Uniform Target Research Articles

Leveraging Universal Adversarial Perturbation and Frequency Band Filters Against Face Recognition

Universal adversarial perturbation (UAP) exhibits universality as it is independent of specific images. Although previous investigations have shown that the classification of natural images is susceptible to universal adversarial attacks, the impact of UAP on face recognition has not been fully investigated. Thus, in this paper we assess the vulnerability of face recognition for UAP. We propose FaUAP-FBF, which exploits the frequency domain by learning high, middle, and low band filters as an additional dimension of refining facial UAP. The facial UAP and filters are alternately and repeatedly learned from a training set. Furthermore, we convert non-target attacks to target attacks by customizing a target example, which is an out-of-distribution sample for a training set. Accordingly, non-target and target attacks form a uniform target attack. Finally, the variance of cosine similarity is incorporated into the adversarial loss, thereby enhancing the attacking capability. Extensive experiments on LFW and CASIA-WebFace datasets show that FaUAP-FBF has a higher fooling rate and better objective stealthiness metrics across the evaluated network structures compared to existing universal adversarial attacks, which confirms the effectiveness of the proposed FaUAP-FBF. Our results also imply that UAP poses a real threat for face recognition systems and should be taken seriously when face recognition systems are being designed.

Strengths and complementarity of systematic conservation planning and key biodiversity area approaches for spatial planning.

Developing biodiversity-inclusive spatial plans at a national level is the focus of Target 1 of the Kunming-Montreal Global Biodiversity Framework (KMGBF). There are 2 general approaches to identifying areas of value for biodiversity plans: criteria-based, such as the Key Biodiversity Areas (KBA) process, and systematic conservation planning (SCP) approaches, which apply complementarity to efficiently achieve specific quantitative targets. We examined the benefits of both approaches and considered how the KBA approach can best complement SCP. We reviewed 200 papers articles that applied SCP to real-world data with the Marxan conservation design software. Our review showed that targets for biodiversity elements are poorly selected in many SCP publications, with more than 75% of the studies applying uniform percentage target amounts to planning elements. Uniform targets favor more widespread species and ecosystems that are likely to be more common and less important for conservation. The strengths and complementarities of KBA and SCP approaches were reviewed and we identified the elements from both approaches that should be considered for spatial planning to achieve Target 1 in the KMGBF. In particular, the global approach of KBAs (i.e., identifying sites of global significance for species or ecosystems) better complements SCP, which often has a national or subnational focus. The KMGBF will fail if conservation of globally significant sites is not targeted and these sites are not incorporated in national spatial planning.

Beyond the 95s: What happens when uniform program targets are applied across a heterogenous HIV epidemic in Eastern and Southern Africa?

The UNAIDS 95-95-95 targets are an important metric for guiding national HIV programs and measuring progress towards ending the HIV epidemic as a public health threat by 2030. Nevertheless, as proportional targets, the outcome of reaching the 95-95-95 targets will vary greatly across, and within, countries owing to the geographic diversity of the HIV epidemic. Countries and subnational units with a higher initial prevalence and number of people living with HIV (PLHIV) will remain with a larger number and higher prevalence of virally unsuppressed PLHIV—persons who may experience excess morbidity and mortality and can transmit the virus to others. Reliance on achievement of uniform proportional targets as a measure of program success can potentially mislead resource allocation and progress towards equitable epidemic control. More granular surveillance information on the HIV epidemic is required to effectively calibrate strategies and intensity of HIV programs across geographies and address current and projected health disparities that may undermine efforts to reach and sustain HIV epidemic control even after the 95 targets are achieved.

Stepwise dual-target magnetic resonance-guided focused ultrasound in tremor-dominant Parkinson disease: One-year follow-up.

