Multiple Programs Research Articles

Evidence for managing herbivores for reef resilience.

Herbivore management is an important tool for resilience-based approaches to coral reef conservation, and evidence-based science is needed to enact successful management. We synthesized data from multiple monitoring programs in Hawai'i to measure herbivore biomass and benthic condition over a 10-year period preceding any major coral bleaching. We analysed data from 20 242 transects alongside data on 27 biophysical and human drivers and found herbivore biomass was highly variable throughout Hawai'i, with high values in remote locations and the lowest values near population centres. Both human and biophysical drivers explained variation in herbivore biomass, and among the human drivers both fishing and land-based pollution had negative effects on biomass. We also found evidence that herbivore functional group biomass is strongly linked to benthic condition, and that benthic condition is sensitive to changes in herbivore biomass associated with fishing. We show that when herbivore biomass is below 80% of potential biomass, benthic condition is predicted to decline. We also show that a range of management actions, including area-specific fisheries regulations and gear restrictions, can increase parrotfish biomass. Together, these results provide lines of evidence to support managing herbivores as an effective strategy for maintaining or bolstering reef resilience in a changing climate.

Changes in perceived stress and food or housing insecurity associated with COVID-19 in doctor of pharmacy students: A pre- and current- COVID-19 survey

BackgroundThe novel coronavirus 2019 (COVID-19) pandemic impacted everyday life for most individuals, including students. Unique COVID-19 stressors among students may include virtual learning, mental stress, and being socially distanced from classmates. Studies examining the impact of COVID-19 on stress and lifestyle changes among pharmacy students are limited. ObjectiveThe primary purpose of this study was to compare stress and food or housing insecurity changes associated with COVID-19 in U.S. Doctor of Pharmacy (PharmD) students pre-COVID vs. during-COVID. MethodsA 23-item survey was administered via Qualtrics® to multiple PharmD programs across the U.S. in pre-COVID-19 (spring 2019) and during-COVID-19 (spring 2021). Participants were recruited via e-mail. The survey included questions related to demographics, lifestyle (sleep, exercise, work hours, extracurricular activities), and food and housing insecurities. The survey also included a validated instrument to measure stress (Cohen-Perceived Stress Scale). Results from 2021 were compared to a similar national survey serendipitously administered prior to COVID-19 in Spring 2019. ResultsPre- and COVID-19 analytical cohorts included 278 and 138 participants, respectively. While pre-COVID-19 students were slightly older (29.9 ± 4.7 vs. 27.7 ± 4.2, p ≤0.001), relative to COVID-19 students, other demographic factors were similar. No significant difference was observed in reported stress levels (PSS = 20.0 ± 6.3 vs. 19.7 ± 6.2, p = 0.610) between time periods. Significant differences in food (53.2% vs. 51.4%, p = 0.731) and housing (45.0% vs. 47.1%, p = 0.680) insecurity were also not seen. ConclusionsThese findings highlight that PharmD students' perceived stress and food and housing insecurities due to COVID-19 may have been minimal. Additional studies on pharmacy students should be conducted to validate these results. These results may help inform policymakers and stakeholders during the early stages of any future pandemics.

Abstract C115: Framework for a community-based multiple myeloma screening program

