Doing Business in Vietnam from the Perspectives of Polish Entrepreneurs – the Role of Local Partners

The purpose of this paper is to investigate the challenges of expanding into an emerging marketfor multinational enterprises (MNEs) and the strategies they adopted to overcome these adversities. Whileinterest in the expansion of MNEs into the Vietnamese market is increasing, there is a lack of research onthis process from the Polish businesses' perspectives, which may differ from existing literature. Theanalysis of information obtained by a semi-structured interview method shows that the psychic/culturaldistance is the most critical challenge the Polish enterprises must face when entering the Vietnamesemarket. The study also shows that the key success factor for the expansion of the Polish enterprises intothis market is a local partner, i.e., acquiring an appropriate Vietnamese partner, good cooperation withhim/her, and building mutual trust. As a result, among the available forms of internationalization, thePolish enterprises most often choose export and various forms of cooperation with local partners as themain ways to enter this market.

A gene-centric approach to biomarker discovery identifies transglutaminase 1 as an epidermal autoantigen

Autoantigen discovery is a critical challenge for the understanding and diagnosis of autoimmune diseases. While autoantibody markers in current clinical use have been identified through studies focused on individual disorders, we postulated that a reverse approach starting with a putative autoantigen to explore multiple disorders might hold promise. We here targeted the epidermal protein transglutaminase 1 (TGM1) as a member of a protein family prone to autoimmune attack. By screening sera from patients with various acquired skin disorders, we identified seropositive subjects with the blistering mucocutaneous disease paraneoplastic pemphigus. Validation in further subjects confirmed TGM1 autoantibodies as a 55% sensitive and 100% specific marker for paraneoplastic pemphigus. This gene-centric approach leverages the wealth of data available for human genes and may prove generally applicable for biomarker discovery in autoimmune diseases.

The value of immunotherapy in pediatric leukemia and lymphoma

SummaryLeukemia and lymphoma are a leading cause of cancer-related mortality in children and the prognosis for patients with relapsed or refractory disease remains poor. Standard therapies are associated with a wide array of acute and long-term toxicities. Immunotherapy is changing the treatment landscape for pediatric leukemia and lymphoma patients and has advanced at a tremendous pace over the last decade. Immunotherapies are thought to exhibit fewer long-term toxicities than chemotherapy and radiation, which makes it very appealing in the field of pediatrics. These novel therapeutic concepts may overcome resistance to and decrease side effects of standard therapy. Many therapies are currently being investigated, from immunomodulatory agents to adoptive cell therapy, bispecific T‑cell engagers, oncolytic virotherapy, and checkpoint inhibition. A critical challenge that must be overcome is the identification of biomarker(s) to identify patients who would benefit from immunotherapy.

Molecular Analysis and Genome Sequencing of SARS-Cov-2 during Second Wave 2021 Revealed Variant Diversity in India

SARS-CoV-2 variants rapid emergence has posed critical challenge of higher transmission and immune escape causing serious threats to control the pandemic. The present study was carried out in confirmed cases of SARS-CoV-2 patients to elucidate the prevalence of SARS-CoV-2 variant strain. We performed RT-PCR using extracted RNA from the nasopharyngeal swabs of suspected Covid-19 patients. Confirmed positive cases with CT<25 were subjected to whole-genome sequencing to track the prevalence of the virus in the Malwa region of Punjab. The presence of B.1, B.1.1.7, B.1.351, B.1.617.1, B.1.617.2, AY.1 and other unidentified variants of SARS-CoV-2 was found in the studied population. Among all the variants, B.1.1.7 (UK variant) and B.1.617.2 (delta-Indian variant) was found to be the most dominant variant in the population and was found majorly in Patiala followed by Ludhiana, SBS Nagar, Mansa and Sangrur. In addition to this, sequencing results also observed that the dominant trait was more prevalent in male population and age group 21-40 years. The B.1.1.7 and B.1.617.2 variant of SARS-CoV-2 is replacing the wild type (Wuhan Strain) and emerging as the dominant variant in Punjab.