Magnetic resonance-guided focused ultrasound (MRgFUS) is a nonsurgical treatment for Parkinson disease (PD). Some selected anatomical structures can be targeted by MRgFUS in PD. However, there is no uniform target yet. We have reported that stepwise dual-target MRgFUS was successfully applied to treat refractory tremors with akinetic-rigid features in PD. It generated two precise thermal ablations in the ventral intermediate nucleus (VIM) and pallidothalamic tract (PTT). Here, we report more PD patients to verify the safety and efficacy of stepwise dual-target MRgFUS. Ten tremor-dominant PD patients (mean age = 66.7 ± 3.2 years, eight men) received the stepwise dual-target MRgFUS treatment with a series of primary and secondary outcome measures. The VIM and PTT were navigated based on brain magnetic resonance images. Outcome measures were categorized into primary and secondary assessments. The primary outcome measures consisted of resting tremor, action/kinetic tremor, rigidity, and bradykinesia. Secondary outcome measures encompassed non-motor symptoms scale of PD. Data collected at follow-up time points, including 1 day, 3 months, 6 months, and 1 year posttreatment, were compared with baseline data. The severity of tremor and motor deficits represented by Clinical Rating Scale for Tremor parts A and B during off-medication status and Unified Parkinson's Disease Rating Scale III on the treated side were significantly improved (p < 0.05 by paired t-test) at 1-year follow-up. At the 1-year follow-up, significant improvement was observed in the non-motor symptoms scale. Additionally, no severe adverse effects were reported, except temporary treatment-related discomfort during the procedure. In conclusion, stepwise dual-target MRgFUS emerges as a safe and effective therapeutic modality for PD patients, particularly in addressing medication-refractory tremor and akinetic-rigid syndrome.

Microjet printing of metal salt or oxide targets for nuclear reaction studies on radionuclides

Radioactive targets for direct measurements of neutron-induced reactions are required to improve evaluated cross-section data and, ultimately, the fidelity of neutron reaction network simulations. Electrodeposition and molecular plating are the current state-of-the-art radioactive target production techniques, but not all metals can be electrodeposited or molecular plated with high yields. Alternative techniques can be expensive or may produce targets that are unsatisfactory in terms of thickness, yield, or purity. Microjet printing is a new, rather inexpensive technique that utilizes equipment with a small footprint and has the potential to produce thin, highly radioactive targets with good uniformity and minimal impurities from the target fabrication process. This study involved optimizing the process of producing microjet printed targets to allow for the fabrication of a stable vanadium(V) oxide (V2O5) target that was compared with an analogous electrodeposition V2O5 target manufactured via the application of a vanadium chemical conversion coating on aluminum (Al) foil. The results from these studies suggest microjet printing could be used to produce relatively uniform target layers with adequate film thicknesses (<15μm). V2O5 microjet printed targets, when compared with chemical conversion coating V2O5 targets, appeared to be qualitatively less uniform and quantitatively larger in thickness (11.7(27) μm vs. 5.3(18) μm). However, the conversion coating target contained more impurities and the Al backing had a higher background contribution to measurements of neutron-induced reactions as opposed to targets produced via microjet printing. Overall, the results from this study suggest microjet printing has the capability to be an excellent alternative target production technique to the electrodeposition and molecular plating methods.

Temporal Monitoring of Simulated Burials in an Arid Environment Using RGB/Multispectral Sensor Unmanned Aerial Vehicles

For the first time, RGB and multispectral sensors deployed on UAVs were used to facilitate grave detection in a desert location. The research sought to monitor surface anomalies caused by burials using manual and enhanced detection methods, which was possible up to 18 months. Near-IR (NIR) and Red-Edge bands were the most suitable for manual detection, with a 69% and 31% success rate, respectively. Meanwhile, the enhanced method results varied depending on the sensor. The standard Reed–Xiaoli Detector (RXD) algorithm and Uniform Target Detector (UTD) algorithm were the most suitable for RGB data, with 56% and 43% detection rates, respectively. For the multispectral data, the percentages varied between the algorithms with a hybrid of the RXD and UTD algorithms yielding a 56% detection rate, the UTD algorithm 31%, and the RXD algorithm 13%. Moreover, the research explored identifying grave mounds using the normalized digital surface model (nDSM) and evaluated using the normalized difference vegetation index (NDVI) in grave detection. nDSM successfully located grave mounds at heights as low as 1 cm. A noticeable difference in NDVI values was observed between the graves and their surroundings, regardless of the extreme weather conditions. The results support the potential of using RGB and multispectral sensors mounted on UAVs for detecting burial sites in an arid environment.