Abstract Purpose: We develop a framework for a community-based screening program for multiple myeloma (MM). MM is known to be twice as common in Black/African American (B/AA) persons compared to white persons and B/AA patients have a higher risk of delay in initial treatment compared to white patients. Therefore, we developed a community-wide screening program for B/AA persons 50 years and older. As the first of these programs, we reveal an organizational framework that prioritizes engagement with key community partners who address barriers to cancer screening. Experimental Procedures: We expand organizational development knowledge about how to implement community-based MM screening and address barriers. The study uses an iterative and qualitative continuous improvement process. The study draws on literature review and multi-disciplinary team collaboration among clinicians, researchers, administrators, and the Cleveland Clinic Community Outreach Program (Cleveland Outreach). Data Summary: Our framework includes three interrelated partners and each address barriers to MM screening: 1) Cleveland Clinic Cancer Center. The multi-disciplinary team designs an educational brochure, secures pilot grant funding, plans for insurance/financial assistance as needed, develops care algorithms, and evaluates the impact of the program. Cleveland Outreach, a department within the Cancer Center, uses the Harold Freeman model as its foundational approach, which includes patient navigators and community outreach managers who are culturally/linguistically matched to medically underserved communities. The Cancer Center addresses barriers including program implementation despite a lack of national screening guidelines, insurance/financial barriers, and patient navigation to address fears and health literacy. 2) Faith-based organizations. Church leaders committed to cancer prevention participate in Cleveland Outreach’s faith-based outreach model. Faith-based partners address barriers of trust and fear. Also, by providing space at churches for on-site screening blood draws, they address transportation barriers. 3) Clinicians at Federally Qualified Health Centers (FQHC’s). Providers and nurses at FQHC’s receive a Continuing Medical Education program about MM screening designed/funded by the Cancer Center. From within the community, providers notify medically underserved patients about the screening. With their primary care patient population, FQHC partners address barriers such as trust, health literacy, and fear of blood draws. They facilitate on-site screening at FQHC’s and health fairs, which addresses transportation barriers. Conclusions: Given that there are no universal guidelines for MM screening, we develop a novel approach to early disease detection in B/AA patients. Our framework is a partnership between the Cancer Center, faith-based organizations, and FQHC’s. Collaboratively, we address barriers to screening including fear, trust, insurance/financial, health literacy, transportation, and patient navigation if abnormal results suggest the need for further testing. Citation Format: Heather McKee Hurwitz, Kimberly Bell, Diana Basali, Raymond D. Jackson II, Jason Valent. Framework for a community-based multiple myeloma screening program [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C115.

Perinatal interventions to reduce the severity of postpartum depression: A narrative review

Postpartum depression (PPD) is a mental disorder that can affect mothers and their families, with symptoms of fatigue, mood swings, frequent anger for no reason, and excessive worry for the baby. Several studies regarding interventions that can be given to postpartum women with PPD have been carried out. The purpose of this review is to assess evidence on the effectiveness of a broad range of perinatal interventions to reduce the severity of PPD. The review of the literature has been done through PubMed, for papers with Randomized Control Trial (RCT) design published in 2012-2021. The approach was to explore quantitative parameters which is the EPDS score. More than 300 papers were identified, but only 6 studies met the inclusion criteria. A narrative review was conducted due to the studies' significant heterogeneity. Six studies reported a decrease in EPDS score. Six interventions have been identified to reduce the severity of PPD, they are exercise, psychological intervention, telephone-based Cognitive Behavioral Therapy (CBT), iBA (internet Behavioral Activation), application-based Cognitive Behavioral Therapy (CBT) and psychoeducation. This review suggests that multiple intervention program may lead to better outcomes in terms of client’s satisfaction. There is also some indication that psychoeducation support Maternal Parental Self-efficacy (MPSE) and social support besides EPDS.

Impact of Preference Signals on Interview Selection Across Multiple Residency Specialties and Programs.

Background Program signaling is an innovation that allows applicants to express interest in specific programs while providing programs the opportunity to review genuinely interested applicants during the interview selection process. Objective To examine the influence of program signaling on "selected to interview" status across specialties in the 2022 Electronic Residency Application Service (ERAS) application cycle. Methods Dermatology, general surgery-categorical (GS), and internal medicine-categorical (IM-C) programs that participated in the signaling section of the 2022 supplemental ERAS application (SuppApp) were included. Applicant signal data was collected from SuppApp, applicant self-reported characteristics collected from the MyERAS Application for Residency Applicants, and 2020 program characteristics collected from the 2020 GME Track Survey. Applicant probability of being selected for interview was analyzed using logistic regression, determined by the selected to interview status in the ERAS Program Director's WorkStation. Results Dermatology had a 62% participation rate (73 of 117 programs), GS a 75% participation rate (174 of 232 programs), and IM-C an 86% participation rate (309 of 361 programs). In all 3 specialties examined, on average, signaling increased the likelihood of being selected to interview compared to applicants who did not signal. This finding held across gender and underrepresented in medicine (UIM) groups in all 3 specialties, across applicant types (MDs, DOs, international medical graduates) for GS and IM-C, and after controlling for United States Medical Licensing Examination Step 1 scores. Conclusions Although there was variability by program, signaling increased likelihood of being selected for interview without negatively affecting any specific gender or UIM group.

