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Sustainable improvement of food SMEs through halal certification: A meta-analysis

AIP Conference Proceedings 2024年第1期2957卷

作者： Rizal Bahara Muhammad N. Aidi Khaswar Syamsu Euis Sunarti Anuraga Jayanegara Natural Resources and Environmental Management Science Study Program Graduate School IPB University Jl Pajajaran No 1 Kampus IPB Baranangsiang Bogor West Java 1614 Indonesia Statistics and Data Science Department Mathematics and Natural Science Faculty IPB University Jl. Lingkar Kampus IPB Dramaga Bogor West Java 16680 Indonesia Halal Science Center LPPM IPB. Gedung Pascasarjana Gedung Kimia IPB University Jl Pajajaran No 1 Kampus IPB Baranangsiang Bogor West Java 1644 Indonesia Department of Family and Consumer Sciences Faculty of Human Ecology IPB University Jl. Lingkar Kampus IPB Dramaga Bogor West Java 16610 Indonesia Department of Nutrition and Feed Technology Faculty of Animal Science IPB University Jl. Lingkar Kampus IPB Dramaga Bogor West Java 16680 Indonesia

Small and medium enterprises (SMEs) are one of the important economic drivers in Indonesia, including during the Covid-19 pandemic. Indonesia as the country with the largest Muslim population requires halal certificates for all food products sold in Indonesia. Obstacles to the implementation and certification of halal in the food SME sector are still encountered due to, among others, the cost of certification, knowledge from human resources, ease of access and information. The purpose of this study was to evaluate the role of halal certification on financial performance in Food SMEs by employing the meta-analysis method. A number of six articles out of 55 articles were selected and integrated into a database. The data were analyzed based on the Hedges’ d (standardized mean difference/SMD) effect size values and confidence interval (CI) values by using the Open MEE software. The results showed that halal-certified food SMEs significantly increased sales (SMD: 3.182; 95% CI:1.228 to 5.136; p<0.001) as compared to those of food SMEs that were not halal-certified. In the location in the Indonesia subgroup, halal certification at Food SMEs in Bogor city had a higher sale (SMD: 12.105; 95% CI: 10.289 to 13.922; p<0.001) compared to other cities. The conclusion of this study is that halal certification enhances sales and thus contributes to the sustainability of food SMEs.

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Weakly Supervised AI for Efficient Analysis of 3D Pathology Samples

arXiv

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arXiv 2023年

作者： Song, Andrew H. Williams, Mane Williamson, Drew F.K. Jaume, Guillaume Zhang, Andrew Chen, Bowen Serafin, Robert Liu, Jonathan T.C. Baras, Alex Parwani, Anil V. Mahmood, Faisal Department of Pathology Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Pathology Massachusetts General Hospital Harvard Medical School BostonMA United States Cancer Program Broad Institute of Harvard and MIT CambridgeMA United States Data Science Program Dana-Farber Cancer Institute BostonMA United States Department of Biomedical Informatics Harvard Medical School BostonMA United States Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology CambridgeMA United States Department of Mechanical Engineering Bioengineering Laboratory Medicine & Pathology University of Washington SeattleWA United States Department of Pathology Johns Hopkins Hospital BaltimoreMD United States Department of Biomedical Engineering Johns Hopkins Hospital BaltimoreMD United States Department of Pathology The Ohio State University ColumbusOH United States

