A modification term for Black-Scholes model based on discrepancy calibrated with real market data. Data science in finance and economics

The Black-Scholes option pricing model (B-S model) generally requires the assumption that the volatility of the underlying asset be a piecewise constant. However, empirical analysis shows that there are discrepancies between the option prices obtained from the B-S model and the market prices. Most current modifications to the B-S model rely on modelling the implied volatility or interest rate. In contrast to the existing modifications to the Black-Scholes model, this paper proposes the concept of including a modification term to the B-S model itself. Using the actual discrepancies of the results of the Black-Scholes model and the market prices, the modification term related to the implied volatility is derived. Experimental results show that the modified model produces a better option pricing results when compare to market data

bpftime: userspace eBPF Runtime for Uprobe, Syscall and Kernel-User Interactions

In kernel-centric operations, the uprobe component of eBPF frequently encounters performance bottlenecks, largely attributed to the overheads borne by context switches. Transitioning eBPF operations to user space bypasses these hindrances, thereby optimizing performance. This also enhances configurability and obviates the necessity for root access or privileges for kernel eBPF, subsequently minimizing the kernel attack surface. This paper introduces bpftime, a novel user-space eBPF runtime, which leverages binary rewriting to implement uprobe and syscall hook capabilities. Through bpftime, userspace uprobes achieve a 10x speed enhancement compared to their kernel counterparts without requiring dual context switches. Additionally, this runtime facilitates the programmatic hooking of syscalls within a process, both safely and efficiently. Bpftime can be seamlessly attached to any running process, limiting the need for either a restart or manual recompilation. Our implementation also extends to interprocess eBPF Maps within shared memory, catering to summary aggregation or control plane communication requirements. Compatibility with existing eBPF toolchains such as clang and libbpf is maintained, not only simplifying the development of user-space eBPF without necessitating any modifications but also supporting CO-RE through BTF. Through bpftime, we not only enhance uprobe performance but also extend the versatility and user-friendliness of eBPF runtime in user space, paving the way for more efficient and secure kernel operations

SATB2 shows different profiles between appendiceal adenocarcinomas ex goblet cell carcinoids and appendiceal/colorectal conventional adenocarcinomas: An immunohistochemical study with comparison to CDX2

Background: Special AT-rich sequence-binding protein 2 (SATB2) is a novel marker for colorectal adenocarcinomas but little is known about its expression in appendiceal adenocarcinomas. We aim to investigate SATB2 in these tumors and colorectal adenocarcinomas with comparison to CDX2. Methods: Immunohistochemical stains for SATB2 and CDX2 were performed in 49 appendiceal adenocarcinomas (23 conventional, 26 adenocarcinoma ex goblet cell carcinoids (AdexGCCs)) and 57 colorectal adenocarcinomas. Their expression was correlated with tumor differentiation and growth patterns. Results: SATB2 staining was positive in 26/26 (100%) appendiceal AdexGCCs and 15/23 (65%) appendiceal conventional adenocarcinomas (P = 0.001). Their mean percentage of SATB2-positive cells was 93% and 34%, respectively (P \u3c 0.0001). CDX2 staining was seen in 26/26 (100%) AdexGCCs and 22/23 (96%) appendiceal conventional adenocarcinomas (P = 0.4694). SATB2 and CDX2 showed similar staining in AdexGCCs but CDX2 labeled more tumor cells than SATB2 in conventional adenocarcinomas (mean 84% vs. 34%, P \u3c 0.0001). SATB2 and CDX2 staining was seen in 82% (47/57) and 96% (55/57) colorectal adenocarcinomas, respectively (P = 0.01). The mean percentage of cells positive for SATB2 and CDX2 was 48% and 91%, respectively (P \u3c 0.00001). Decreased SATB2 immunoreactivity was associated with non-glandular differentiation particularly signet ring cells in colorectal (P = 0.001) and appendiceal conventional adenocarcinomas (P = 0.04) but not in appendiceal AdexGCCs. Conclusions: SATB2 is a highly sensitive marker for appendiceal AdexGCCs with similar sensitivity as CDX2. In colorectal and appendiceal conventional adenocarcinomas, SATB2 is not as sensitive as CDX2 and its immunoreactivity is dependent on tumor differentiation

IoT Implementation of Kalman Filter to Improve Accuracy of Air Quality Monitoring and Prediction

In order to obtain high-accuracy measurements, traditional air quality monitoring and prediction systems adopt high-accuracy sensors. However, high-accuracy sensors are accompanied with high cost, which cannot be widely promoted in Internet of Things (IoT) with many sensor nodes. In this paper, we propose a low-cost air quality monitoring and real-time prediction system based on IoT and edge computing, which reduces IoT applications dependence on cloud computing. Raspberry Pi with computing power, as an edge device, runs the Kalman Filter (KF) algorithm, which improves the accuracy of low-cost sensors by 27% on the edge side. Based on the KF algorithm, our proposed system achieves the immediate prediction of the concentration of six air pollutants such as SO2, NO2 and PM2.5 by combining the observations with errors. In the comparison experiments with three common predicted algorithms including Simple Moving Average, Exponentially Weighted Moving Average and Autoregressive Integrated Moving Average, the KF algorithm can obtain the optimal prediction results, and root-mean-square error decreases by 68.3% on average. Taken together, the results of the study indicate that our proposed system, combining edge computing and IoT, can be promoted in smart agriculture

A Novel Displacement and Tilt Detection Method Using Passive UHF RFID Technology

The displacement and tilt angle of an object are useful information for wireless monitoring applications. In this paper, a low-cost detection method based on passive radio frequency identification (RFID) technology is proposed. This method uses a standard ultrahigh-frequency (UHF) RFID reader to measure the phase variation of the tag response and detect the displacement and tilt angle of RFID tags attached to the targeted object. An accurate displacement result can be detected by the RFID system with a linearly polarized (LP) reader antenna. Based on the displacement results, an accurate tilt angle can also be detected by the RFID system with a circularly polarized (CP) reader antenna, which has been proved to have a linear relationship with the phase parameter of the tag’s backscattered wave. As far as accuracy is concerned, the mean absolute error (MAE) of displacement is less than 2 mm and the MAE of the tilt angle is less than 2.5° for an RFID system with 500 mm working range

A multiple modulation synthesis method with high spatial resolution for noninvasive neurostimulation.