Regulator Reputation and Stakeholder Participation: A Case Study of the UK’s Regulatory Sandbox for Fintech

This article contributes to the discussion about managing the risks and uncertainties of emerging technologies through increased stakeholder participation. Authorities have increasingly invited stakeholders from high-technology sectors to participate in assessing the risks of, and designing responses to, new technologies. Yet authorities often struggle to attract stakeholders from such sectors to participate; a critical challenge identified but still undertheorised in the literature. Responding to this gap, this article presents a case study of the UK’s regulatory sandbox for financial technologies, applying a document study, questionnaire and interviews to explore fintech firm motivations and apprehensions about participation. Drawing on the bureaucratic reputation literature, the study finds that fintech firms have a range of practical, reputational and normative motivations to participate, and these motivations are inextricably tied to the regulator’s strong reputation with the sector as procedurally correct, high-performing and morally committed to facilitating innovation. On this basis, recommendations for practitioners and hypotheses for future research into the drivers of stakeholder participation in regulatory decision-making surrounding emerging technologies are proposed.

Benefit of a Short Chain Peptide as a Targeting Ligand of Nanocarriers for a Brain-Driven Purpose

Treatment of glioma remains a critical challenge worldwide, since the therapeutic effect is greatly hindered by poor transportation across the blood brain barrier (BBB) and low penetration into tumor cells. In this study, a peptide-conjugated nano-delivery system was explored for the purpose of glioma therapy. A peptide-decorated copolymer was used to prepare nanoparticles (NPs) by a solvent evaporation method. The particle size was in the range of 160.9 ± 3.3–173.5 ± 3.6 nm with monodistribution, and the zeta potentials ranged from −18.6 ± 1.2 to +7.9 ± 0.6 mV showing an increasing trend with R9-peptide. An in vitro cocultured BBB model illustrated the internalization of peptide-conjugated NPs in bEnd.3 cells followed by uptake by U87-MG cells indicating both BBB-crossing and glioma-penetrating abilities. IVIS (In Vivo Imaging System) images revealed that T7-conjugated NPs specifically accumulated in the brain more than peptide-free NPs and had less biodistribution in nontarget tissues than T7/R9 dual-peptide conjugated NPs. The benefit of T7-peptide as a targeting ligand for NPs across the BBB with accumulation in the brain was elucidated.

Modelling of Powder Removal for Additive Manufacture Postprocessing

A critical challenge underpinning the adoption of Additive Manufacture (AM) as a technology is the postprocessing of manufactured components. For Powder Bed Fusion (PBF), this can involve the removal of powder from the interior of the component, often by vibrating the component to fluidise the powder to encourage drainage. In this paper, we develop and validate a computational model of the flow of metal powder suitable for predicting powder removal from such AM components. The model is a continuum Eulerian multiphase model of the powder including models for the granular temperature; the effect of vibration can be included through appropriate wall boundaries for this granular temperature. We validate the individual sub-models appropriate for AM metal powders by comparison with in-house and literature experimental results, and then apply the full model to a more complex geometry typical of an AM Heat Exchanger. The model is shown to provide valuable and accurate results at a fraction of the computational cost of a particle-based model.

US-India-Pakistan cyber cooperation will be limited

Significance Washington, Delhi and Islamabad all view cybersecurity as a critical challenge, and the US administration wants to work multilaterally to address shared global threats. However, the lack of precedent for trilateral cooperation, deep US-Pakistan and India-Pakistan mistrust, and US preference for cyber cooperation only with top allies impede collaboration. Impacts US-India-Pakistan cyber cooperation may offer a new template for three-way collaboration on other threats such as climate change. Any India-Pakistan cooperation on cybersecurity could spur additional bilateral collaboration in other areas. Such cooperation would boost efforts to develop global norms to tackle cybersecurity.

Modelling of Powder Removal for Additive Manufacture Postprocessing

A critical challenge underpinning the adoption of Additive Manufacture (AM) as a technology is the postprocessing of manufactured components. For Selective Laser Sintering (SLS) this can involve the removal of powder from the interior of the component, often by vibrating the component to fluidise the powder to encourage drainage. In this paper we develop and validate a computational model of the flow of metal powder suitable for predicting powder removal from such AM components. The model is a continuum Eulerian multiphase model of the powder including models for the granular temperature; the effect of vibration can be included through appropriate wall boundaries for this granular temperature. We validate the individual sub-models appropriate for AM metal powders by comparison with in-house and literature experimental results, and then apply the full model to a more complex geometry typical of an AM Heat Exchanger. The model is shown to provide valuable and accurate results at a fraction of the computational cost of a particle-based model.