Miracle-dz/UniFAR-FTUs huggingface dataset:
Ambient sampling of real-world residential wood combustion plumes

ABSTRACT Wood smoke contains large quantities of carbonaceous aerosols known to increase climate forcing and be detrimental to human health. This paper reports the findings from our ambient sampling of fresh residential wood combustion (RWC) plumes in two heating seasons (2015–2016, 2016–2017) in Upstate New York. An Aethalometer (AE33) and a pDR-1500 were employed to monitor residential wood smoke plumes in Ithaca, NY through a hybrid mobile-stationary method. Fresh wood smoke plumes were captured and characterized at 13 different RWC sources in the city, all without significant influence from other combustion sources or atmospheric aging. Wood smoke absorption Ångström exponent (AAE) was estimated using both a one-component model, AAEWB, and a two-component model, AAEBrC (assuming AAEBC = 1.0). Consistent with the recent laboratory studies, our results show that AAEs were highly variable for residential wood smoke for the same source and across different sources, with AAEWB values ranging from 1.3 to 5.0 and AAEBrC values ranging from 2.2 to 7.4. This finding challenges the use of using a single AAE wood smoke value within the range of 1 to 2.5 for source apportionment studies. Furthermore, the PM2.5/BC ratio measured using optical instruments was demonstrated to be potentially useful to characterize burning conditions. Different wood smoke sources can be distinguished by their PM2.5/BC ratio, which range between 15 and 150. This shows promise as an in-situ, cost-effective, ambient sampling-based method to characterize wood burning conditions. Implications: There are two main implications from this paper. First, the large variability in wood smoke absorption Ångström exponent (AAE) values revealed from our real-world, ambient sampling of residential wood combustion plumes indicated that it is not appropriate to use a single AAE wood smoke value for source apportionment studies. Second, the PM2.5/BC ratio has been shown to serve as a promising in-situ, cost-effective, ambient sampling-based indicator to characterize wood burning conditions. This has the potential to greatly reduce the costs of insitu wood smoke surveillance.
Comparing costs and health care resource utilization between nmHSPC and mHSPC patients: a retrospective claims analysis

BACKGROUND: Prostate cancer is common among men in the United States, and hormone sensitive-prostate cancer (HSPC) is the predominant etiology. However, there is a paucity of evidence documenting the financial impact of metastatic disease within this etiology. OBJECTIVE: To estimate the differences in health care resource utilization (HCRU) and costs for patients with nonmetastatic HSPC (nmHSPC) and metastatic HSPC (mHSPC) and their payers. METHODS: We conducted a retrospective cohort analysis using claims data from the IBM MarketScan databases from January 2016 to December 2019. HSPC was defined as having at least 1 inpatient services or 2 outpatient services claims with a prostate cancer diagnosis and a claim for androgen deprivation therapy use within 6 months of the initial diagnostic claim. Metastatic patients had a secondary diagnosis code of metastasis with their initial diagnostic claim. We compared mean 12-month HCRU, patient out-of-pocket (OOP), and payer costs between patients with nmHSPC and mHSPC using multivariable linear regression. RESULTS: 4,329 patients met the study inclusion criteria, 600 of which had mHSPC. Patients with mHSPC had more outpatient prescription fills (10.91 additional fills; 95% CI = 8.09-13.99) and outpatient services visits (10.61 additional visits; 95% CI = 8.38-13.04) but similar other HCRU. The overall 12-month costs of patients with mHSPC were significantly greater than patients with nmHSPC for patient OOP ($1,244; 95% CI = $1,004-$1,513) and payers ($113,725; 95% CI = $91,494-$141,127). CONCLUSIONS: Compared with patients with nmHSPC, individuals with mHSPC incur greater HCRU and significant personal and overall financial burden.
PTPN2 elicits cell autonomous and non–cell autonomous effects on antitumor immunity in triple-negative breast cancer