Human tissue consists of complex structures that display a diversity of morphologies, forming a tissue microenvironment that is, by nature, three-dimensional (3D). However, the current standard-of-care involves slicing 3D tissue specimens into two-dimensional (2D) sections and selecting a few for microscopic evaluation1,2, with concomitant risks of sampling bias and misdiagnosis3–6. To this end, there have been intense efforts to capture 3D tissue morphology and transition to 3D pathology, with the development of multiple high-resolution 3D imaging modalities7–18. However, these tools have had little translation to clinical practice as manual evaluation of such large data by pathologists is impractical and there is a lack of computational platforms that can efficiently process the 3D images and provide patient-level clinical insights. Here we present Modality-Agnostic Multiple instance learning for volumetric Block Analysis (MAMBA), a deep-learning-based platform for processing 3D tissue images from diverse imaging modalities and predicting patient outcomes. Archived prostate cancer specimens were imaged with open-top light-sheet microscopy12–14 or microcomputed tomography15,16 and the resulting 3D datasets were used to train risk-stratification networks based on 5-year biochemical recurrence outcomes via MAMBA. With the 3D block-based approach, MAMBA achieves an area under the receiver operating characteristic curve (AUC) of 0.86 and 0.74, superior to 2D traditional single-slice-based prognostication (AUC of 0.79 and 0.57), suggesting superior prognostication with 3D morphological features. Further analyses reveal that the incorporation of greater tissue volume improves prognostic performance and mitigates risk prediction variability from sampling bias, suggesting that there is value in capturing larger extents of spatially heterogeneous 3D morphology. With the rapid growth and adoption of 3D spatial biology and pathology techniques by researchers and clinicians, M

关键词： Pathology

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Adjacent segment disease following Dynesys stabilization for lumbar disorders:A case series of mid-and long-term follow-ups

引用

World Journal of Clinical Cases 2021年第35期9卷 10850-10860页

作者： Kuan-Ju Chen Chien-Ying Lai Lu-Ting Chiu Wei-Sheng Huang Pang-Hsuan Hsiao Chien-Chun Chang Cheng-Jyh Lin Yuan-Shun Lo Yen-Jen Chen Hsien-Te Chen Department of Orthopedic Surgery China Medical University HospitalTaichung City 404Taiwan Spine Center China Medical University HospitalTaichung City 404Taiwan Management Office for Health Data China Medical University HospitalTaichung City 404Taiwan College of Medicine China Medical UniversityTaichung City 404Taiwan School of Chinese Medicine China Medical UniversityTaichung City 404Taiwan Department of Orthopedic Surgery China Medical University HospitalChina Medical UniversityTaichung City 404Taiwan Spine Center China Medical University HospitalChina Medical UniversityTaichung City 404Taiwan Degree Program of Biomedical Science and Engineering National Chiao Tung UniversityHsinchu City 300Taiwan Department of Biological Science and Technology National Chiao Tung UniversityHsinchu City 300Taiwan Department of Orthopedic Surgery China Medical University Beigang HospitalYunlin County 651Taiwan Graduate Institute of Precision Engineering National Chung Hsing UniversityTaichung City 404Taiwan School of Medicine China Medical UniversityTaichung City 404Taiwan Department of Sport Medicine College of Health CareChina Medical UniversityTaichung City 404Taiwan

BACKGROUND Radiologic adjacent segment degeneration(ASDeg)can occur after spinal *** segment disease(ASDis)is defined as the development of new clinical symptoms corresponding to radiographic changes adjacent to the level of previous spinal *** pre-existing ASDeg is generally considered to result in more severe ASDis;nonetheless,whether the ASDeg status before index surgery influences the postoperative risk of revision surgery due to ASDis warrants *** To identify possible risk factors for ASDis and verify the concept that greater preexisting ASDeg leads to more severe *** data from 212 patients who underwent posterior decompression with Dynesys stabilization from January 2006 to June 2016 were retrospectively *** who underwent surgery for ASDis were categorized as group A(n=13),whereas those who did not were classified as group B(n=199).Survival analysis and Cox proportional hazards models were used to compare the modified Pfirrmann grade,University of California-Los Angeles grade,body mass index,number of Dynesys-instrumented levels,and *** The mean time of reoperation was 7.22(1.65–11.84)years in group A,and the mean follow-up period was 6.09(0.10–12.76)years in group *** significant difference in reoperation risk was observed:Modified Pfirrmann grade 3 vs 4(P=0.53)or 4 vs 5(P=0.46)for the upper adjacent disc,University of California-Los Angeles grade 2 vs 3 for the upper adjacent segment(P=0.66),age of<60 vs>60 years(P=0.9),body mass index<25 vs>25 kg/m2(P=0.3),and sex(P=0.8).CONCLUSION Greater preexisting upper ASDeg was not associated with a higher rate of reoperation for ASDis after Dynesys *** overweight tended to increase reoperation risk after Dynesys surgery for ASDis.

