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1.
14th International Conference on Machine Learning and Computing, ICMLC 2022 ; : 455-460, 2022.
Article in English | Scopus | ID: covidwho-1932812

ABSTRACT

The COVID-19 infections segmentation is a challenging task due to the high variation in shape, size and position of infections or lesions in medical images. To solve it, we propose a deep learning-based segmentation method for COVID-19 chest CT images that can automatically segment COVID-19 lung lesions. Based on the U-Net model, we introduce a feature fusion and an attention block for increasing the multi-scale feature learning capacity. Moreover, the network is also equipped with a residual block and a deep supervision mechanism to improve model segmentation accuracy and completeness rate. Experimental results show that the method has a good test effect after training, and the Dice index can reach 63.26%, which is beneficial for the diagnosis of the coronary pneumonia. © 2022 ACM.

2.
Chinese Journal of Laboratory Medicine ; 45(4):360-365, 2022.
Article in Chinese | Scopus | ID: covidwho-1905720

ABSTRACT

Objective To analyze the laboratory detection methods and clinical characteristics of patients with 2019-nCoV Omicron variant infection, to realize the rapid identification and diagnosis of 2019-nCoV Omicron variants. Methods Totally 80 overseas patients in First Hospital of Changsha from December 16 in 2021 to January 5 in 2022 were selected, the nucleic acids and mutant genes were detected by fluorescent PCR and genome sequencing, and the clinical characteristics of patients with 2019-nCoV Omicron variant infection were analyzed. Results The specificity was 100% (58/58) and positive predictive value was 100% (21/21) respectively, the sensitivity was 95.5% (21/22), negative predictive value was 98.3% (58/59) by detected with fluorescent PCR. It was found that there were 45-50 nucleotide displacement sites in the genome and 25-30 amino acid mutation sites in S gene fragment by genome sequencing. Clinical analysis showed that mild cases were 59.1% (13/22) in layouts, without severe and critical cases. Ages were positively associated with the clinical classification (ρ =0.698, P<0.001), foundation infections were positively associated with the clinical classification (ρ =0.636, P<0.001). Conclusions Patients with 2019-nCoV Omicron variant infection had a high viral load and long negative conversion time of nucleic acid. Ages and foundation infections were positively associated with the clinical classification. AST/ALT was higher in the early stage of the disease. Fluorescent PCR method can be used in rapid screening patients with 2019-nCoV Omicron variant infection. © 2022 Chinese Medical Journals Publishing House Co.Ltd. All rights reserved.

3.
Science of Advanced Materials ; 14(2):408-413, 2022.
Article in English | English Web of Science | ID: covidwho-1883369

ABSTRACT

The management of breast cancer patients in the current COVID-19 outbreak is challenging. Myelosuppres-sion associated with cancer treatment may increase the risk of infection in both hospitals and at home. We implemented the following strategy to reduce myelosuppression of adjuvant chemotherapy during the COVID-19 pandemic: (1) changing the original regimen of AC x 4-* wT x 12 to wT x 12-* AC x 4. (2) substitution of standard paclitaxel with nanoparticle albumin-bound (nab)-paclitaxel (nab-paclitaxel). For 43 patients who com-IP: 14.98.160.66 On: Fri, 13 May 2022 09:27:55 pleted nab-paclitaxel treatment, the compliance rate was 100%, without interruption or delay of nab-paclitaxel Copyright: American Scientific Publishers Delivered by Ingenta treatment. Dose reduction was necessary in 2 patients (4.6%) due to peripheral neuropathy. Thus, 98.6% of the planned doses were administered. As expected, the adjusted adjuvant regimen was safe and well toler-ated. Therefore wT x 12-* AC x 4 treatment procedure may be considered for breast cancer patients during COVID-19 pandemic.