The tumor-suppressor PTPN2 is diminished in a subset of triple-negative breast cancers (TNBCs). Paradoxically, PTPN2-deficiency in tumors or T cells in mice can facilitate T cell recruitment and/or activation to promote antitumor immunity. Here, we explored the therapeutic potential of targeting PTPN2 in tumor cells and T cells. PTPN2-deficiency in TNBC associated with T cell infiltrates and PD-L1 expression, whereas low PTPN2 associated with improved survival. PTPN2 deletion in murine mammary epithelial cells TNBC models, did not promote tumorigenicity but increased STAT-1–dependent T cell recruitment and PD-L1 expression to repress tumor growth and enhance the efficacy of anti-PD-1. Furthermore, the combined deletion of PTPN2 in tumors and T cells facilitated T cell recruitment and activation and further repressed tumor growth or ablated tumors already predominated by exhausted T cells. Thus, PTPN2-targeting in tumors and/or T cells facilitates T cell recruitment and/or alleviates inhibitory constraints on T cells to combat TNBC.
Effects of triton X-100 pretreatment of lyophilized and frozen-thawed ram sperm on preimplantation embryo developmental competence

Abstract In this study, it was aimed to determine the effect of destruction of lyophilized and frozen-thawed ram sperm plasma and acrosomal membrane on development of embryos produced by intracytoplasmic sperm injection (ICSI). Semen samples were divided into two groups for lyophilization (L) and freezing (F). For the removal of the plasma membrane, L and F groups were incubated with Triton X-100 (LTX-100 and FTX-100, respectively). Integrities of the plasma membrane, acrosome and chromatin structure were evaluated. Oocytes were injected with these sperm groups. Although no plasma membrane and acrosome integrities of the L (0.0%) group were detected, the plasma membrane integrity of the F group (69.4%) was significantly higher than the FTX-100 group (23.6%) (p < 0.05). The acrosome integrity of the FTX-100 group (3.80%) was significantly lower than the F group (55.6%) (p < 0.05). The chromatin integrities of L and F groups were higher than the Triton X-100 treated groups (p < 0.05). ICSIs with L, LTX-100, F and FTX-100 sperm were produced similar cleavage and blastocyst rates. In conclusion, data presented here confirm that ram spermatozoa can effectively be lyophilized and injected into oocytes for initiation of embryonic development and Triton X-100 pretreatment is not necessary while using lyophilized and frozen semen.
Equivalent Operative Outcomes for Emergency Colon Cancer Resections Among Acute Care Surgeons and Specialists in Colorectal Surgery

Objectives Improved screening has decreased but not eliminated the need for emergent surgery for colon cancer (CC), many of which are performed by acute care surgery (ACS) surgeons. This retrospective review compares outcomes for CC resections on the ACS service to the surgical oncology and colorectal services (SO/CRS). Methods Retrospective review was performed for CC operations between 2014 and 2019. Data for margin status, cancer stage, number of lymph nodes dissected, time to medical oncology follow-up, and time to initiation of chemotherapy were collected. Patients with curative resection, who chose comfort care, presented on alternative services or with non-CC indications as well as those were lost to follow-up were excluded. Results 36 ACS patients and 269 SO/CRS patients underwent CC resections. Most ACS patients presented emergently compared to the SO/CC group (83.3% vs 1%, P < .05) as well as with more advanced tumor stage. There were no statistically significant differences for presence of metastatic disease, number of lymph nodes obtained, or time to post-surgical care (in days) and chemotherapy initiation (in days). 3 (8%) EGS patients had positive margins compared to 6 (2%) CRS/SO patients due to the presence of perforated tumors in the ACS group (p < .05). There were no statistically significant differences in 30- day or 1-year mortality despite the emergent presentation of the ACS patients. Discussion These findings suggest that despite emergent presentation and advanced disease burden, ACS surgeons provide quality care to CC patients, both in the operating room and in coordination of care.
Association of primary and community care services with emergency visits and hospital admissions at the end of life in people with cancer: a retrospective cohort study