A Scaffolded Model for Preparing Doctoral Students to Teach in Higher Education

Even though effective teaching is required when doctoral students assume positions in higher education, few doctoral programs have courses or formalized experiences designed around pedagogy for undergraduate and graduate students. The lack of pedagogical emphasis is especially concerning for newly minted doctoral students who will be preparing future special educators to teach students with disabilities in K-12 settings. In this article, the Continuum of Teaching Experiences (CTE) Model for preparing doctoral students to teach in higher education is described. This university teaching model depicts practice opportunities that promote pedagogical learning and prepare doctoral students for independent instruction of higher education courses. The CTE model scaffolds opportunities that provide doctoral students with varied entry points across a continuum of possibilities. Additionally, the CTE model is highly adaptable across multiple doctoral preparation programs, emphasizing a malleable framework that can be refined for variable programmatic needs.

Abstract A111: Summertime fun: Findings from three cohorts of C-STEPS summer research trainees

Abstract Introduction: For the past three summers (2021-2023), a National Cancer Institute-funded R25 research education program has been underway at the University of New Mexico Comprehensive Cancer Center, entitled “Cancer Research—Scholarship and Training Experiences in Population Sciences” (C-STEPS). The program engages a diverse population of undergraduate students from across the nation in hands-on, mentored 10-week summer research education and training in cancer control and population science (CCPS). Methods: Using a data-driven methodology, the C-STEPS team has collected quantitative and qualitative data via REDCap surveys to evaluate program aims and student progress and ascertain how students experience the program to improve it for future cohorts. Students who decline admission are provided a one-time survey about the reasons they declined and asked to prioritize factors in their selection of summer research programs. Students enrolled in the program complete a pre- and post-program survey, pre- and post-seminar surveys, and a bi-annual alumni survey. The pre- and post-seminar surveys reflect expected competencies for each of the eight seminars that are part of the curriculum. The alumni survey captures academic accomplishments and career updates since completion of the summer program. Results: We have collected three years of pre/post-program data and pre/post-seminar data. Student knowledge, confidence, and interest in CCPS has steadily increased within each cohort across each of the three time periods: pre-program, immediately post-program, and alumni (1-3 years after the initial research experience). The pre/post seminar surveys indicated that the structure of the seminars inhibited interactions between the presenter and students and warranted change. We have administered the decliner and alumni survey twice each. Data from the decliner survey suggest that students apply to multiple programs each summer and the timeframe for notification to students about their acceptance may need to be shortened to give students more time to consider their C-STEPS offer in relation to other summer opportunities. Data from the alumni survey indicate that students continue to engage in research with their C-STEPS mentor and present the research at their home institution. Conclusion: Efforts to decrease the length of time between when a student applies and when they are notified of their acceptance are at the forefront of the refinement process for the next cohort. The seminars have been restructured to promote more student-led discussions and interactions between presenters and students. The CCPS research experiences and professional networks students develop during the summer have led to new educational and career opportunities. Initial evidence indicates that the success of C-STEPS extends well beyond the immediate one-time immersive research experience. Citation Format: Shoshana Adler Jaffe, Paige A. Lynch, Judith Sheche, Joseph Rodman, Miria Kano, Shiraz I. Mishra. Summertime fun: Findings from three cohorts of C-STEPS summer research trainees [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr A111.