4.
7th International Conference on Big Data Analytics, ICBDA 2022 ; : 96-103, 2022.
Article in English | Scopus | ID: covidwho-1846095

ABSTRACT

With the outbreak of the COVID-19, people are eager to develop potential drugs for specific diseases through efficient technological means. Alzheimer's disease (AD) has become one of the top ten causes of death in the world and is a typical neurodegenerative disease. When acetylcholinesterase (AChE) is inhibited, it improves the transmission of cholinergic neurotransmitters in patients and restores cognitive function, so acetylcholinesterase inhibitors (AChEIs) are often considered by researchers as potential drugs for the treatment of AD. Machine learning algorithms and data mining techniques can accelerate drug development and reduce the cost of biological experiments, so it is of great significance to develop models that can accurately predict AChEIs. However, few studies have applied efficient and mature ensemble learning methods to the problem of predicting potential inhibitors of AChE. In this study, we constructed a dataset from a publicly available biological experiment database, and for the first time established an ensemble learning model based on CatBoost and XGBoost to predict potential AChEIs. We demonstrate the advantages of ensemble learning models in building AChEIs predictor based on imbalanced, heterogeneous data through a comprehensive evaluation. Afterwards, we also combined the best-performing models into a blending model AChEI-EL for case studies, and obtained the top-ranked potential inhibitors that have been shown to have the potential to inhibit the AChE. These results suggest that our method has a promising application in the field of AD. Finally, we developed a WEB online prediction platform based on the best model for the use and reference of researchers. © 2022 IEEE.

5.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-334805

ABSTRACT

Omicron sub-lineage BA.2 has rapidly surged globally, accounting for over 60% of recent SARS-CoV-2 infections. Newly acquired RBD mutations and high transmission advantage over BA.1 urge the investigation of BA.2's immune evasion capability. Here, we show that BA.2 causes strong neutralization resistance, comparable to BA.1, in vaccinated individuals' plasma. However, BA.2 displays more severe antibody evasion in BA.1 convalescents, and most prominently, in vaccinated SARS convalescents' plasma, suggesting a substantial antigenicity difference between BA.2 and BA.1. To specify, we determined the escaping mutation profiles1,2 of 714 SARS-CoV-2 RBD neutralizing antibodies, including 241 broad sarbecovirus neutralizing antibodies isolated from SARS convalescents, and measured their neutralization efficacy against BA.1, BA.1.1, BA.2. Importantly, BA.2 specifically induces large-scale escape of BA.1/BA.1.1effective broad sarbecovirus neutralizing antibodies via novel mutations T376A, D405N, and R408S. These sites were highly conserved across sarbecoviruses, suggesting that Omicron BA.2 arose from immune pressure selection instead of zoonotic spillover. Moreover, BA.2 reduces the efficacy of S309 (Sotrovimab)3,4 and broad sarbecovirus neutralizing antibodies targeting the similar epitope region, including BD55-5840. Structural comparisons of BD55-5840 in complexes with BA.1 and BA.2 spike suggest that BA.2 could hinder antibody binding through S371F-induced N343-glycan displacement. Intriguingly, the absence of G446S mutation in BA.2 enabled a proportion of 440-449 linear epitope targeting antibodies to retain neutralizing efficacy, including COV2-2130 (Cilgavimab)5. Together, we showed that BA.2 exhibits distinct antigenicity compared to BA.1 and provided a comprehensive profile of SARS-CoV-2 antibody escaping mutations. Our study offers critical insights into the humoral immune evading mechanism of current and future variants.

6.
WSEAS Transactions on Business and Economics ; 19:739-747, 2022.
Article in English | Scopus | ID: covidwho-1789985

ABSTRACT

In Taiwan, real estate is not only the high price product but also is necessities. Every family needs real estate to live. Maybe, some citizens decide to rent house in the short period. But, major part of citizen will purchase real estate in the future. In past researches, evaluating performance of real estate mainly consider the function and condition of this house such as location, house type, floor, building age etc. However, the demand of specific consumer is importance factors to evaluate the performance of this customer. Especially, the requirement of real estate for consumer has been changed after COVID-19. The goal of this study is to build the evaluation model and relative criteria to evaluate performance of real estate in order to fit with the requirement of specific real estate consumer. Case study will be implemented for readers realize proposed method. Sensitive analysis will be executed and proposed method will be compared with traditional multi criteria method to justify the usefulness of this method. Some conclusion and future research will be taken over as ending. © 2022, World Scientific and Engineering Academy and Society. All rights reserved.