关键词： Adjacent segment degeneration Adjacent segment disease Degenerative lumbar spondylolisthesis Dynamic stabilization Dynesys Spinal stenosis

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Finite-time Analysis of Globally Nonstationary Multi-Armed Bandits

arXiv

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arXiv 2021年

作者： Komiyama, Junpei Fouché, Edouard Honda, Junya Stern School of Business New York University 44 West 4th Street New YorkNY United States Institute for Program Structures and Data Organization Karlsruhe Institute of Technology Am Fasanengarten 5 Karlsruhe76131 Germany Department of Systems Science Graduate School of Informatics Kyoto University Yoshida Honmachi Sakyo-ku Kyoto606-8501 Japan

We consider nonstationary multi-armed bandit problems where the model parameters of the arms change over time. We introduce the adaptive resetting bandit (ADR-bandit), a bandit algorithm class that leverages adaptive windowing techniques from literature on data streams. We first provide new guarantees on the quality of estimators resulting from adaptive windowing techniques, which are of independent interest. Furthermore, we conduct a finite-time analysis of ADR-bandit in two typical environments: an abrupt environment where changes occur instantaneously and a gradual environment where changes occur progressively. We demonstrate that ADR-bandit has nearly optimal performance when abrupt or gradual changes occur in a coordinated manner that we call global changes. We demonstrate that forced exploration is unnecessary when we assume such global changes. Unlike the existing nonstationary bandit algorithms, ADR-bandit has optimal performance in stationary environments as well as nonstationary environments with global changes. Our experiments show that the proposed algorithms outperform the existing approaches in synthetic and real-world environments. © 2021, CC BY.

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Phase I Study of Ixazomib with Conventional Chemotherapy in the Treatment of Acute Myeloid Leukemia in Older Adults

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BLOOD 2020年 136卷 7-8页

作者： Amrein, Philip C. Attar, Eyal C. Fell, Geoffrey Blonquist, Traci M. Brunner, Andrew M. Hobbs, Gabriela S. Hock, Hanno R. McAfee, Steven L. Narayan, Rupa Moran, Jenna A. Bergeron, Meghan Foster, Julia E. Bertoli, Christina McGregor, Kristin Macrae, Molly Burke, Meghan Behnan, Tanya T. Som, Tina T. Ramos, Aura Y. Vartanian, Megan K. Story, Jennifer Lombardi Neuberg, Donna S. Fathi, Amir T. Leukemia Center/MGH Cancer Center Massachusetts General Hospital Belmont MA Agios Boston MA Data Science Dana-Farber Cancer Institute Boston MA Center for Leukemia Massachusetts General Hospital Boston MA Leukemia Center Massachusetts General Hospital Boston MA Leukemia Center Massachusetts General Hospital / Harvard Medical School Boston MA Massachusetts General Hospital Blood and Marrow Transplant Program Boston MA Leukemia Center Massachusetts General Hospital Center for Leukemia Cambridge MA