Objective To examine the association between primary and community care use and measures of acute hospital use in people with cancer at the end of life. Design Retrospective cohort study. Setting We used Discover, a linked administrative and clinical data set from general practices, community and hospital records in North West London (UK). Participants People registered in general practices, with a diagnosis of cancer who died between 2016 and 2019. Primary and secondary outcome measures ≥3 hospital admissions during the last 90 days, ≥1 admissions in the last 30 days and ≥1 emergency department (ED) visit in the last 2 weeks of life. Results Of 3581 people, 490 (13.7%) had ≥3 admissions in last 90 days, 1640 (45.8%) had ≥1 admission in the last 30 days, 1042 (28.6%) had ≥1 ED visits in the last 2 weeks; 1069 (29.9%) had more than one of these indicators. Contacts with community nurses in the last 3 months (≥13 vs <4) were associated with fewer admissions in the last 30 days (risk ratio (RR) 0.88, 95% CI 0.90 to 0.98) and ED visits in the last 2 weeks of life (RR 0.79, 95% CI 0.68 to 0.92). Contacts with general practitioners in the last 3 months (≥11 vs <4) was associated with higher risk of ≥3 admissions in the last 90 days (RR 1.63, 95% CI 1.33 to 1.99) and ED visits in the last 2 weeks of life (RR 1.27, 95% CI 1.10 to 1.47). Conclusions Expanding community nursing could reduce acute hospital use at the end of life and improve quality of care.
Validation of MyDiagnostick tool to identify atrial fibrillation in a multi-ethnic Asian population

Introduction: MyDiagnostick is an atrial fibrillation (AF) screening tool that has been validated in the Caucasian population in the primary care setting. Methods: In our study, we compared MyDiagnostick with manual pulse check for AF screening in the community setting. Results: In our cohort of 671 candidates from a multi-ethnic Asian population, AF prevalence was found to be 1.78%. Of 12 candidates, 6 (50.0%) had a previous history of AF and another 6 (50.0%) were newly diagnosed with AF. Candidates found to have AF during the screening were older (72.0 ± 11.7 years vs. 56.0 ± 13.0 years, P < 0.0001) and had a higher CHADSVASC risk score (2.9 ± 1.5 vs. 1.5 ± 1.1, P = 0.0001). MyDiagnostick had a sensitivity of 100.0% and a specificity of 96.2%. In comparison, manual pulse check had a sensitivity of 83.3% and a specificity of 98.9%. Conclusion: MyDiagnostick is a simple AF screening device that can be reliably used by non-specialist professionals in the community setting. Its sensitivity and specificity are comparable and validated across various studies performed in different population cohorts.
Atmospheric particulate matter aggravates CNS demyelination through involvement of TLR-4/NF-kB signaling and microglial activation

Atmospheric Particulate Matter (PM) is one of the leading environmental risk factors for the global burden of disease. Increasing epidemiological studies demonstrated that PM plays a significant role in CNS demyelinating disorders; however, there is no direct testimony of this, and yet the molecular mechanism by which the occurrence remains unclear. Using multiple in vivo and in vitro strategies, in the present study we demonstrate that PM exposure aggravates neuroinflammation, myelin injury, and dysfunction of movement coordination ability via boosting microglial pro-inflammatory activities, in both the pathological demyelination and physiological myelinogenesis animal models. Indeed, pharmacological disturbance combined with RNA-seq and ChIP-seq suggests that TLR-4/NF-kB signaling mediated a core network of genes that control PM-triggered microglia pathogenicity. In summary, our study defines a novel atmospheric environmental mechanism that mediates PM-aggravated microglia pathogenic activities, and establishes a systematic approach for the investigation of the effects of environmental exposure in neurologic disorders.
Increase in SARS-CoV-2 RBD-Specific IgA and IgG Antibodies in Human Milk From Lactating Women Following the COVID-19 Booster Vaccination

Background: The United States Centers for Disease Control and Prevention recommended a third dose or booster of the Pfizer-BioNTech Comirnaty (BNT162b2) COVID-19 mRNA vaccine in September 2021 for high-risk individuals. Pregnant and high-risk lactating women were encouraged to receive the booster to obtain potential prolonged protection for themselves and their infants. Research Aim: To investigate the ability of the booster vaccine to increase IgA and IgG antibodies specific to the receptor-binding domain of the SARS-CoV-2 spike protein in human milk compared to levels pre-booster. Methods: This was a prospective one-group study with a pretest-posttest design. Six of 12 participants were recruited prospectively. Participants were instructed to collect ≥ 2 ounces of milk in the morning at 30 days and 1-day pre-booster, and 7, 14, 21, 30, 45, and 60 days post-booster. Levels of IgA and IgG antibodies specific to the receptor-binding domain of the SARS-CoV-2 spike protein were quantified in human milk via an ELISA assay. Results: We found a significant increase in anti-receptor-binding domain-specific IgA and IgG antibodies in human milk 1–2 weeks after the Pfizer-BioNTech booster and at the study endpoint (45- and 60-days post-booster) Conclusions: This suggests that the booster vaccination enhances SARS-CoV-2 specific immunity in human milk, which may be protective for infants.
Olfactory loss is an early and reliable marker for COVID-19

