Exploring Enablers and Barriers to Municipal Solid Waste (MSW) Management Technologies Adoption in the Kingdom of Bahrain

Municipal Solid Waste (MSW) becomes a point of focus globally due to its harmful effects on the environment and human health if it is not managed properly. MSW was proved globally to be used as a resource, and it has a major opportunity in the realm of conversion technologies. Accordingly, this study aims to explore the enablers and barriers to six different MSW management (MSWM) technologies adopted in the Kingdom of Bahrain, in order to ensure the successful adoption of these technologies that are Anaerobic Digestion (AD), Incineration, Pyrolysis, Gasification, Composting and Refused Derived Fuel (RDF). This study provides sufficient information to the decision and policy-makers for the processes of selection and adoption of the MSWM technologies in Bahrain, using a qualitative approach “mainly semi-structured interviews” with experts and then Thematic Analysis using nvivo12 software. The results show that the main themes that enablers and barriers fall under are: political (e.g. national waste management strategy), technical (e.g. segregation at source), managerial (e.g. capacity building), social (e.g. public awareness), economic (e.g. incentives to investment) and environmental (e.g. air quality). This study concluded that in order to succeed in the MSWM technologies adoption, the resulted barriers should be overcome. Furthermore, Incineration was recommended as the best solution to manage MSW which has the least barriers and most enablers in Bahrain as per the experts.

Enablers, Difficulties and Features to Implement E-Learning Technology in Conventional Higher Education: Case Study and Prototype Implication

Supporting higher education with modern technologies like E-Learning is very important for one country to improve quality of education, to meet student’s expectations and to continue teaching-learning and training when face to face education is impossible. However, it is in its preliminary stage in developing countries like Ethiopia. This study examined the enabling factors, difficulties and opportunities of E-Learning implementation in Assosa University (ASU), Ethiopia. Its purpose is to find the enabling factors, difficulties and opportunities of E-Learning implementation in ASU and developing prototype of E-Learning system to show its practicality and to identify approaches of students’ and lecturers towards E-Learning. The study employed questionnaires, observation and interview to gather the required information. A sample of 309 students and 64 Lecturers randomly selected from 7 colleges and two schools as well as ICT workers and other concerned bodies in the university. Also prototyping as a methodology was used to implement and test the proposed system for proof of concept. This study investigating the possibility of implementing E-Learning in ASU and important enablers, difficulties and opportunities is identified. Also the E-Learning platform of the university is developed and introduced for students and lecturers to show its practicality. Most students and lecturers showed good motivation in E-Learning implementation and they assumed that it is useful for the university. The result shows that although there are difficulties to implement E-Learning in ASU, the possibility of fully implementing E-Learning in the University is relatively high with mixed method. With this, the approaches of students and lecturers are positively viewed and the opportunities are very noticeable in the University. So, conventional higher education can practically implement E-Learning with mixed approach to use as supportive tool for educational improvements and to reduce physical presence.

Attitudes,beliefs,behaviours and perspectives on barriers and enablers of Australian general practitioners towards non-drug interventions:a national survey

Background Many guidelines recommend non-drug interventions(NDIs)for managing common conditions in primary care.However,compared with drug interventions,NDIs are less widely known,promoted and used.We aim to(1)examine general practitioners’(GPs’)knowledge,attitudes and practices for NDIs,including their use of the Royal Australian College of General Practitioners(RACGP)Handbook of Non-Drug Interventions(HANDI),and(2)identify factors influencing their use of NDIs and HANDI.Methods We conducted a web-based cross-sectional survey of practicing GP members in Australia during October-November 2022.The survey contained five sections:characteristics of GP;knowledge and use of NDIs;attitudes towards NDIs;barriers and enablers to using HANDI;and suggestions of NDIs and ideas to improve the uptake of NDIs in primary care.Results Of the 366 GPs who completed the survey,242(66%)were female,and 248(74%)were≥45 years old.One in three GPs reported that they regularly(‘always’)recommend NDIs to their patients when appropriate(34%),whereas one-third of GPs were unaware of HANDI(39%).GPs identified several factors that improve the uptake of HANDI,including‘access and integration of HANDI in clinical practice’,‘content and support to use in practice’and‘awareness and training’.Conclusions While many GPs are aware of the effectiveness of NDIs and often endorse their use,obstacles still prevent widespread adoption in primary care.The results of this survey can serve as a foundation for developing implementation strategies to improve the uptake of effective evidence-based NDIs in primary care.