Introduction: Outcomes for acute myeloid leukemia (AML) among older patients has remained largely unchanged for decades. Long-term survival for patients aged >60 years is poor (median survival 10.5 months). Targeting the proteasome in AML is attractive, since leukemia stem cells have demonstrated sensitivity to proteasome inhibition in preclinical models, perhaps through down regulation of nuclear NF-KB (Guzman, Blood 2001). AML cell lines are susceptible to synergistic cytotoxicity when bortezomib, a proteasome inhibitor, is combined with daunorubicin and cytarabine. We have shown that adding bortezomib to standard treatment in AML results in a high remission rate, although grade 2 sensory neurotoxicity was noted in approximately 12% of treated patients. A newer generation proteasome inhibitor, ixazomib, is less frequently associated with neurotoxicity, and, therefore, was selected for combination with conventional chemotherapy in this phase I trial. The primary objective of this study was to determine the maximum tolerated dose (MTD) of ixazomib in combination with conventional induction and consolidation chemotherapy for AML. Herein are the initial results of this trial. Methods: Adults >60 years of age with newly diagnosed AML were screened for eligibility. Patients with secondary AML were eligible, including those with prior hypomethylating agent therapy for myelodysplastic syndromes (MDS). We excluded those with promyelocytic leukemia. There were 2 phases in this study. In the first phase (A), the induction treatment consisted of the following: cytarabine 100 mg/m2/day by continuous IV infusion, Days 1-7; daunorubicin 60 mg/m2/day IV, Days 1, 2, 3, and ixazomib was provided orally at the cohort dose, Days 2, 5, 9, and 12. Consolidaton or transplant was at the discretion of the treating physician in phase A. In the second phase (B), induction was the same as that with the determined MTD of ixazomib. All patients were to be treated with the following consolidati

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Advising big data transfer over dedicated connections based on profiling optimization

Advising big data transfer over dedicated connections based ...

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作者： Yun, Daqing Wu, Chase Q. Rao, Nageswara S. V. Kettimuthu, Rajkumar Computer and Information Sciences Program Harrisburg University HarrisburgPA17101 United States Department of Computer Science New Jersey Institute of Technology NewarkNJ07102 United States Computer Science and Mathematics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Data Science and Learning Division Argonne National Laboratory ArgonneIL60439 United States

Big data transfer in next-generation scientific applications is now commonly carried out over dedicated channels in high-performance networks (HPNs), where transport protocols play a critical role in maximizing application-level throughput. Optimizing the performance of these protocols is challenging: i) transport protocols perform differently in various network environments, and the protocol choice is not straightforward;ii) even for a given protocol in a given environment, different parameter settings of the protocol may lead to significantly different performance and oftentimes the default setting does not yield the best performance. However, it is prohibitively time-consuming to conduct exhaustive transport profiling due to the large parameter space. In this paper, we propose a PRofiling Optimization Based data Transfer Advisor (Probdata) to help end users determine the most effective transport method with the most appropriate parameter settings to achieve satisfactory performance for big data transfer over dedicated connections in HPNs. Probdata employs a fast profiling scheme based on the Simultaneous Perturbation Stochastic Approximation algorithm, namely, FastProf, to accelerate the exploration of the optimal operational zones of various transport methods to improve profiling efficiency. We first present a theoretical background of the optimized profiling approach in Probdata and then detail its design and implementation. The advising procedure and performance benefits of FastProf and Probdata are illustrated and evaluated by both extensive emulations based on real-life performance measurements and experiments over various physical connections in existing production HPNs. © 1993-2012 IEEE.

关键词： data transfer

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How the world’s collective attention is being paid to a pandemic: COVID-19 related 1-gram time series for 24 languages on Twitter

arXiv

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arXiv 2020年

作者： Alshaabi, Thayer Arnold, Michael V. Minot, Joshua R. Adams, Jane Lydia Dewhurst, David Rushing Reagan, Andrew J. Muhamad, Roby Danforth, Christopher M. Dodds, Peter Sheridan Computational Story Lab Vermont Complex Systems Center MassMutual Center of Excellence for Complex Systems and Data Science Vermont Advanced Computing Core University of Vermont BurlingtonVT05401 MassMutual Data Science AmherstMA01002 International Class Program Faculty of Social and Political Sciences University of Indonesia Jakarta Indonesia Department of Mathematics & Statistics University of Vermont BurlingtonVT05401 United States