Targeting the transferrin receptor to transport antisense oligonucleotides across the mammalian blood-brain barrier.

Antisense oligonucleotides (ASOs) are promising therapeutics for treating various neurological disorders. However, ASOs are unable to readily cross the mammalian blood-brain barrier (BBB) and therefore need to be delivered intrathecally to the central nervous system (CNS). Here, we engineered a human transferrin receptor 1 (TfR1) binding molecule, the oligonucleotide transport vehicle (OTV), to transport a tool ASO across the BBB in human TfR knockin (TfRmu/hu KI) mice and nonhuman primates. Intravenous injection and systemic delivery of OTV to TfRmu/hu KI mice resulted in sustained knockdown of the ASO target RNA, Malat1, across multiple mouse CNS regions and cell types, including endothelial cells, neurons, astrocytes, microglia, and oligodendrocytes. In addition, systemic delivery of OTV enabled Malat1 RNA knockdown in mouse quadriceps and cardiac muscles, which are difficult to target with oligonucleotides alone. Systemically delivered OTV enabled a more uniform ASO biodistribution profile in the CNS of TfRmu/hu KI mice and greater knockdown of Malat1 RNA compared with a bivalent, high-affinity TfR antibody. In cynomolgus macaques, an OTV directed against MALAT1 displayed robust ASO delivery to the primate CNS and enabled more uniform biodistribution and RNA target knockdown compared with intrathecal dosing of the same unconjugated ASO. Our data support systemically delivered OTV as a potential platform for delivering therapeutic ASOs across the BBB.

Optimisation Design of Thermal Test System for Metal Fibre Surface Combustion Structure

The metal fibre surface combustion structure has the characteristics of strong thermal matching ability, short response time, and strong shape adaptability. It has more advantages in the thermal test of complex hypersonic vehicle surface inlet, leading edge, etc. In this paper, a method of aerodynamic thermal simulation test based on metal fibre surface combustion is proposed. The aim of the study was to create a uniform target heat flow on the inner wall surface of a cylindrical specimen by matching the gas jet flow rate and the geometry of the combustion surface. The research adopted the optimisation design method based on the surrogate model to establish the numerical calculation model of a metal fibre combustion jet heating cylinder specimen. One hundred sample points were obtained through Latin hypercube sampling, and a database of design parameters and heat flux was established through numerical simulation. The kriging surrogate model and the non-dominated sequencing genetic optimisation algorithm with elite strategy were adopted. A bi-objective optimisation design was carried out with the optimisation objective of the coincidence between the predicted and the target heat flux on the inner wall of the specimen. The results showed that the average relative errors of heat flow density on the specimen surface were 8.8% and 6% through the leave-one-out cross-validation strategy and the validation of six test sample points, respectively. The relative error values in most regions were within 5%, which indicates that the established kriging surrogate model has high prediction accuracy. Under the optimal solution conditions, the numerical calculation results of the heat flow on the inner wall of the specimen were in good agreement with the target heat flow values, with an average relative error of less than 5% and a maximum value of less than 8%. These results show that the optimisation design method based on the kriging surrogate model can effectively match the thermal test parameters of metal fibre combustion structures.