Real-Time Collaboration in Code Development: A Comprehensive Review of Code Jett

CodeJett is a pioneering collaborative real-time code editor that serves as a beacon of innovation in the field of software development. With the increasing prevalence of remote work and distributed development teams, the need for tools that facilitate seamless collaboration among developers is paramount. CodeJett rises to this challenge by offering an array of features, including real-time synchronization, syntax highlighting, version control integration, and a built-in chat system. This paper provides a comprehensive overview of CodeJett, highlighting its significance and the evolving landscape of collaborative development tools. In a world where software development transcends borders and time zones, CodeJett acts as a unifying force, enabling developers to work together harmoniously on coding projects. The real-time nature of the tool eliminates the need for manual synchronization, enhancing productivity and reducing the likelihood of errors. CodeJett's versatility extends to its support for multiple programming languages, making it accessible to a broad spectrum of developers. This abstract underscore the role of CodeJett in facilitating collaboration, real-time development, and efficient communication within the software development community. The paper also explores the technical challenges faced in the development of CodeJett and offers insights into its future potential as a transformative tool in an ever-changing software development landscape. With keywords such as collaboration, real-time synchronization, syntax highlighting, and version control, this abstract encapsulates the essence of CodeJett's importance and its enduring impact on the field of software development.

API Recommendation For Mashup Creation: A Comprehensive Survey

Abstract Mashups are web applications that expedite software development by reusing existing resources through integrating multiple application programming interfaces (APIs). Recommending the appropriate APIs plays a critical role in assisting developers in building such web applications easily and efficiently. The proliferation of publicly available APIs on the Internet has inspired the community to adopt various models to accomplish the recommendation task. Until present, considerable efforts have been made to recommend the optimal set of APIs, delivering fruitful results and achieving varying recommendation performance. This paper presents a timely review on the topic of API recommendations for mashup creation. Specifically, we investigate and compare not only traditional data mining approaches and recommendation techniques but also more recent approaches based on network representation learning and deep learning techniques. By analyzing the merits and pitfalls of existing approaches, we pinpoint a few promising directions to address the remaining challenges in the current research. This survey provides a timely comprehensive review of the API recommendation research and could be a useful reference for relevant researchers and practitioners.

Genomic Landscape of Epstein-Barr Virus in Endemic Burkitt Lymphoma

Introduction: Endemic Burkitt lymphoma (eBL) is a fast-growing B-cell malignancy strongly linked to Epstein-Barr virus (EBV) infection, a member of the herpes virus family. The virus is widespread, infecting 95% of the global population, and has also been linked to several other cancers, including nasopharyngeal carcinoma (NPC), diffuse large B-cell lymphoma (DLBCL), Hodgkin lymphoma (HL), natural killer T-cell lymphoma (NKTCL), gastric carcinoma (GC) and leiomyosarcomas. The distribution of these cancers is inconsistent in different regions, raising the hypothesis of whether different strains are linked to specific cancers. Using high throughput sequencing, we obtained EBV whole genome sequences from the plasma of children with eBL diagnosis from a large cohort study in East Africa. Methods: Twenty-one EBV-positive patients (Sixteen BL, one diffuse large B-cell lymphoma, one lymphoblastoid lymphoma, one clear cell sarcoma, one small blue cell tumour and one alveolar rhabdomyosarcoma) were recruited from St Mary's Hospital Lacor, in Uganda, between 2020 and 2023. Venous blood samples were collected in appropriate DNA tubes, and ~ 5 ml of plasma was used for cfDNA extraction using QIAamp circulating Nucleic acid kit (Qiagen, USA). The cfDNA libraries were prepared using the Thruplex Tag- Seq kit (Takara Bio Inc. Japan), target capture and enrichment was performed using an EBV-custom panel (IDT Inc. USA) before sequencing. The Illumina fastq files were processed using an in-house pipeline, and paired-end reads were aligned to a bespoke hybrid EBV reference genome (NC_007605.1 and EBNA genes from NC_009334) using BWA with an alt-ware method. The average sequencing depth and EBV genome coverage were 5164 and 97.8%, respectively. Following the GATK best practice workflows (version 4.0), 15,318 variants were called across all samples using Varscan and Vardict after base and variant recalibration. Functional annotation was performed using the SNPEff package (v5.1d) according to the reference genome (NC_007605.1, NCBI annotation, Nov 2013). For the phylogenetic analysis, 322 public EBV genomes were downloaded from the GenBank and aligned with 21 EBV genomes from the current study using a multiple sequence alignment program (MAFFT v7.52), and the maximum likelihood of the phylogenetic relationship was inferred using RAxML (v8.0), assuming a general time reversible (GTR) model. The inferred phylogeny was subsequently rooted using the evolutionary placement (EPA) algorithm from RAxML using a Macacine herpesvirus 4 genome sequence (NC_006146) as an outer group. The tree was annotated using FigTree software (v1.4.4). The study was approved by the Oxford Tropical Research Ethics Committee (OxTREC Ref: 15-19), National Institute of Medical Research (NIMR/HQ/R.8a/Vol.IX/3408), Uganda National Council of Science and Technology (Ref: HS529ES), and St Mary's Hospital Lacor Institutional Research Ethics Committee. Participants provided written informed consent and assent for minors. Results: We examined the genomes of 21 EBV samples, including 18 type-1 and 3 type-2 strains. Our analysis revealed an average of 729 mutations per sample, comprised of 707 SNVs and 26 indels (<50bp) per sample (Figure 1). Within 16 eBL tumours, we observed the 30-bp deletion in LMP-1 in 43.8% (7/16) cases. This deletion has been previously reported in NPC in Southeast Asia and is associated with high oncogenic potential and weak immunogenicity. We also identified a novel frameshift variant (15-bp deletion) in LMP-1 in 66.7% (14/21) of tumour samples. The LMP-1 gene encodes a 356-amino acid polypeptide with a cytoplasmic amino terminus, a transmembrane domain, and a cytoplasmic carboxy terminus. The C-terminus interacts with cellular proteins, activating the transcriptional nuclear factor-kB (NF-kB) pathway associated with antiapoptotic cell signalling. Additionally, we observed a high degree of polymorphism in EBNA-1, EBNA3s, LMP-2A, BALF1, and BOLF-1 viral genes. Our phylogenetic analysis revealed distinct clustering of African EBV genomes compared to Asian strains and NPC versus eBL (Figure 2). Conclusions: Overall, our study provides the first-ever comprehensive mutational profile of EBV in eBL clinical samples, offering valuable insights into the somatic events of EBV in tumour biology.

