials. All of these are recorded for future use, due to the continuous extinction of the traditional features in today’s society, particularly in the Rumuche Emohua community.