Investigation of intra-fractionated range guided adaptive proton therapy (RGAPT): II. Range-shift compensated on-line treatment adaptation and verification

We previously proposed range-guided adaptive proton therapy (RGAPT) that uses mid-range treatment beams as probing beams and intra-fractionated range measurements for online adaptation. In this work, we demonstrated experimental verification and reported the dosimetric accuracy for RGAPT. A STEEV phantom was used for the experiments, and a 3 × 3 × 3 cm3 cube inside the phantom was assigned to be the treatment target. We simulated three online range shift scenarios: reference, overshoot, and undershoot, by placing upstream Lucite sheets, 4, 0, and 8 that corresponded to changes of 0, 6.8, and −6.8 mm, respectively, in water-equivalent path length. The reference treatment plan was to deliver single-field uniform target doses in pencil beam scanning mode and generated on the Eclipse treatment planning system. Different numbers of mid-range layers, including single, three, and five layers, were selected as probing beams to evaluate beam range (BR) measurement accuracy in positron emission tomography (PET). Online plans were modified to adapt to BR shifts and compensate for probing beam doses. In contrast, non-adaptive plans were also delivered and compared to adaptive plans by film measurements. The mid-range probing beams of three (5.55MU) and five layers (8.71MU) yielded accurate range shift measurements in 60 s of PET acquisition with uncertainty of 0.5 mm while the single-layer probing (1.65MU) was not sufficient for measurements. The adaptive plans achieved an average gamma (2%/2 mm) passing rate of 95%. In contrast, the non-adaptive plans only had an average passing rate of 69%. RGAPT planning and delivery are feasible and verified by the experiments. The probing beam delivery, range measurements, and adaptive planning and delivery added a small increase in treatment delivery workflow time but resulted in substantial dose improvement. The three-layer mid-range probing was most suitable considering the balance of high range measurement accuracy and the low number of probing beam layers.

Risk-Targeted Seismic Design Maps with Aleatory and Epistemic Uncertainty in Tehran and Surrounding Areas

ABSTRACT This study aims to introduce a risk-targeted probabilistic model that facilitates seismic design hazard mapping. Here, we investigate how to incorporate hazard regional variations and different structural fragility typologies so as to achieve a uniform target risk across the map. This paper takes Tehran, the capital city, and its surrounding area as a case study and explores the highly digitized hazard curves conditioned on the time-dependent occurrence of an earthquake at a 50-year exposure time. We introduce a new set of parameterized quantile functions for Risk-targeted design Intensity Measure (IMR) as the seismic design hazard. A group of IMR maps is subsequently prepared based on a 1% collapse probability during the next 50-year lifetime. Furthermore, the quantile function corresponding to each fragility type is able to show the aleatory uncertainty at each site on the region map. The uncertainty maps illustrate relatively less inherent variability than what exists in the hazard curves themselves. Then, we tackle the source of uncertainty arising from percentile hazard curves into IMR, known as epistemic uncertainty, by deriving a new closed-form expression, which allows for a sampling-free estimation of the epistemic uncertainty. The risk-targeted seismic design hazard with its accompanying uncertainties can lead to a promising seismic design hazard with potential applications for the insurance industry, urban planners, and risk-aware building owners.

Tumor-Targeted cRGD-Coated Liposomes Encapsulating Optimized Synergistic Cepharanthine and IR783 for Chemotherapy and Photothermal Therapy.