Noninvasive neurostimulation plays a pivotal role in the direct control of neural circuits and the modulation of neuronal function. However, it is difficult to balance both spatial resolution and penetration depth when stimulating deep neurons. Here, we designed a multiple (time-division, frequency and polarity) modulation synthesis (MMS) method for noninvasively stimulating deep neurons with low-frequency envelopes. Compared to conventional transcranial electrical stimulation, we demonstrated that it can stimulate deep neurons at the desired firing rate (beat frequency) with higher spatial resolution via a computational model combining finite element analysis and Hodgkin-Huxley action potential model. Additionally, we measured the distribution of stimulus waveforms in saline solution to validate its effect. Taken together, the results of this study indicate that MMS stimulation with higher spatial resolution is steerable and might be a potential alternative to traditional implanted electrodes

IoT Implementation of Kalman Filter to Improve Accuracy of Air Quality Monitoring and Prediction

In order to obtain high-accuracy measurements, traditional air quality monitoring and prediction systems adopt high-accuracy sensors. However, high-accuracy sensors are accompanied with high cost, which cannot be widely promoted in Internet of Things (IoT) with many sensor nodes. In this paper, we propose a low-cost air quality monitoring and real-time prediction system based on IoT and edge computing, which reduces IoT applications dependence on cloud computing. Raspberry Pi with computing power, as an edge device, runs the Kalman Filter (KF) algorithm, which improves the accuracy of low-cost sensors by 27% on the edge side. Based on the KF algorithm, our proposed system achieves the immediate prediction of the concentration of six air pollutants such as SO2, NO2 and PM2.5 by combining the observations with errors. In the comparison experiments with three common predicted algorithms including Simple Moving Average, Exponentially Weighted Moving Average and Autoregressive Integrated Moving Average, the KF algorithm can obtain the optimal prediction results, and root-mean-square error decreases by 68.3% on average. Taken together, the results of the study indicate that our proposed system, combining edge computing and IoT, can be promoted in smart agriculture

GATA3 is a sensitive marker for primary genital extramammary paget disease: an immunohistochemical study of 72 cases with comparison to gross cystic disease fluid protein 15

Abstract Background GATA-binding protein 3 (GATA3) has been identified as a sensitive marker for breast carcinoma but its sensitivity in primary genital extramammary Paget diseases (EMPDs) has not been well studied. Methods Here we investigated immunohistochemical expression of GATA3 in 72 primary genital EMPDs (35 from female, 37 from male; 45 with intraepithelial disease only, 26 with both intraepithelial disease and invasive adenocarcinoma including 14 also metastasis, 1 with metastatic adenocarcinoma only for study). We also compared GATA3 to gross cystic disease fluid protein 15 (GCDFP15) for their sensitivity. Results Positive GATA3 staining was seen in all 71 (100%) intraepithelial diseases, 25/26 (96%; female 10/10, male 15/16) invasive adenocarcinomas and 14/15 (93%; female 3/3, male 11/12) metastatic adenocarcinomas, respectively. Positive GCDFP15 staining was seen in 46/71 (65%; female 28/34 or 82%, male 18/37 or 49%) intraepithelial diseases, 20/26 (77%; female 9/10, male 11/16) invasive adenocarcinomas, and 12/15 (80%; female 2/3, male 10/12) metastatic adenocarcinomas, respectively (GATA3 versus GCDFP15: p < 0.01 for both intraepithelial disease and invasive adenocarcinoma, p = 0.28 for metastatic adenocarcinoma). In positive-stained cases, GATA3 stained more tumor cells than GCDFP15 (79% versus 25% for intraepithelial disease, 71% vs 34% for invasive adenocarcinoma, 73% vs 50% for metastatic adenocarcinoma, p < 0.01 for all 3 components). Conclusions Our findings indicate that GATA3 is a very sensitive marker for primary genital EMPDs and is more sensitive than GCDFP15

Nanoparticle-mediated local depletion of tumour-associated platelets disrupts vascular barriers and augments drug accumulation in tumours

Limited intratumoural perfusion and nanoparticle retention remain major bottlenecks for the delivery of nanoparticle therapeutics into tumours. Here, we show that polymer-lipid-peptide nanoparticles delivering the antiplatelet antibody R300 and the chemotherapeutic agent doxorubicin can locally deplete tumour-associated platelets, thereby enhancing vascular permeability and augmenting the accumulation of the nanoparticles in tumours. R300 is specifically released in the tumour on cleavage of the lipid-peptide shell of the nanoparticles by matrix metalloprotease 2, which is commonly overexpressed in tumour vascular endothelia and stroma, thus facilitating vascular breaches that enhance tumour permeability. We also show that this strategy leads to substantial tumour regression and metastasis inhibition in mice