7.
Climate Change Economics ; : 29, 2022.
Article in English | Web of Science | ID: covidwho-1745660

ABSTRACT

Regional attempts to reduce pollution levels emerging from the European Union (EU) relative to 2010 are contrasted with unique policies of individual member countries' aims to achieve a 10% reduction per country. Given this scenario, this research expands on the topic by developing a novel framework that links macroeconomic policies, total national expenditure per person, traditional energy use, renewable energy use, and CO2 emissions levels in EU countries from 1990 to 2016. The study utilizes the second generation cross-sectional-autoregressive-distributed lag (CS-ARDL) panel data method. According to the study's findings, the monetary instruments of growth exacerbated the adverse effects of CO2 emissions, and by tightening monetary policy, the harmful effects of CO2 emissions levels have been reduced. Further, the Granger causality test indicates a bidirectional causality between monetary policy and CO2 emissions levels, and unidirectional causality from the policy assessment for energy use. The finding confirms that the assessment policy recommendations on energy consumption have future effects on ecological value.

8.
2021 IEEE International Conference on Engineering, Technology and Education, TALE 2021 ; : 35-41, 2021.
Article in English | Scopus | ID: covidwho-1741267

ABSTRACT

School closures during the COVID-19 pandemic highlight the need for promoting efficient online learning. Without external pressure and guidance, fully online learners are expected to self-monitor their learning process and find paths to achieve learning goals;such abilities are considered self-regulated learning (SRL) skills. To become a self-regulated learner, the first step is to learn how to set effective learning goals. However, this is difficult for learners with lower SRL skills, since they may not have enough knowledge on selecting and adopting the appropriate goal setting strategies. Thus, there is a need for supporting fully online learners on setting effective learning goals. This study introduces a new approach of enhancing students' goal setting skills by interacting with a chatbot, which embedded some guiding questions based on a goal setting strategy. Students in an online course were invited to complete a goal setting activity prior to class, and their perceptions of the activity were collected via interviews. The findings from this study shed light on future designs of chatbot supporting SRL activities. © 2021 IEEE.

9.
Stroke ; 53(SUPPL 1), 2022.
Article in English | EMBASE | ID: covidwho-1724021

ABSTRACT

Objectives: Acute ischemic stroke patients with severe acute respiratory syndrome coronavirus maybe candidates for acute revascularization treatments (intravenous thrombolysis and/or mechanical thrombectomy). Materials and Methods: We analyzed the data from 62 healthcare facilities to determine the odds of receiving acute revascularization treatments in severe acute respiratory syndrome coronavirus infected patients and odds of composite of death and non-routine discharge with severe acute respiratory syndrome coronavirus infected and non-infected patients undergoing acute revascularization treatments after adjusting for potential confounders. Results: Acute ischemic stroke patients with severe acute respiratory syndrome coronavirus infection were significantly less likely to receive acute revascularization treatments (odds ratio 0.6, 95% confidence interval 0.5-0.8, p=0.0001). Among ischemic stroke patients who received acute revascularization treatments, severe acute respiratory syndrome coronavirus infection was associated with increased odds of death or non-routine discharge (odds ratio 3.0, 95% confidence interval 1.8-5.1). The higher odds death or non-routine discharge (odds ratio 2.1, 95% confidence interval 1.9-2.3) with severe acute respiratory syndrome coronavirus infection were observed in all ischemic stroke patients without any modifying effect of acute revascularization treatments (interaction term for death (p=0.9) or death or non-routine discharge (p=0.2). Conclusions: Patients with acute ischemic stroke patients with severe acute respiratory syndrome coronavirus infection were significantly less likely to receive acute revascularization treatments. Severe acute respiratory syndrome coronavirus infection was associated with a significantly higher rate of death or non-routine discharge among acute ischemic stroke patients receiving revascularization treatments.