Combination therapy offers superior therapeutic results compared to monotherapy. However, the outcomes of combination therapy often fall short of expectations, mainly because of increased toxicity from drug interactions and challenges in achieving the desired spatial and temporal distribution of drug delivery. Optimizing synergistic drug combination ratios to ensure uniform targeting and distribution across space and time, particularly in vivo, is a significant challenge. In this study, cRGD-coated liposomes encapsulating optimized synergistic cepharanthine (CEP; a chemotherapy drug) and IR783 (a phototherapy agent) were developed for combined chemotherapy and photothermal therapy in vitro and in vivo. An MTT assay was used to evaluate the combination index of CEP and IR783 in five cell lines. The cRGD-encapsulated liposomes were prepared via thin-film hydration, and unencapsulated liposomes served as controls for the loading of CEP and IR783. Fluorescence and photothermal imaging were used to assess the efficacy of CEP and IR783 encapsulated in liposomes at an optimal synergistic ratio, both in vitro and in vivo. The combination indices of CEP and IR783 were determined in five cell lines. As a proof-of-concept, the optimal synergistic ratio (1:2) of CEP to IR783 in 4T1 cells was evaluated in vitro and in vivo. The average diameter of the liposomes was approximately 100 nm. The liposomes effectively retained the encapsulated CEP and IR783 in vitro at the optimal synergistic molar ratio for over 7 d. In vivo fluorescence imaging revealed that the fluorescence signal from cRGD-CEP-IR783-Lip was detectable at the tumor site at 4 h post-injection and peaked at 8 h. In vivo photothermal imaging of tumor-bearing mice indicated an increase in tumor temperature by 32°C within 200 s. Concurrently, cRGD-CEP-IR783-Lip demonstrated a significant therapeutic effect and robust biosafety in the in vivo antitumor experiments. The combination indices of CEP and IR783 were successfully determined in vitro in five cell lines. The cRGD-coated liposomes encapsulated CEP and IR783 at an optimal synergistic ratio, exhibiting enhanced antitumor effects and targeting upon application in vitro and in vivo. This study presents a novel concept and establishes a research framework for synergistic chemotherapy and phototherapy treatment.

Biological optimization for hybrid proton-photon radiotherapy

Objective. Hybrid proton-photon radiotherapy (RT) is a cancer treatment option to broaden access to proton RT. Additionally, with a refined treatment planning method, hybrid RT has the potential to offer superior plan quality compared to proton-only or photon-only RT, particularly in terms of target coverage and sparing organs-at-risk (OARs), when considering robustness to setup and range uncertainties. However, there is a concern regarding the underestimation of the biological effect of protons on OARs, especially those in close proximity to targets. This study seeks to develop a hybrid treatment planning method with biological dose optimization, suitable for clinical implementation on existing proton and photon machines, with each photon or proton treatment fraction delivering a uniform target dose. Approach. The proposed hybrid biological dose optimization method optimized proton and photon plan variables, along with the number of fractions for each modality, minimizing biological dose to the OARs and surrounding normal tissues. To mitigate underestimation of hot biological dose spots, proton biological dose was minimized within a ring structure surrounding the target. Hybrid plans were designed to be deliverable separately and robustly on existing proton and photon machines, with enforced uniform target dose constraints for the proton and photon fraction doses. A probabilistic formulation was utilized for robust optimization of setup and range uncertainties for protons and photons. The nonconvex optimization problem, arising from minimum monitor unit constraint and dose-volume histogram constraints, was solved using an iterative convex relaxation method. Main results. Hybrid planning with biological dose optimization effectively eliminated hot spots of biological dose, particularly in normal tissues surrounding the target, outperforming proton-only planning. It also provided superior overall plan quality and OAR sparing compared to proton-only or photon-only planning strategies. Significance. This study presents a novel hybrid biological treatment planning method capable of generating plans with reduced biological hot spots, superior plan quality to proton-only or photon-only plans, and clinical deliverability on existing proton and photon machines, separately and robustly.