Effective extraction of polyribosomes from astrocytes enables future discoveries on translation regulation

Translation regulation is an important layer of gene expression:Generation of genome-wide expression datasets at multi-omics levels in spatial,temporal,and cell-type resolution is essential for deciphering brain complexity.Regulation of gene expression is a highly dynamic process aiming at the production of precise levels of gene products to guarantee optimal cellular function,in response to physiological cues.Speedy advances in next-generation sequencing enabled the understanding of epigenomic and transcriptomic dynamic landscapes of different brain regions along development,aging,and disease progression.However,the correlation of the“transcriptome”with protein levels is poor because numerous mRNAs are subjected to manipulation of their translation efficiency,to warrant a favorable result under certain conditions.Hence,it is widely accepted that regulation at the translation level is a vital layer of gene expression.Quantification of actively translated mRNA populations(i.e.,“translatome”)is a more reliable predictor of the“proteome”(Wang et al.,2020).

Inspires effective alternatives to backpropagation:predictive coding helps understand and build learning

Artificial neural networks are capable of machine learning by simulating the hiera rchical structure of the human brain.To enable learning by brain and machine,it is essential to accurately identify and correct the prediction errors,referred to as credit assignment(Lillicrap et al.,2020).It is critical to develop artificial intelligence by understanding how the brain deals with credit assignment in neuroscience.

The COVID-19 vaccination campaign in Bhutan: strategy and enablers

Bhutan has reported a total of 2596 COVID-19 cases and three deaths as of September 15,2021.With support from India,the United States,Denmark,the People’s Republic of China,Croatia and other countries,Bhutan was able to conduct two rounds of nationwide vaccination campaign.While many countries struggle to overcome vaccine refusal or hesitancy due to complacency,a lack of trust,inconvenience and fear,escalated in some countries by anti-vaccine groups,Bhutan managed to inoculate more than 95%of its eligible populations in two rounds of vaccination campaign.Enabling factors of this successful vaccination campaign were strong national leadership,a well-coordinated national preparedness plan,and high acceptability of vaccine due to effective mass communication and social engagement led by religious figures,volunteers and local leaders.In this short report,we described the national strategic plan and enabling factors that led to the success of this historical vaccination campaign.

A multilevel process view of organizational knowledge transfer: enablers versus barriers

The importance of knowledge as a strategic asset for organizations has been recognized by both researchers and practitioners.To gain a competitive advantage,firms are required to effectively manage their knowledge resources.The most central activity in managing knowledge is to ensure its transfer within and between organizations.Knowledge transfer(KT)has thus been recognized as a key component of the knowledge management processes.The purpose of this research is to provide a holistic view of the KT barriers and enablers within an organization,from a multilevel and process-based perspectives.We first review the extant literature to identify the key enablers and barriers to KT.Second,we develop a multilevel conceptualization of enablers and barriers that can influence KT at different levels–individual,team/exchange and organization.The proposed model improves current understanding of KT by offering a holistic and integrated view of enablers and barriers.

Dendritic Deep Learning for Medical Segmentation

Dear Editor,This letter presents a novel segmentation approach that leverages dendritic neurons to tackle the challenges of medical imaging segmentation.In this study,we enhance the segmentation accuracy based on a SegNet variant including an encoder-decoder structure,an upsampling index,and a deep supervision method.Furthermore,we introduce a dendritic neuron-based convolutional block to enable nonlinear feature mapping,thereby further improving the effectiveness of our approach.

Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications

Osteoarthritis(OA)is a debilitating degenerative disease affecting multiple joint tissues,including cartilage,bone,synovium,and adipose tissues.OA presents diverse clinical phenotypes and distinct molecular endotypes,including inflammatory,metabolic,mechanical,genetic,and synovial variants.Consequently,innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches.Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints,causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues.This issue has led to standardization difficulties and hindered the success of clinical trials.Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues,encompassing DNA,RNA,metabolites,and proteins,as well as their chemical properties,elemental composition,and mechanical attributes,can contribute to a more comprehensive understanding of the disease subtypes.Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment,providing a more holistic view of cellular function.Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various-omics lenses,such as genomics,transcriptomics,proteomics,and metabolomics,with spatial data.This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates.Furthermore,advanced imaging techniques,including high-resolution microscopy,hyperspectral imaging,and mass spectrometry imaging,enable the visualization and analysis of the spatial distribution of biomolecules,cells,and tissues.Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes.This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis.It explores their applications,challenges,and potential opportunities in the field of OA.Additionally,this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.