10.
Stroke ; 53(SUPPL 1), 2022.
Article in English | EMBASE | ID: covidwho-1723998

ABSTRACT

Background: Undiagnosed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may be seen in acute stroke patients. Rapid screening is important to reduce exposure to medical professionals and other patients during acute assessment and treatment. Chest computed tomographic (CT) scan may be another time-sensitive option for identification of SARS-CoV-2 infection in acute stroke patients. Objective: We report our experience of incorporating chest CT scan in the initial neuroimaging protocol for evaluation of acute stroke patients. Methods: All acute stroke patients underwent chest CT scan concurrent to CT head, CT angiogram of head and neck and CT perfusion for 10 months. We identified patients who had chest CT scan findings that were suggestive of SARS-CoV-2 infection including bilateral, multilobar ground glass opacification with a peripheral or posterior distribution, and/or consolidation. All patients subsequently underwent polymerase chain reaction (PCR) testing using nasopharyngeal specimen for identification of SARS-CoV-2 with contact isolation. Sensitivity, specificity, and likelihood ratios were calculated. Results: A total of 530 consecutive acute stroke patients (mean age in years 65.6± SD;15.4;280 were men) underwent neuroimaging with concurrent chest CT scan. The chest CT scan identified findings suggestive of SARS-CoV-2 infection in 34 (6.4%) patients. Subsequent PCR testing confirmed the diagnosis of SARS-CoV-2 infection in 21 of 34 patients. Among 491 patients in whom chest CT scan did not identify any findings suggestive of SARS-CoV-2 infection, 387 underwent PCR tests;PCR testing confirmed the diagnosis of SARS-CoV-2 infection in 13 of 34 patients. Sensitivity and specificity of chest CT scan for detecting SARS-CoV-2 infection was 61.9% and 96.2%, respectively. Positive and negative likelihood ratio of chest CT scan for detecting SARSCoV-2 infection is 16.26 and 0.39, respectively. Conclusions: Although specificity was high, the relatively low sensitivity of chest CT scan in identifying SARS-CoV-2 infection limits the value of adding this imaging to standard neuroimaging in acute stroke patients. At our institution, we have subsequently discontinued the protocol.

11.
Frontiers in Environmental Science ; 10, 2022.
Article in English | Scopus | ID: covidwho-1714996

ABSTRACT

Coronavirus disease 2019 (COVID-19) has become a major public health concern worldwide. In this study, we aimed to analyze spatial clusters of the COVID-19 epidemic and explore the effects of population emigration and socioeconomic factors on the epidemic at the county level in Guangdong, China. Data on confirmed cases, population migration, and socioeconomic factors for 121 counties were collected from 1 December 2019 to 17 February 2020, during which there were a total of 1,328 confirmed cases. County-level infected migrants of Guangdong moving from Hubei were calculated by integrating the incidence rate, population migration data of Baidu Qianxi, and the resident population. Using the spatial autocorrelation method, we identified high-cluster areas of the epidemic. We also used a geographical detector to explore infected migrants and socioeconomic factors associated with transmission of COVID-19 in Guangdong. Our results showed that: 1) the epidemic exhibited significant positive global spatial autocorrelation;high–high spatial clusters were mainly distributed in the Pearl River Estuary region;2) city-level population migration data corroborated with the incidence rate of each city in Hubei showed significant association with confirmed cases;3) in terms of potential factors, infected migrants greatly contributed to the spread of COVID-19, which has strong ability to explain the COVID-19 epidemic;besides, the companies, transport services, residential communities, restaurants, and community facilities were also the dominant factors in the spread of the epidemic;4) the combined effect produced by the intersecting factors can increase the explanatory power. The infected migrant factor interacted strongly with the community facility factor with the q value of 0.895. This indicates that the interaction between infected migrants and community facilities played an important role in transmitting COVID-19 at the county level. Copyright © 2022 Xu, Deng, Yang, Huang, Yan, Xie, Li and Jing.