Knowledge of Healthcare Workers about SCD in India- Barrier to “Elimination of Sickle Cell” Program

Introduction:India ranks second in SCD prevalence worldwide. The disease is more common in rural areas, with a higher density of tribal and socioeconomically challenged populations. With a special focus on the upliftment of these groups, the government has rolled multiple programs, including national sickle cell missions, aimed at early diagnosis and prevention of morbidity and mortality. Knowledge of healthcare workers (HCW) is one of the most important drivers of healthcare interventions, especially when investigations and treatments have been made accessible according to standard treatment guidelines. This study was undertaken to assess the extent of knowledge of healthcare professionals about SCD, its treatment, and management, in various parts of India, including the areas with high prevalence and low prevalence. Methods:This was an observational cross-sectional study. The questionnaire was a slightly modified DFConhecimento instrument (Deniz et al.) and was sent to HCW using a web tool to be filled through a link. The questions were in a multiple-choice setup, and participants had to choose the best response for each question. The instrument scores were calculated with one being assigned for correct answers and zero for incorrect answers (Total score-0-13) for the 13 questions copied from the original instrument. To calculate the overall knowledge of SCD, the sum of all correct answers was calculated considering the following knowledge score ranges: >7 (more than 54 % accuracy)as good or adequate knowledge and ≤ 7(54 % or less accuracy) as poor or inadequate knowledge. A minimum sample size of 384 participants was required for this study. Standard statistical methods were used for the statistical analysis. Result: A total of 416 HCW participated in this survey. The median age of the participants was 34 years, and 190 participants (45.7%) were male. Two hundred seventy-four (65.8%) participants reported providing healthcare services to patients with SCD. Fifty-nine participants (14.2%) received SCD training. The majority had experience of working long term in medical facilities-38.2 % (159/416) were working for more than 10 years. On assessing the knowledge, 52 (12.5 %) had good(adequate) knowledge and 364 (87.5%) had poor(inadequate) knowledge. In the prevalent zone, 14.7% of the HCW had adequate knowledge, and in the non-prevalent zone, only 2.6% had adequate knowledge. On univariate analysis, male sex (OR (95 CI)= 3.97 (2.04- 7.72)), doctors as HCW( OR (95 CI)= 8.010 (3.787-16.943)), postgraduate educational status(OR (95 CI)= 3.195 (1.753- 5.824)), experience of > 10 years (( OR (95 CI)= 3.550 (1.631- 7.729] ), and healthcare workers who received short training in SCD ( OR (95 CI)= (2.612 (1.313- 5.195] ) were associated with adequate knowledge. On multivariate analysis, doctors as healthcare workers (OR (95 CI)= 4.891(2.174-11)) were associated with adequate knowledge. Conclusion:According to our survey, a very low number of HCW (only 14.7%) had adequate knowledge. This situation is far from expected, even in areas where SCD is prevalent. This is an alarming situation that requires urgent attention from all the stakeholders. With the government rolling out a massive mission to eliminate SCD, poor knowledge of healthcare workers is likely to serve as a major roadblock. There is an urgent need to focus on skill development, capacity building, and empowerment of HCW in SCD. This will eventually improve the care and prognosis of SCD patients.