Implantable probe with integrated reference electrode for in situ neural signal and calcium ion monitoring

Monitoring the electrophysiology activity of neurons and blood calcium signals can enable a better understanding of disease-related neural system circuits.However,currently,in situ calcium ion monitoring tools are scarce and exhibit low integration and limited sensitivity.In this letter,we propose an implantable probe with an integrated in situ Ag/AgCl reference electrode(ISA/ARE)that can monitor action potential(AP)and Ca^(2+) concentrations.

Proteins as nanomagnets and magnetoreceptors

It is an appealing notion that a protein molecule could act as a nanomagnet.A genetically encodable biomolecule with a permanent magnetic moment at room temperature could have a range of applications:a magnetogenetic actuator,a magnetic tag for purifying and immobilizing enzymes,a contrast agent for magnetic resonance imaging,and a basis for a biomimetic magnetic sensing device,to name just a few.A magnetic protein could perhaps also function as the sensor in the magnetic compass that enables small songbirds to navigate the huge distances between their breeding and wintering grounds.Attractive though such possibilities may be,how realistic are they?

Deep Reinforcement Learning or Lyapunov Analysis?A Preliminary Comparative Study on Event-Triggered Optimal Control

Dear Editor,This letter develops a novel method to implement event-triggered optimal control(ETOC) for discrete-time nonlinear systems using parallel control and deep reinforcement learning(DRL), referred to as Deep-ETOC. The developed Deep-ETOC method introduces the communication cost into the performance index through parallel control, so that the developed method enables control systems to learn ETOC policies directly without triggering conditions.

Current-Induced Magnetization Switching Behavior in Perpendicular Magnetized L1_(0)-MnAl/B2-CoGa Bilayer

Rare-earth-free Mn-based binary alloy L1_(0)-MnAl with bulk perpendicular magnetic anisotropy(PMA) holds promise for high-performance magnetic random access memory(MRAM) devices driven by spin-orbit torque(SOT). However, the lattice-mismatch issue makes it challenging to place conventional spin current sources, such as heavy metals, between L1_(0)-MnAl layers and substrates. In this work, we propose a solution by using the B2-CoGa alloy as the spin current source. The lattice-matching enables high-quality epitaxial growth of 2-nm-thick L1_(0)-MnAl on B2-CoGa, and the L1_(0)-MnAl exhibits a large PMA constant of 1.04 × 10^(6)J/m^(3). Subsequently, the considerable spin Hall effect in B2-CoGa enables the achievement of SOT-induced deterministic magnetization switching. Moreover, we quantitatively determine the SOT efficiency in the bilayer. Furthermore, we design an L1_(0)-MnAl/B2-CoGa/Co_(2)MnGa structure to achieve field-free magnetic switching. Our results provide valuable insights for achieving high-performance SOT-MRAM devices based on L1_(0)-MnAl alloy.

Discontinuities of Banana Integrals in Dispersion Relation Representation

We derive the discontinuities of banana integrals using the dispersion relation iteratively,and find a series of identities between the parameterized discontinuities of banana integrals(p-DOBIs).Similar to elliptic integrals,these identities enable the reduction of various p-DOBIs to be a linear combination of some fundamental ones.We present a practical application of p-DOBIs for deriving the Picard–Fuchs operator.Then we establish the expression of generalized dispersion relation,which enables us to obtain the dispersion relation representation of arbitrary banana integrals.Moreover,we propose a hypothesis for generalized dispersion relation and p-DOBIs,which provides a simple way to calculate the discontinuities and transform dispersion relation representation to p-DOBIs.