12.
ISPRS International Journal of Geo-Information ; 11(2), 2022.
Article in English | Scopus | ID: covidwho-1699583

ABSTRACT

COVID-19 has had a huge impact on many industries around the world. Internationallyfunded enterprises have been greatly affected by COVID-19 prevention and control measures, such as border controls. However, few studies have examined the impact of COVID-19 on internationally-funded enterprises. To this end, this paper considered 12 of China’s industrial parks situated in Southeast Asia, while comparing the operation status before and after the outbreak of COVID-19 based on remote sensing of nighttime lights (NTL). The NTL is generally used as a proxy for economic activity. First, six parameters were proposed to quantify and monitor the operation status based on NTL data. Subsequently, these parameters were calculated for the parks and for 10 km buffer zones surrounding them to analyze the differences in operating conditions. The results showed that (1) despite the negative impact of COVID-19, 9 out of the 12 parks had a mean NTL greater than 1, indicating that these parks are in better operating condition in 2020 than 2019;(2) 7 out of the 10 km buffer zones around the parks showed a decline in mean NTL. Only three parks showed a decline in mean NTL. The impact of COVID-19 on surrounding areas was greater than the impact on parks. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

13.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326996

ABSTRACT

Vaccine boosters and infection can facilitate the development of SARS-CoV-2 antibodies with improved potency and breadth. Here, we observed super-immunity in a camelid extensively immunized with the SARS-CoV-2 receptor-binding domain (RBD). We rapidly isolated a large repertoire of specific ultrahigh-affinity nanobodies that bind strongly to all known sarbecovirus clades using integrative proteomics. These pan-sarbecovirus nanobodies (psNbs) are highly effective against SARS-CoV and SARS-CoV-2 variants including the Omicron, with the best median neutralization potency at single-digit ng/ml. Structural determinations of 13 psNbs with the SARS-CoV-2 spike or RBD revealed five epitope classes, providing insights into the mechanisms and evolution of their broad activities. The highly evolved psNbs target small, flat, and flexible epitopes that contain over 75% of conserved RBD surface residues. Their potencies are strongly and negatively correlated with the distance of the epitopes to the receptor binding sites. A highly potent, inhalable and bispecific psNb (PiN-31) was developed. Our findings inform on the development of broadly protective vaccines and therapeutics.

14.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326980

ABSTRACT

Omicron, the most heavily mutated SARS-CoV-2 variant so far, is highly resistant to neutralizing antibodies, raising unprecedented concerns about the effectiveness of antibody therapies and vaccines. We examined whether sera from individuals who received two or three doses of inactivated vaccine, could neutralize authentic Omicron. The seroconversion rates of neutralizing antibodies were 3.3% (2/60) and 95% (57/60) for 2- and 3-dose vaccinees, respectively. For three-dose recipients, the geometric mean neutralization antibody titer (GMT) of Omicron was 15, 16.5-fold lower than that of the ancestral virus (254). We isolated 323 human monoclonal antibodies derived from memory B cells in 3-dose vaccinees, half of which recognize the receptor binding domain (RBD) and show that a subset of them (24/163) neutralize all SARS-CoV-2 variants of concern (VOCs), including Omicron, potently. Therapeutic treatments with representative broadly neutralizing mAbs individually or antibody cocktails were highly protective against SARS-CoV-2 Beta infection in mice. Atomic structures of the Omicron S in complex with three types of all five VOC-reactive antibodies defined the binding and neutralizing determinants and revealed a key antibody escape site, G446S, that confers greater resistance to one major class of antibodies bound at the right shoulder of RBD through altering local conformation at the binding interface. Our results rationalize the use of 3-dose immunization regimens and suggest that the fundamental epitopes revealed by these broadly ultrapotent antibodies are a rational target for a universal sarbecovirus vaccine.

15.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326764

ABSTRACT

The SARS-CoV-2 B.1.1.529 variant (Omicron) contains 15 mutations on the receptor-binding domain (RBD). How Omicron would evade RBD neutralizing antibodies (NAbs) requires immediate investigation. Here, we used high-throughput yeast display screening1,2 to determine the RBD escaping mutation profiles for 247 human anti-RBD NAbs and showed that the NAbs could be unsupervised clustered into six epitope groups (A-F), which is highly concordant with knowledge-based structural classifications3-5. Strikingly, various single mutations of Omicron could impair NAbs of different epitope groups. Specifically, NAbs in Group A-D, whose epitope overlap with ACE2-binding motif, are largely escaped by K417N, G446S, E484A, and Q493R. Group E (S309 site)6 and F (CR3022 site)7 NAbs, which often exhibit broad sarbecovirus neutralizing activity, are less affected by Omicron, but still, a subset of NAbs are escaped by G339D, N440K, and S371L. Furthermore, Omicron pseudovirus neutralization showed that single mutation tolerating NAbs could also be escaped due to multiple synergetic mutations on their epitopes. In total, over 85% of the tested NAbs are escaped by Omicron. Regarding NAb drugs, the neutralization potency of LYCoV016/LY-CoV555, REGN10933/REGN10987, AZD1061/AZD8895, and BRII-196 were greatly reduced by Omicron, while VIR-7831 and DXP-604 still function at reduced efficacy. Together, data suggest Omicron would cause significant humoral immune evasion, while NAbs targeting the sarbecovirus conserved region remain most effective. Our results offer instructions for developing NAb drugs and vaccines against Omicron and future variants.