In confronting the global spread of the coronavirus disease COVID-19 pandemic we must have coordinated medical, operational, and political responses. In all efforts, data is crucial. Fundamentally, and in the possible absence of a vaccine for 12 to 18 months, we need universal, well-documented testing for both the presence of the disease as well as confirmed recovery through serological tests for antibodies, and we need to track major socioeconomic indices. But we also need auxiliary data of all kinds, including data related to how populations are talking about the unfolding pandemic through news and stories. To in part help on the social media side, we curate a set of 1000 day-scale time series of 1-grams across 24 languages on Twitter that are most ‘important’ for March 2020 with respect to March 2019. We determine importance through our allotaxonometric instrument, rank-turbulence divergence. We make some basic observations about some of the time series, including a comparison to numbers of confirmed deaths due to COVID-19 over time. We broadly observe across all languages a peak for the language-specific word for ‘virus’ in January followed by a decline through February and a recent surge through March. The world’s collective attention dropped away while the virus spread out from China. We host the time series on Gitlab, updating them on a daily basis while relevant. Our main intent is for other researchers to use these time series to enhance whatever analyses that may be of use during the pandemic as well as for retrospective investigations. Copyright © 2020, The Authors. All rights reserved.

关键词： Time series

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Homogenisation for the monodomain model in the presence of microscopic fibrotic structures

arXiv

引用

arXiv 2020年

作者： Lawson, Brodie A.J. dos Santos, Rodrigo Weber Turner, Ian W. Bueno-Orovio, Alfonso Burrage, Pamela Burrage, Kevin Centre for Data Science Queensland University of Technology QLD Australia ARC Centre of Excellence for Mathematical and Statistical Frontiers Queensland University of Technology QLD Australia Graduate Program on Computational Modeling Universidade de Juiz de Fora Minas Gerais Brazil Department of Computer Science University of Oxford Oxfordshire United Kingdom

MSC Codes 35B27Computational models in cardiac electrophysiology are notorious for long runtimes, restricting the numbers of nodes and mesh elements in the numerical discretisations used for their solution. This makes it particularly challenging to incorporate structural heterogeneities on small spatial scales, preventing a full understanding of the critical arrhythmogenic effects of conditions such as cardiac fibrosis. In this work, we explore the technique of homogenisation by volume averaging for the inclusion of non-conductive micro-structures into larger-scale cardiac meshes with minor computational overhead. Importantly, our approach is not restricted to periodic patterns, enabling homogenised models to represent, for example, the intricate patterns of collagen deposition present in different types of fibrosis. We first highlight the importance of appropriate boundary condition choice for the closure problems that define the parameters of homogenised models. Then, we demonstrate the technique’s ability to correctly upscale the effects of fibrotic patterns with a spatial resolution of 10 µm into much larger numerical mesh sizes of 100-250 µm. The homogenised models using these coarser meshes correctly predict critical pro-arrhythmic effects of fibrosis, including slowed conduction, source/sink mismatch, and stabilisation of re-entrant activation patterns. As such, this approach to homogenisation represents a significant step towards whole organ simulations that unravel the effects of microscopic cardiac tissue heterogeneities. © 2020, CC BY.

关键词： Heart

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Estimating the number of infected cases in COVID-19 pandemic

arXiv

引用

arXiv 2020年

作者： Yan, Donghui Xu, Ying Wang, Pei Department of Mathematics and Program in Data Science University of Massachusetts DartmouthMA02747 United States Indigo Agriculture Inc BostonMA United States Icahn School of Medicine at Mount Sinai NYCNY United States