Abstract 5239: Discovery of AML associated therapeutic targets

Abstract Chimeric Antigen Receptor T-cell (CART) immunotherapy has shown significant success in the treatment of hematological malignancies. However, their efficacy in AML is limited due to the disease's genetic diversity and lack of uniform antigen targets. To identify potential AML cell-surface markers, we employed a comprehensive approach that involved the utilization of 3' single-cell RNA sequencing (scRNA-seq), bulk RNA sequencing (RNA-seq), and enhanced whole exome sequencing (eWES). A total of 21 samples were analyzed, comprising 18 distinct AML patients and 3 healthy bone marrow aspirates, serving as controls. We conducted scRNAseq on 21 samples, yielding a total of 185,106 high-quality cells, which were effectively clustered into 38 unbiased groups. Notably, tumor clusters exhibited highest copy number variations and formed separate clusters from other non-tumor immune cells. To uncover key functional pathways, we conducted pathway enrichment analysis comparing tumor cells to non-tumor cells. Our findings demonstrated a significant overrepresentation of cellular processes related to Allograft rejection, IL2/STAT5 signaling, IFN-gamma response and apoptosis. To identify AML specific markers, we performed an unbiased systematic search of the scRNAseq dataset for genes with unique expression patterns in tumor cells compared to the healthy bone marrow controls. Our analysis identified differentially expressed genes, with many genes displaying relative cell and tissue specificity. Notably, among these genes, we unveiled key potential targets with cell surface specificity, including novel markers alongside previously known ones. Noteworthy candidates, such as ADGRE2, CD33, CD123, CLEC12A, and FLT3 and understudied novel markers such as CD86, CSF1R, S100 proteins and VMP1, were prominently expressed, showcasing their potential significance as targets for engineered immunotherapy. To validate and consolidate our discoveries, we conducted a cross-referencing exercise by comparing our scRNAseq data against bulk RNA data from primary human AML samples and cell lines. Bulk global proteomics, flow cytometry-based and CART generation studies are ongoing to confirm our discoveries. Our rigorous computational and experimental approach provides valuable insights into tumor-specific cell surface proteins, which hold promise as potential targets for innovative and precision immunotherapeutic interventions in the realm of AML treatment. Citation Format: Omar M. Ibrahim, Michael P. Rettig, Reyka G. Jayasinghe, Li Ding, John F. DiPersio. Discovery of AML associated therapeutic targets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5239.

When lattice bases are Markov bases

Sampling the fibre comprising the solutions of a linear inverse problem for count data is an important practical problem. Connectivity of the sampler is guaranteed only if a Markov basis, defining a sufficiently rich variety of sampling directions, is available. Computation of a Markov basis is typically challenging, and the mixing properties of the resulting sampler can be poor. However, for some problems a suitably chosen lattice basis will be a Markov basis. We provide an easily checkable condition for the existence of such a lattice Markov basis, and demonstrate that associated hit-and-run samplers will mix rapidly for uniform target distributions.

A Novel Framework for Thermoradiotherapy Treatment Planning

Thermoradiotherapy combines radiation therapy with hyperthermia to increase therapeutic effectiveness. Currently, both modalities are optimized separately and in state-of-the-art research the enhanced therapeutic effect is evaluated using equivalent radiation dose in 2-Gy fractions (EQD2). This study proposes a novel thermoradiotherapy treatment planning framework with voxelwise EQD2 radiation therapy optimizing including thermal radiosensitization and direct thermal cytotoxicity. To demonstrate proof-of-concept of the planning framework, 3 strategies consisting of 20 radiation therapy fractions were planned for 4 prostate cancer cases with substantially different temperature distributions: (1) Conventional radiation therapy plan of 60 Gy combined with 4 hyperthermia sessions (RT60 + HT), (2) standalone uniform dose escalation to 68 Gy without hyperthermia (RT68), and (3) uniform target EQD2 that maximizes the tumor control probability (TCP) accounting for voxelwise thermal effects of 4 hyperthermia sessions without increasing normal tissue doses (RTHT + HT). Assessment included dose, EQD2, TCP, and rectal normal tissue complication probability (NTCP), alongside robustness analyses for TCP and NTCP against parameter uncertainties. The estimated TCP of around 76% for RT60 without hyperthermia was increased to an average of 85.9% (range, 81.3%-90.5%) for RT60 + HT, 92.5% (92.4%-92.5%) for RT68, and 94.4% (91.7%-96.6%) for RTHT + HT. The corresponding averaged rectal NTCPs were 8.7% (7.9%-10.0%), 14.9% (13.8%-17.1%), and 8.4% (7.5%-9.7%), respectively. RT68 and RTHT + HT exhibited slightly enhanced TCP robustness against parameter uncertainties compared with RT60 + HT, and RT68 presented higher and less robust rectal NTCP values compared with the other planning strategies. This study introduces an innovative thermoradiotherapy planning approach, integrating thermal effects into EQD2-based radiation therapy optimization. Results demonstrate an ability to achieve enhanced and uniform target EQD2 and TCP across various temperature distributions without elevating normal tissue EQD2 or NTCP compared with conventional methods. Although promising for improving clinical outcomes, realizable enhancements depend on accurate tumor- and tissue-specific data and precise quantification of hyperthermic effects, which are seamlessly integrable in the planning framework as they emerge.