17.
Nguyen, T.; Qureshi, M.; Martins, S.; Yamagami, H.; Qiu, Z.; Mansour, O.; Czlonkowska, A.; Abdalkader, M.; Sathya, A.; de Sousa, D. A.; Demeestere, J.; Mikulik, R.; Vanacker, P.; Siegler, J.; Korv, J.; Biller, J.; Liang, C.; Sangha, N.; Zha, A.; Czap, A.; Holmstedt, C.; Turan, T.; Grant, C.; Ntaios, G.; Malhotra, K.; Tayal, A.; Loochtan, A.; Mistry, E.; Alexandrov, A.; Huang, D.; Yaghi, S.; Raz, E.; Sheth, S.; Frankel, M.; Lamou, E. G. B.; Aref, H.; Elbassiouny, A.; Hassan, F.; Mustafa, W.; Menecie, T.; Shokri, H.; Roushdy, T.; Sarfo, F. S.; Alabi, T.; Arabambi, B.; Nwazor, E.; Sunmonu, T. A.; Wahab, K. W.; Mohammed, H. H.; Adebayo, P. B.; Riahi, A.; Ben Sassi, S.; Gwaunza, L.; Rahman, A.; Ai, Z. B.; Bai, F. H.; Duan, Z. H.; Hao, Y. G.; Huang, W. G.; Li, G. W.; Li, W.; Liu, G. Z.; Luo, J.; Shang, X. J.; Sui, Y.; Tian, L.; Wen, H. B.; Wu, B.; Yan, Y. Y.; Yuan, Z. Z.; Zhang, H.; Zhang, J.; Zhao, W. L.; Zi, W. J.; Leung, T. K.; Sahakyan, D.; Chugh, C.; Huded, V.; Menon, B.; Pandian, J.; Sylaja, P. N.; Usman, F. S.; Farhoudi, M.; Sadeghi-Hokmabadi, E.; Reznik, A.; Sivan-Hoffman, R.; Horev, A.; Ohara, N.; Sakai, N.; Watanabe, D.; Yamamoto, R.; Doijiri, R.; Tokuda, N.; Yamada, T.; Terasaki, T.; Yazawa, Y.; Uwatoko, T.; Dembo, T.; Shimizu, H.; Sugiura, Y.; Miyashita, F.; Fukuda, H.; Miyake, K.; Shimbo, J.; Sugimura, Y.; Yagita, Y.; Takenobu, Y.; Matsumaru, Y.; Yamada, S.; Kono, R.; Kanamaru, T.; Yamazaki, H.; Sakaguchi, M.; Todo, K.; Yamamoto, N.; Sonodda, K.; Yoshida, T.; Hashimoto, H.; Nakahara, I.; Faizullina, K.; Kamenova, S.; Kondybayeva, A.; Zhanuzakov, M.; Baek, J. H.; Hwang, Y.; Lee, S. B.; Moon, J.; Park, H.; Seo, J. H.; Seo, K. D.; Young, C. J.; Ahdab, R.; Aziz, Z. A.; Zaidi, W. A. W.; Bin Basri, H.; Chung, L. W.; Husin, M.; Ibrahim, A. B.; Ibrahim, K. A.; Looi, I.; Tan, W. Y.; Yahya, Wnnw, Groppa, S.; Leahu, P.; Al Hashmi, A.; Imam, Y. Z.; Akhtar, N.; Oliver, C.; Kandyba, D.; Alhazzani, A.; Al-Jehani, H.; Tham, C. H.; Mamauag, M. J.; Narayanaswamy, R.; Chen, C. H.; Tang, S. C.; Churojana, A.; Aykac, O.; Ozdemir, A. O.; Hussain, S. I.; John, S.; Vu, H. L.; Tran, A. D.; Nguyen, H. H.; Thong, P. N.; Nguyen, T.; Nguyen, T.; Gattringer, T.; Enzinger, C.; Killer-Oberpfalzer, M.; Bellante, F.; De Blauwe, S.; Van Hooren, G.; De