Association of Geographic Distance and Hospital Characteristics With Use of Interhospital Transfer by Air: A Multicenter Retrospective Study

ObjectiveInterhospital transfer by air (IHTA) represents the majority of helicopter air ambulance transports in the United States, but the evaluation of what factors are associated with utilization has been limited. We aimed to assess the association of geographic distance and hospital characteristics (including patient volume) with the use of IHTA. MethodsThis was a multicenter, retrospective study of helicopter flight request data from 2018 provided by a convenience sample of 4 critical care transport medicine programs in 3 US census regions. Nonfederal referring hospitals located in the home state of the associated critical care transport medicine program and within 100 miles of the primary receiving facility in the region were included if complete data were available. We fit a Poisson principal component regression model incorporating geographic distance, the number of emergency department visits, the number of hospital discharges, case mix index, the number of intensive care unit beds, and the number of general beds and tested the association of the variables with helicopter emergency medical services utilization. ResultsA total of 106 referring hospitals were analyzed, 21 of which were hospitals identified as having a consistent request pattern. Using the hospitals with a consistent referral pattern, geographic distance had a significant positive association with flight request volume. Other variables, including emergency department visit volume, were not associated. Overall, the included variables offered poor explanatory power for the observed variation between referring facilities in the use of IHTA (r2 = 0.09). Predicted flights based on the principal component regression model for all referring hospitals suggested the majority of referring hospitals used multiple flight programs. ConclusionGeographic distance is associated with the use of IHTA. Unexpectedly, most basic hospital characteristics are not associated with the use of IHTA, and the degree of variation between referring facilities that is explained by patient volume is limited. The evaluation of nonhospital factors, such as the density and availability of critical care or advanced life support ground emergency medical services resources, is needed.

A criterion space algorithm for solving linear multiplicative programming problems

A criterion space algorithm for solving linear multiplicative programming problems

Manipulating hidden-Markov-model inferences by corrupting batch data

Time-series models typically assume untainted and legitimate streams of data. However, a self-interested adversary may have incentive to corrupt this data, thereby altering a decision maker’s inference. Within the broader field of adversarial machine learning, this research provides a novel, probabilistic perspective toward the manipulation of hidden Markov model inferences via corrupted data. In particular, we provision a suite of corruption problems for filtering, smoothing, and decoding inferences leveraging an adversarial risk analysis approach. Multiple stochastic programming models are set forth that incorporate realistic uncertainties and varied attacker objectives. Three general solution methods are developed by alternatively viewing estimation from frequentist and Bayesian perspectives. The efficacy of each method is illustrated via extensive, empirical testing. The developed methods are characterized by their solution quality and computational effort, resulting in a stratification of techniques across varying problem-instance architectures. This research highlights the weaknesses of hidden Markov models under adversarial activity, thereby motivating the need for robustification techniques to ensure their security.