A reinforcement learning agent for head and neck intensity-modulated radiation therapy

Head and neck (HN) cancers pose a difficult problem in the planning of intensity-modulated radiation therapy (IMRT) treatment. The primary tumor can be large and asymmetrical, and multiple organs at risk (OARs) with varying dose-sparing goals lie close to the target volume. Currently, there is no systematic way of automating the generation of IMRT plans, and the manual options face planning quality and long planning time challenges. In this article, we present a reinforcement learning (RL) model for the purposes of providing automated treatment planning to reduce clinical workflow time as well as providing a better starting point for human planners to modify and build upon. Several models with progressing complexity are presented, including the relevant plan dosimetry analysis and model interpretations of the resulting strategies learned by the auto-planning agent. Models were trained on a set of 40 patients and validated on a set of 20 patients. The presented models are shown to be consistent with the requirements of an RL model to be underpinned by a Markov decision process (MDP). In-depth interpretability of the models is presented by examination of the decision space using action hyperplanes. The auto-planning agent was able to generate plans with superior reduction in the mean dose of the left and right parotid glands by approximately 7 Gy ± 2.5 Gy (p &amp;lt; 0.01) over a starting, static template plan with only pre-defined general prescription information. RL plans were comparable to a human expert’s clinical plans for the primary (44 Gy), boost (26 Gy) , and the summed plans (70 Gy) with p-values of 0.43, 0.72, and 0.67, respectively, for the dosimetric endpoints and uniform target coverage normalization. The RL planning agent was able to produce the plans used in validation in an average of 13.58 min, with a minimum and a maximum planning time of 2.27 and 44.82 min, respectively.

Vancomycin AUC-Based Dosing Practices in a Non-Teaching Community Hospital and Associated Outcomes: A One-Year Survey of Uniform Targets for Infections with or without MRSA.

Intravenous (IV) vancomycin area under the curve (AUC)-based dosing is used uniformly for Gram-positive organisms in non-teaching community hospitals. However, evidence for using vancomycin AUC-based dosing for non-methicillin-resistant Staphylococcus aureus (non-MRSA) and less serious infections is limited in the literature. A gap in the literature also exists with respect to comparisons between the outcomes that can be derived using the regimens suggested by Bayesian programs and target doses of the AUC of 400-499 and 500-600. A retrospective review of all patients hospitalized in a non-teaching community hospital who used AUC-based vancomycin was performed over a 1-year period. Only 17.6% of the included patients had confirmed MRSA. The values for the overall early response rate, 30-day all-cause mortality, and rate of acute kidney injury (AKI) were 50.3%, 11.3%, and 3.8%, respectively, in this population. In regression analysis, compared to non-MRSA infections, a significantly higher rate of early response was seen in patients with MRSA (unadjusted OR = 2.68, 95% CI [1.06-6.76] p = 0.04). Patients in the AUC 400-499 group had a non-significant higher incidence of 30 d mortality and new AKI compared to patients in the AUC 500-600 group. In our Kaplan-Meier survival analysis, there was no statistically significant difference between the comparison groups. Early response was lower in patients with non-MRSA compared to patients with MRSA despite achieving the AUC target. There was no apparent difference in clinical outcomes between the higher and lower AUC groups. Further large-scale research is needed to confirm these findings.