Raedt, S.; Dusart, A.; Ligot, N.; Rutgers, M.; Yperzeele, L.; Alexiev, F.; Sakelarova, T.; Bedekovic, M. R.; Budincevic, H.; Cindric, I.; Hucika, Z.; Ozretic, D.; Saric, M. S.; Pfeifer, F.; Karpowicz, I.; Cernik, D.; Sramek, M.; Skoda, M.; Hlavacova, H.; Klecka, L.; Koutny, M.; Vaclavik, D.; Skoda, O.; Fiksa, J.; Hanelova, K.; Nevsimalova, M.; Rezek, R.; Prochazka, P.; Krejstova, G.; Neumann, J.; Vachova, M.; Brzezanski, H.; Hlinovsky, D.; Tenora, D.; Jura, R.; Jurak, L.; Novak, J.; Novak, A.; Topinka, Z.; Fibrich, P.; Sobolova, H.; Volny, O.; Christensen, H. K.; Drenck, N.; Iversen, H.; Simonsen, C.; Truelsen, T.; Wienecke, T.; Vibo, R.; Gross-Paju, K.; Toomsoo, T.; Antsov, K.; Caparros, F.; Cordonnier, C.; Dan, M.; Faucheux, J. M.; Mechtouff, L.; Eker, O.; Lesaine, E.; Ondze, B.; Pico, F.; Pop, R.; Rouanet, F.; Gubeladze, T.; Khinikadze, M.; Lobjanidze, N.; Tsiskaridze, A.; Nagel, S.; Ringleb, P. A.; Rosenkranz, M.; Schmidt, H.; Sedghi, A.; Siepmann, T.; Szabo, K.; Thomalla, G.; Palaiodimou, L.; Sagris, D.; Kargiotis, O.; Kaliaev, A.; Liebeskind, D.; Hassan, A.; Ranta, A.; Devlin, T.; Zaidat, O.; Castonguay, A.; Jovin, T.; Tsivgoulis, G.; Malik, A.; Ma, A.; Campbell, B.; Kleinig, T.; Wu, T.; Gongora, F.; Lavados, P.; Olavarria, V.; Lereis, V. P.; Corredor, A.; Barbosa, D. M.; Bayona, H.; Barrientos, J. D.; Patino, M.; Thijs, V.; Pirson, A.; Kristoffersen, E. S.; Patrik, M.; Fischer, U.; Bernava, G.; Renieri, L.; Strambo, D.; Ayo-Martin, O.; Montaner, J.; Karlinski, M.; Cruz-Culebras, A.; Luchowski, P.; Krastev, G.; Arenillas, J.; Gralla, J.; Mangiafico, S.; Blasco, J.; Fonseca, L.; Silva, M. L.; Kwan, J.; Banerjee, S.; Sangalli, D.; Frisullo, G.; Yavagal, D.; Uyttenboogaart, M.; Bandini, F.; Adami, A.; de Lecina, M. A.; Arribas, M. A. T.; Ferreira, P.; Cruz, V. T.; Nunes, A. P.; Marto, J. P.; Rodrigues, M.; Melo, T.; Saposnik, G.; Scott, C. A.; Shuaib, A.; Khosravani, H.; Fields, T.; Shoamanesh, A.; Catanese, L.; Mackey, A.; Hill, M.; Etherton, M.; Rost, N.; Lutsep, H.; Lee, V.; Mehta, B.; Pikula, A.; Simmons, M.; Macdougall, L.; Silver, B.; Khandelwal, P.; Morris, J.; Novakovic-White, R.; Ramakrishnan, P.; Shah, R.; Altschul, D.; Almufti, F.; Amaya, P.; Ordonez, C. E. R.; Lara, O.; Kadota, L. R.; Rivera, L. I. P.; Novarro, N.; Escobar, L. D.; Melgarejo, D.; Cardozo, A.; Blanco, A.; Zelaya, J. A.; Luraschi, A.; Gonzalez, V. H. N.; Almeida, J.; Conforto, A.; Almeida, M. S.; Silva, L. D.; Cuervo, D. L. M.; Zetola, V. F.; Martins, R. T.; Valler, L.; Giacomini, L. V.; Cardoso, F. B.; Sahathevan, R.; Hair, C.; Hankey, G.; Salazar, D.; Lima, F. O.; Mont'Alverne, F.; Moises, D.; Iman, B.; Magalhaes, P.; Longo, A.; Rebello, L.; Falup-Pecurariu, C.; Mazya, M.; Wisniewska, A.; Fryze, W.; Kazmierski, R.; Wisniewska, M.; Horoch, E.; Sienkiewicz-Jarosz, H.; Fudala, M.; Rogoziewicz, M.; Brola, W.; Sobolewski, P.; Kaczorowski, R.; Stepien, A.; Klivenyi, P.; Szapary, L.; van den