Detection of early and reliable symptoms is important in relation to limiting the spread of an infectious disease. For COVID-19, the most prevalent symptom is either losing or experiencing reduced olfactory functions. Anecdotal evidence suggests that olfactory dysfunction is also one of the earlier symptoms of COVID-19 but objective measures supporting this notion are currently missing. To determine whether olfactory dysfunction is an early sign of COVID-19, we assessed available longitudinal data from a web-based interface enabling individuals to test their sense of smell by rating the intensity of selected household odors. Individuals continuously used the interface to assess their olfactory functions and at each login, in addition to odor ratings, recorded their symptoms and result from potential COVID-19 test. A total of 205 COVID-19 positive individuals and 156 pseudo-randomly matched control individuals lacking positive test provided longitudinal data which enabled us to assess olfactory functions in relation to their test results date. We found that odor intensity ratings started to decline in the COVID-19 group as early as 6 days prior to test result date. Symptoms such as sore throat, aches, and runny nose appear around the same point in time; however, with a lower predictability of a COVID-19 diagnose. Our results suggest that olfactory dysfunction is an early symptom but does not appear before other related COVID-19 symptoms. Olfactory dysfunction is, however, more predictive of an COVID-19 diagnose than other early symptoms.
Using natural language prompts for machine translation

We explore the use of natural language prompts for controlling various aspects of the outputs generated by machine translation models. We demonstrate that natural language prompts allow us to influence properties like formality or specific dialect of the output. We show that using language names to control the output language of multilingual translation models enables positive transfer for unseen language pairs. This unlocks the ability to translate into languages not seen during fine-tuning by using their English names. We investigate how scale, number of pre-training steps, number of languages in fine-tuning, and language similarity affect this phenomenon.
Systematic Prevention of On-Core Timing Channels by Full Temporal Partitioning

Microarchitectural timing channels enable unwanted information flow across security boundaries, violating fundamental security assumptions. They leverage timing variations of several state-holding microarchitectural components and have been demonstrated across instruction set architectures and hardware implementations. Analogously to memory protection, (Ge et al. 2019) have proposed time protection for preventing information leakage via timing channels. They also showed that time protection calls for hardware support. This work leverages the open and extensible RISC-V instruction set architecture (ISA) to introduce the temporal fence instruction fence.t, which provides the required mechanisms by clearing vulnerable microarchitectural state and guaranteeing a history-independent context-switch latency. We propose and discuss three different implementations of fence.t and implement them on an experimental version of the seL4 microkernel (Klein et al. 2014) and CVA6, an open-source, in-order, application class, 64-bit RISC-V core (Zaruba and Benini 2019). We find that a complete, systematic, ISA-supported erasure of all non-architectural core components is the most effective implementation while featuring a low implementation effort, a minimal performance overhead of less than 1%, and negligible hardware costs.
Advanced Situational Graphs for Robot Navigation in Structured Indoor Environments

Mobile robots extract information from its environment to understand their current situation to enable intelligent decision making and autonomous task execution. In our previous work, we introduced the concept of Situation Graphs (S-Graphs) which combines in a single optimizable graph, the robot keyframes and the representation of the environment with geometric, semantic and topological abstractions. Although S-Graphs were built and optimized in real-time and demonstrated state-of-the-art results, they are limited to specific structured environments with specific hand-tuned dimensions of rooms and corridors. In this work, we present an advanced version of the Situational Graphs (S-Graphs+), consisting of the five layered optimizable graph that includes (1) metric layer along with the graph of free-space clusters (2) keyframe layer where the robot poses are registered (3) metric-semantic layer consisting of the extracted planar walls (4) novel rooms layer constraining the extracted planar walls (5) novel floors layer encompassing the rooms within a given floor level. S-Graphs+ demonstrates improved performance over S-Graphs efficiently extracting the room information while simultaneously improving the pose estimate of the robot, thus extending the robots situational awareness in the form of a five layered environmental model.
Polynomial effective equidistribution