Study and development of diagnostic systems to characterise the extraction region in SPIDER

SPIDER, an RF-driven negative ion source in the Neutral Beam Test Facility (NBTF), serves as the prototype for ITER's neutral beam injector (NBI). It is composed of 8 drivers powered by 4 RF generators, aiming to accelerate 50 A of negative hydrogen ions to 100 KeV with a beam uniformity target of 10%. The experiment, launched in 2018, tested negative ion production using caesium. Results match those of similar facilities, but SPIDER faces challenges due to its size, multiple drivers, and non-uniform plasma expansion. These issues impact beam uniformity, preventing the machine from reaching expected performance. To address this, SPIDER initiated a significant shutdown at the end of 2021 for improvements.One the most important aspects studied during the first experimental campaign is source uniformity, addressed both in terms of plasma and of caesium distribution. The latter is particularly relevant since its quality is directly related to the beam uniformity and divergence. To have more insight about these issues, monitoring the plasma properties in the extraction region is crucial, hence in the present contribution, the design and development of two new diagnostic systems are described: a movable Langmuir probe and a Retarding Field Energy Analyser (RFEA).The first can provide a vertical scan of the main plasma parameters close to the plasma grid. The spatial resolution would improve with respect to the already installed set of fixed Langmuir probes embedded in the grid system, and the newly installed diagnostic could interact with other sensors to produce complementary measurements (namely, electron photo-detachment).The latter, instead, allows the monitoring of the positive ion energy distribution: positive ions, in fact, can be precursors of the negative ones produced at the caesiated surface, but also influence the energy of negative ion and their extraction probability and thus collecting information about their energy distribution allows inferring details about the extracted negative ion beam.The two diagnostics are designed focusing on the experimental constraint of integrating the diagnostics in a harsh and complex environment such as SPIDER plasma: a preliminary study of the placement inside the source is carried out, then the electrode of the movable probe and the RFEA sensor are sized according to the spatial and energy resolution requested by the system.

A Review Study of Sweeping and Normal Impingement Jets

This review focuses on the experimental and numerical studies of sweeping impingement jets that serve in cooling of hot surfaces. It is known that the impinging jets produce high-localized heat transfer coefficient. The sweeping jet covers a wider area on a hot target to improve the heat transfer rate, they could be used to increase the cooling rate of the impingement surface by disturbing the boundary layer. To display a readable survey, the current review was partitioned to four groups based on engineering configurations. The review shows that the sweeping nozzle gives better efficiency in heat transfer, improved Nusselt number and uniform target surface temperature, compared with the conventional normal jets. The current review reveals that the sweeping-jet mechanism can be achieved either by fluidic oscillator or by exciting a flexible wall forming an oscillating jet. Most of the fluidic oscillator researches are conducted experimentally (27%), while the researches that use flexible wall are about 24%.

The 2022 community-based integrated care reform in Italy: From desiderata to implementation

The Italian National Recovery and Resilience Plan allocated € 7 Bn for community care. In May 2022, the Italian government issued a Decree to define the strategy for the development of community-based integrated care. The reform aims to create uniformly a network of services close to where patients live, thus overcoming geographical disparities between regions. The strategy is based on a strong role of the central government in community care, but still leaves autonomy to regions. Levelling availability of services across territories, setting uniform targets with a short period horizon and disregarding starting points may create important implementation problems. Financial constraints will also hamper the implementation of the reform. Ultimately the development of Italian community care will depend on the institutional and managerial capabilities of regions and local health authorities. Firstly, they should shape the actual implementation of community care services by defining organizational arrangements, priority targets and models of care delivery. Secondly, they should develop strategies to face the lack of financial resources and the shortage of healthcare workforce. This contribution informs international readers about a major policy in a European country and its implementation challenges. It offers insights into inter-government relations in NHS-type healthcare systems (Nordic countries and Spain), showcasing the complexity of policymaking involving multiple political actors and resulting indeterminacy of policies and their implementation.