A magic organic molecule assembled capping layer enables airprocessed α-FAPbI_(3) perovskite solar cell with state-of-the-art performances

The black-phase formamidine-lead iodide(α-FAPbI_(3)),boasting an optimal bandgap of 1.5 eV,stands out as a premier choice for narrow-bandgap perovskite solar cells(PSCs),achieving a certified power conversion efficiency(PCE)of 26.1%[1−5].This impressive performance hinges on the orderly and homogeneous crystallization ofα-phase pure FAPbI_(3),facilitated by coordinating solvents such as dimethyl sulfoxide(DMSO)to form intermediates like PbI_(2)-DMSO complex(D-complex).The D-complex plays a pivotal role in crystallization thermodynamics,enabling the direct formation of α-FAPbI_(3) without the photoinactiveδ-phase[6−9].However,DMSO,a commonly used coordinating solvent,is highly hygroscopic and prone to hydration upon moisture exposure.This tendency leads to incomplete perovskite crystallization and accelerates the transformation of α-FAPbI_(3) into itsδ-phase[2,10].Consequently,the best-performing α-FAPbI_(3)PSCs must be processed in an inert atmosphere with strictly controlled relative humidity(RH)and suffers from relatively poor reproducibility.Given the hard-to-control atmosphere at industrial scale,it is challenging yet imperative to eliminate the negative effects stemming from hygroscopic coordinating solvents[11−13].

How to manage the malposition of deep vein catheterization into the artery?

Central venous catheterization establishes temporary,efficient,and rapid use of deep venous access in patients,which provides high flow rate fluid perfusion,enables measurement of central venous pressure,and acts as an important reference for clinical decision-making.However,various complications such as pneumothorax,hemothorax,hematoma,and puncture failure can easily occur during the puncture and catheterization process.

Enabling Technologies for Autonomous Robotic Systems in Manufacturing

Research of autonomous manufacturing systems is motivated both by the new technical possibilities of cyber-physical systems and by the practical needs of the industry.Autonomous operation in semi-structured industrial environments can now be supported by advanced sensor technologies,digital twins,artificial intelligence and novel communication techniques.These enable real-time monitoring of production processes,situation recognition and prediction,automated and adaptive(re)planning,teamwork and performance improvement by learning.This paper summarizes the main requirements towards autonomous industrial robotics and suggests a generic workflow for realizing such systems.Application case studies will be presented from recent practice at HUN-REN SZTAKI in a broad range of domains such as assembly,welding,grinding,picking and placing,and machining.The various solutions have in common that they use a generic digital twin concept as their core.After making general recommendations for realizing autonomous robotic solutions in the industry,open issues for future research will be discussed.

Building mm Wave on the Evolving C-V2X:mm Wave NR-V2X

Since the evolving standardization of cellular V2X(C-V2X)technologies is continuously developed by 3GPP,research on new radio(NR-V2X)has been on schedule by academic and industries.Though millimeter wave(mm Wave)frequency band is supposed to provide large transmission bandwidth,yet the development of mm Wave band in NR-V2X is still in preliminary stage.In this article,a comprehensive discussion of mm Wave NR-V2X is given covering trends,standardization landscape,and enabling technologies,aiming at tackling the challenge of channel modeling,directional channel access,beamforming and blockage management.The vision of mm Wave NR-V2X is to fully support the development of automated driving,holographic control display and improved in-car infotainment for the future.

Global AI Governance:Realistic Difficulties,Mode Selection,and Chinese Solutions

Today,global AI governance is still in the exploratory stage,and the complex nature and uncertainty of technology require global collaboration.THE rapid advancement of artificial intelligence(AI)technology has undoubtedly become the center of global attention in recent years,especially generative AI technology.This technology is rapidly shaping the trends of digital society,while its risks are also spreading,thus making it imperative to strengthen global AI governance so as to enable effective risk control.

GE 64排128层螺旋CT图像伪影故障维修1例

0引言GE 64排128层螺旋CT是一款高档容积CT（volume CT,VCT）,具有扫描速度快、检查范围大、剂量低、应用新、视野大和图像分辨率高的特点[1]。但经较长时间运行或其他原因,也出现了一些故障。作者总结了在CT维修实践中遇到的1例由探测器造成伪影的故障,以供同行参考。1故障现象机器正常扫描时突然出现宽带高密度的环形伪影,如图1所示。重启机器扫描,图像伪影依然存在,