We prove effective equidistribution theorems, with polynomial error rate, for orbits of the unipotent subgroups of $\operatorname{SL}_2(\mathbb R)$ in arithmetic quotients of $\operatorname{SL}_2(\mathbb C)$ and $\operatorname{SL}_2(\mathbb R)\times\operatorname{SL}_2(\mathbb R)$. The proof is based on the use of a Margulis function, tools from incidence geometry, and the spectral gap of the ambient space.
On Learning Mixture Models with Sparse Parameters

Mixture models are widely used to ﬁt complex and multimodal datasets. In this paper we study mixtures with high dimensional sparse latent parameter vectors and consider the problem of support recovery of those vectors. While parameter learning in mixture models is well-studied, the sparsity constraint remains relatively unexplored. Sparsity of parameter vectors is a natural constraint in variety of settings, and support recovery is a major step towards parameter estimation. We provide eﬃcient algorithms for support recovery that have a logarithmic sample complexity dependence on the dimensionality of the latent space. Our algorithms are quite general, namely they are applicable to 1) mixtures of many diﬀerent canonical distributions including Uniform, Poisson, Laplace, Gaus-sians, etc. 2) Mixtures of linear regressions and linear classiﬁers with Gaussian covariates under diﬀerent assumptions on the unknown parameters. In most of these settings, our results are the ﬁrst guarantees on this problem while in the rest, we provide signiﬁcant improvements on existing results in certain regimes.
Robust Federated Learning with Connectivity Failures: A Semi-Decentralized Framework with Collaborative Relaying

Intermittent connectivity of clients to the parameter server (PS) is a major bottleneck in federated edge learning frameworks. The lack of constant connectivity induces a large generalization gap, especially when the local data distribution amongst clients exhibits heterogeneity. To overcome intermittent communication outages between clients and the central PS, we introduce the concept of collaborative relaying wherein the participating clients relay their neighbors' local updates to the PS in order to boost the participation of clients with poor connectivity to the PS. We propose a semi-decentralized federated learning framework in which at every communication round, each client initially computes a local consensus of a subset of its neighboring clients' updates, and eventually transmits to the PS a weighted average of its own update and those of its neighbors'. We appropriately optimize these local consensus weights to ensure that the global update at the PS is unbiased with minimal variance - consequently improving the convergence rate. Numerical evaluations on the CIFAR-10 dataset demonstrate that our collaborative relaying approach outperforms federated averaging-based benchmarks for learning over intermittently-connected networks such as when the clients communicate over millimeter wave channels with intermittent blockages.
High-mobility two-dimensional electron gas in 
<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>γ</mml:mi><mml:mtext>−</mml:mtext><mml:msub><mml:mi>Al</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn>3</mml:mn></mml:msub><mml:mo>

The origin of the two-dimensional electron gas (2DEG) in the interface between $\gamma$-Al$_2$O$_3$ (GAO) and SrTiO$_3$ (STO) (GAO/STO) as well as the reason for the high mobility of the 2DEG is still in debate. In this paper, the electronic structures of [001]-oriented GAO/STO heterostructures with and without oxygen vacancies are investigated by first-principle calculations based on the density functional theory. The calculation results show that the necessary condition for the formation of 2DEG is that the GAO/STO heterostructure has the interface composed of Al and TiO$_2$ layers. For the heterostructure without oxygen vacancy on the GAO side, the 2DEG originates from the polar discontinuity near the interface, and there is a critical thickness for the GAO film, below which the 2DEG would not present and the heterostructure exhibits insulator characteristics. For the case that only the GAO film contains oxygen vacancies, the polar discontinuity near the interface disappears, but the 2DEG still exists. In this situation, the critical thickness of the GAO film for 2DEG formation does not exist either. When the GAO film and STO substrate both contain oxygen vacancies, it is found that the 2DEG retains as long as the oxygen vacancies on the STO side are not very close to the interface. The low-temperature mobilities of the 2DEGs in these GAO/STO heterostructures are considered to be governed by the ionized impurity scattering, and $\sim$3 to $\sim$11 times as large as that in LaAlO$_3$/SrTiO$_3$ heterojunction. The high mobility of the 2DEG is mainly due to the small electron effective mass in GAO/STO heterostructure.