A common weights multiplicative aggregation approach for composite indicators: the case of Global City Competitiveness Index

We propose a mathematical programming approach to assess a set of entities against a composite index. The weights used to construct the composite index are derived via optimization process. Specifically, we adopt the multiplicative method for the aggregation of the components (sub-indicators) of the evaluated index, which reduces the effect of compensation between the components. Also, we model the problem of identifying a common weighting scheme for the evaluated entities as a multiple objective programming (MOP) problem, with the performance of each entity being a distinct objective-criterion. This allows for comparisons and inferences between the assessed entities as a common ground is established. We stick to the concept of multiplicative aggregation by scalarizing the MOP problem using the weighted product method. Utilizing the multiplicative aggregation method in our modelling approach results in a nonlinear model that is scale invariant. However, using logarithms we show that is straightforwardly converted to a linear equivalent model, which is translation invariant. We examine whether the derived weighting scheme is unique, and in case there are alternative optimal solutions, we employ a max–min achievement function to identify a unique solution. We demonstrate our approach using synthetic datasets and compare it to other multiplicative approaches in the literature. We show that the proposed approach has neglective computational requirements and discriminates to a greater extent than those approaches with which we are compared, while at the same time provides a similar ranking. Similarities and dissimilarities in the results are justified. Since our approach is translation invariant, it enables us to apply it to cases where the data needs translation. We further illustrate our approach for such a case using the Global City Competitiveness Index, developed by Citigroup's Economist Intelligence Unit (EIU), which evaluates the competitiveness of 120 major cities worldwide.

Multi-Threaded Data Communication in Java for Advanced Computing Environments

The performance of operating systems like computers requires the proper functioning of the computer language interpreter. This interpreter follows various types of programming languages that make the performing of computer programming easy and effective. The application of the programming language of Java helps in processing multiple tasks at once. This research analyzes the novelty of Java-based data communication models in advanced computing services. This performance makes the saving of the resources used for the development of the programming language. All these development includes the performing of the multiple threads communication data processing. These multiple threads help distribute the single processed input in the multi-channel language processing, thus helping the work competition in time. It also reduces the cost of maintaining the programming languages reduced. Thus, the implementing cost of resources required for programming performance is reduced. Therefore, this implementation impacts the programmer to become more indented to use the language transformation process of Java. Moreover, it creates a more effective representation of the audio or visual content represented by a multi-tasking operating system. In this process of development in the language transformation of the operating system, the ability of the operating system for data processing improves. The systematic process of this language transformation helps in systematically transforming multiple programs at once.

Exploring the Integration of Machine Learning Models in Programming Languages on GitHub: Impact on Compatibility to Address Them

GitHub repositories are often used for collaborative development, allowing multiple developers to work on the same codebase and contribute their changes. Each repository is typically associated with a specific project, and it can contain everything from code files to documentation, bug reports, and feature requests. Depending on the context, it can contain files, directories, other resources related to a project, and it is often associated with a particular programming language. By default, GitHub automatically detects the primary programming language used in a repository based on the file extensions and content within the repository. However, this detection is not true all the time; there are some potential issues to consider. One of these problems is that the detected language may not accurately reflect the actual programming languages used in the project, especially if the project utilizes multiple programming languages or has undergone language migrations. In this study, we apply an alternative technology to resolve problems with classifying the programming language of a GitHub repository by analysing file extensions and identifying all programming languages used in the project. We also determine the appropriate primary programming language for the repository. This paper investigates how this technology can address the issues surrounding GitHub’s automatic detection of a repository’s primary programming language and how it can provide information on all the programming languages used in a project.

Existence of solutions for polyhedral convex set optimization problems

Polyhedral convex set optimization problems are the simplest optimization problems with set-valued objective function. Their role in set optimization is comparable to the role of linear programs in scalar optimization. Vector linear programs and multiple objective linear programs provide proper subclasses. In this article, we choose a solution concept for arbitrary polyhedral convex set optimization problems out of several alternatives, show existence of solutions and characterize the existence of solutions in different ways. Two known results are obtained as particular cases, both with proofs being easier than the original ones: The existence of solutions of bounded polyhedral convex set optimization problems and a characterization of the existence of solutions of vector linear programs.