The COVID-19 pandemic has caused major disturbance to human life. An important reason behind the widespread social anxiety is the huge uncertainty about the pandemic. A fundamental uncertainty is how many or what percentage of people have been infected. There are published and frequently updated data on various statistics of the pandemic, at local, country or global level. However, due to various reasons, many cases were not included in those reported numbers. We propose a structured approach for the estimation of the number of unreported cases, where we distinguish cases that arrive late in the reported numbers and those who had mild or no symptoms and thus were not captured by any medical system at all. We use post-report data for the estimation of the former and population matching to the latter. We estimate that the reported number of infected cases in the US should be corrected by multiplying a factor of 220.54% as of Apr 20, 2020, while the infection ratio out of the US population is estimated to be 0.53%, implying a case mortality rate at 2.85% which is close to the 3.4% suggested by the WHO in Mar 2020. Towards the end of the summer of 2020, the overall infection ratio of the US rises to 2.49% while the case mortality decreases to 2.09%, and the ratio of asymptomatic cases out of all infected cases reduces from the pre-summer 35-40% to around 20-25%. © 2020, CC BY-NC-ND.

关键词： Population statistics

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Factors associated with mortality in thoracic trauma patients in Cameroon

引用

Heliyon 2025年第1期11卷 e41499页

作者： Kibu, Odette Dzemo Nguefack-Tsague, Georges Maqungo, Sithombo Ngekeng, Serge Dissak Delon, Fanny Nadia Touko, Darwin Oke, Rasheedat Umoh, Cindy Mfondoum, Roland Christie, Sabrinah Ariane Juillard, Catherine Chichom-Mefire, Alain Department of Public Health and Hygiene Faculty of Health Sciences University of Buea Buea Cameroon Department of Public Health Faculty of Medicine and Biomedical Sciences University of Yaoundé I Yaoundé Cameroon Department of Surgery Division of Global Surgery and Division of Orthopaedic Surgery University of Cape Town and Groote Schuur Hospital South Africa Data Science Center for the Study of Surgery Injury and Equity in Africa (D-SINE-Africa) University of Buea Cameroon Department of Surgery Program for the Advancement of Surgical Equity University of California Los Angeles CA United States Faculty of Health Sciences Sustainable Trauma Research Education and Mentorship (STREaM) Project University of Buea Cameroon Department of Surgery Faculty of Health Sciences University of Buea Buea Cameroon

Background: Thoracic trauma is the third most common cause of death after abdominal injury and head trauma in polytrauma patients. The identification of a patient at risk of thoracic trauma mortality is necessary to avoid delays that may lead to morbidity and mortality. Therefore, the objective was to assess the factors associated with mortality among thoracic trauma patients in Cameroon. Materials and methods: This is a retrospective analysis of the Cameroon Trauma Registry currently running in 10 pilot hospital sites across seven of the ten regions. We retrieved data for all patients with thoracic trauma between the period June 2022 to May 2023 and analyzed factors associated to mortality using multivariate logistic regression. Statistical significance was set at p-value <0.05. Results: Out of 4851 trauma patients, 642 (13.2 %) presented with thoracic trauma. Over 80 % were males and the majority [168 (26.2 %)] were within the age group of 25–34 years. The most common injury mechanism was Road Traffic Injury (RTI). Overall thoracic trauma mortality rate was 9 % with road traffic Injury being the commonest mechanism. Factors associated to thoracic trauma mortality were abnormal chest movement and respiration [(AOR = 5.18, 95 % CI = 1.89–14.19, P = 0.001) and (AOR = 4.72, 95 % CI = 1.44–15.42, P = 0.01) respectively]. Tracheal deviation, breath sounds and respiration were other factors associated with mortality. Conclusion: This analysis highlights thoracic trauma in Cameroon and its contribution to the overall injury death toll. Abnormal chest movement and respiration were factors associated with mortality among thoracic trauma patients. To improve the health outcomes, it is important to understand the treatment logic, involve thoracic surgeons and a multidisciplinary team to improve diagnosis and management. © 2024

关键词： Cameroon Mortality Risk factors Thoracic trauma

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