Wijngaard, I.; Demchuk, A.; Abraham, M.; Alvarado-Ortiz, T.; Kaushal, R.; Ortega-Gutierrez, S.; Farooqui, M.; Bach, I.; Badruddin, A.; Barazangi, N.; Nguyen, C.; Brereton, C.; Choi, J. H.; Dharmadhikari, S.; Desai, K.; Doss, V.; Edgell, R.; Linares, G.; Frei, D.; Chaturvedi, S.; Gandhi, D.; Chaudhry, S.; Choe, H.; Grigoryan, M.; Gupta, R.; Helenius, J.; Voetsch, B.; Khwaja, A.; Khoury, N.; Kim, B. S.; Kleindorfer, D.; McDermott, M.; Koyfman, F.; Leung, L.; Linfante, I.; Male, S.; Masoud, H.; Min, J. Y.; Mittal, M.; Multani, S.; Nahab, F.; Nalleballe, K.; Rahangdale, R.; Rafael, J.; Rothstein, A.; Ruland, S.; Sharma, M.; Singh, A.; Starosciak, A.; Strasser, S.; Szeder, V.; Teleb, M.; Tsai, J.; Mohammaden, M.; Pineda-Franks, C.; Asyraf, W.; Nguyen, T. Q.; Tarkanyi, G.; Horev, A.; Haussen, D.; Balaguera, O.; Vasquez, A. R.; Nogueira, R..
Neurology ; 96(15):42, 2021.
Article in English | Web of Science | ID: covidwho-1576349
20.
Journal of Agribusiness in Developing and Emerging Economies ; ahead-of-print(ahead-of-print):14, 2021.
Article in English | Web of Science | ID: covidwho-1583865

ABSTRACT

Purpose This study deals with attenuating the risk of relying on a single export market, which was heightened by the outbreak of the COVID-19 pandemic. It focuses on Taiwanese atemoya (a fruit with short storage life) and the adoption of active controlled atmosphere (CA) containers, a new technology which lengthens storage time for other export markets. This study looks at the financial feasibility of the technology's first ever use in atemoya exports. Design/methodology/approach Apart from the standard financial assessment tools-like net present value (NPV), internal rate of return (IRR), benefit-cost ratio (BCR) and payback period (PBP)-this study calibrated five different scenarios based on data gathered from relevant market agents including suppliers, exporters, customs brokers and technology developer. Findings Due to the high profit margin and low investment cost, the use of active CA containers for long-haul exports of this highly perishable fruit is found both technically and financially feasible, despite the generally higher operational cost during the pandemic. Research limitations/implications This study looked at three specific export markets: Malaysia, Dubai and Canada. Results here may lack generalizability in other markets, although it is believed that slight deviations would not invalidate the conclusions of this research because short, medium and long distances were all covered therein. Originality/value This paper studies the first time that active CA is used for export of atemoyas to expand existing markets.

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