Informing extinction risk: Summarizing population viability through a meta-analysis of multiple long-term monitoring programs for a declining estuarine fish species

Decisions about whether to designate a species for conservation and protection depend on the ability to summarize their population trajectories and their risk of extinction. Such decisions may rely on quantitative population viability analyses based on a time series of abundance index values that are derived from a monitoring program. In the case of the Longfin Smelt (Spirinchus thaleichthys), a decision to protect a distinct population segment of the species under the U.S. Endangered Species Act was informed by several indices of population abundance. In this paper, we combined individual population viability analyses into a single metric for extinction risk using a meta-analysis framework. Individual monitoring surveys for this species generally agreed that the trajectory of abundance was downward, but variation introduced uncertainty. Combining data from several surveys produced a better summary of the population growth rate. We also used the population growth rates in a simulation to estimate the probability that the abundance of Longfin Smelt dropped too low to recover. We found that this probability of quasi-extinction was substantial, exceeding 20 % over two decades. This study demonstrates a practical way that having multiple sources of information creates better information about the trajectory of a population. Individually, the surveys contribute information about specific life stages or ages to our understanding of the population. Combined into one metric and an associated graphical summary, this analysis succinctly communicates risk and creates a benchmark for evaluating future management decisions.

Trial in Progress: A Phase 1 Study of KTX-1001, an Oral, First-in-Class, Selective MMSET Inhibitor in Patients with Relapsed and Refractory Multiple Myeloma

Background: Despite the development and approval of effective therapies for multiple myeloma (MM), MM remains an incurable disease. Moreover, patients with high-risk cytogenetics, like translocation t(4;14), continue to have a poor prognosis compared to standard-risk patients. No novel agents have been approved specifically for this population. There remains an unmet need for precision therapies for MM that can target specific drivers of high-risk MM like t(4;14). Multiple myeloma SET domain-containing protein (MMSET) overexpression observed in 100% of patients with t(4;14) acts through the MMSET-H3K36me2 axis, which promotes malignant transformation through regulation of multiple oncogenic programs. KTX-1001, a methyl transferase inhibitor, is a novel, first-in-class, potent, oral, small molecule that inhibits MMSET and the methylation of lysine K36. KTX-1001 had favorable drug-like properties, demonstrated in vivo activity, and was well tolerated in non-clinical studies. Based on these data, KTX-1001 is now being studied in a Phase 1 dose escalation and expansion study in relapsed and refractory multiple myeloma (RRMM). Study Design and Methods: This multi-country, Phase 1, open-label study (NCT05651932) is designed to assess the safety, tolerability, and initial clinical activity of KTX-1001. The study will also examine the recommended phase 2 dose (RP2D), pharmacokinetics (PK) and pharmacodynamics (PD). Part A of this trial includes an accelerated titration, followed by 3+3 dose escalation with backfill of cohorts for dose optimization prior to moving to Part B, which is an expansion phase at the RP2D (please see Figure 1 for study design schematic). The expansion phase will only include patients with t(4;14). KTX-1001 will be administered orally daily and given until disease progression, unacceptable toxicity, or withdrawal from the study. Estimated enrollment for Parts A and B will be approximately 60 patients. The study will enroll patients with RRMM who have received ≥3 prior lines of therapy, including a proteasome inhibitor (PI), immunomodulatory drug (IMiD), and anti-CD38 antibody. Patients must have measurable disease, be ≥18 years of age, have an Eastern Cooperative Oncology Group score of ≤2, and adequate bone marrow, liver, and kidney function. Key exclusion criteria include history of or current plasma cell leukemia, active central nervous system (CNS) disease, or active unstable cardiovascular function. The primary endpoints of safety and tolerability include incidence of dose-limiting toxicity (DLTs), treatment-emergent adverse events (AEs), and treatment-related AEs. Secondary endpoints include plasma concentrations of KTX-1001 and efficacy outcomes such as objective response rate (ORR), duration of response (DOR), progression-free survival (PFS), and overall survival (OS). Exploratory biomarker and pharmacodynamic assessments will also be performed. The sample size was not determined by formal statistical methods but will be sufficient to provide preliminary information on safety, PK, PD, and efficacy. Statistical analyses will be primarily descriptive. Conclusion: This Phase 1 study will evaluate a potential treatment for RRMM utilizing KTX-1001, which is a novel, first-in-class, potent, oral small-molecule MMSET inhibitor. The study is open and actively enrolling patients at centers in the United States, Spain, France, and Canada.