When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction

Machine learning models are often personalized with categorical attributes that are protected, sensitive, self-reported, or costly to acquire. In this work, we show models that are personalized with group attributes can reduce performance at a group level. We propose formal conditions to ensure the "fair use" of group attributes in prediction tasks by training one additional model -- i.e., collective preference guarantees to ensure that each group who provides personal data will receive a tailored gain in performance in return. We present sufficient conditions to ensure fair use in empirical risk minimization and characterize failure modes that lead to fair use violations due to standard practices in model development and deployment. We present a comprehensive empirical study of fair use in clinical prediction tasks. Our results demonstrate the prevalence of fair use violations in practice and illustrate simple interventions to mitigate their harm.Comment: ICML 2023 Ora

Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals

Heart failure is a debilitating condition that affects millions of people worldwide and has a significant impact on their quality of life and mortality rates. An objective assessment of cardiac pressures remains an important method for the diagnosis and treatment prognostication for patients with heart failure. Although cardiac catheterization is the gold standard for estimating central hemodynamic pressures, it is an invasive procedure that carries inherent risks, making it a potentially dangerous procedure for some patients. Approaches that leverage non-invasive signals - such as electrocardiogram (ECG) - have the promise to make the routine estimation of cardiac pressures feasible in both inpatient and outpatient settings. Prior models trained to estimate intracardiac pressures (e.g., mean pulmonary capillary wedge pressure (mPCWP)) in a supervised fashion have shown good discriminatory ability but have been limited to the labeled dataset from the heart failure cohort. To address this issue and build a robust representation, we apply deep metric learning (DML) and propose a novel self-supervised DML with distance-based mining that improves the performance of a model with limited labels. We use a dataset that contains over 5.4 million ECGs without concomitant central pressure labels to pre-train a self-supervised DML model which showed improved classification of elevated mPCWP compared to self-supervised contrastive baselines. Additionally, the supervised DML model that uses ECGs with access to 8,172 mPCWP labels demonstrated significantly better performance on the mPCWP regression task compared to the supervised baseline. Moreover, our data suggest that DML yields models that are performant across patient subgroups, even when some patient subgroups are under-represented in the dataset. Our code is available at https://github.com/mandiehyewon/ssldm

Thick planar domain wall: its thin wall limit and dynamics

We consider a planar gravitating thick domain wall of the $\lambda \phi^4$ theory as a spacetime with finite thickness glued to two vacuum spacetimes on each side of it. Darmois junction conditions written on the boundaries of the thick wall with the embedding spacetimes reproduce the Israel junction condition across the wall in the limit of infinitesimal thickness. The thick planar domain wall located at a fixed position is then transformed to a new coordinate system in which its dynamics can be formulated. It is shown that the wall's core expands as if it were a thin wall. The thickness in the new coordinates is not constant anymore and its time dependence is given.Comment: 11 pages, to appear in IJMP

A Process Calculus for Dynamic Networks

In this paper we propose a process calculus framework for dynamic networks in which the network topology may change as computation proceeds. The proposed calculus allows one to abstract away from neighborhood-discovery computations and it contains features for broadcasting at multiple transmission ranges and for viewing networks at different levels of abstraction. We develop a theory of confluence for the calculus and we use the machinery developed towards the verification of a leader-election algorithm for mobile ad hoc networks

Scorpion envenomation in Bagh-E Malek, Iran –a 5 year study

Scorpionism is a major health problem in many tropical countries including Iran. The aim of this study was to describe the epidemiological and demographic information among whom stung by scorpions in Bagh-E Malek, Iran. In this retrospective cross-sectional study the information were gathered through evaluation of the records of stung patients referring to Shahid Tabatabai hospital of Bagh-E Malek April 2008 to April 2012. A total of 132 cases stung by scorpion were recorded including 3115 males (43%) and 4121 females (57%).Approximately 42.1 percent of the sting cases occurred in the summer followed by spring with 35.9% of stings. About 59.8% of stings happened in people by the age of 15-44 years old. Most of the stings happened in exposed extremities (78.5%) with most of it in upper limbs (41.8%). The scorpions’ species were unknown but 60.4% of them were yellow, 34.0% black and 5.6% were “other colors”. Since the highest rate of scorpionism cases were reported in rural areas (74.2%), it is suggested that the main focus should be considered for education of rural people, especially women who play a major role in the family. Additionally, evaluation of residential houses and surrounding environment and giving information on method of cleaning up the environment from the equipment and the factors from which scorpion may use as shelter, can also be effective in reducing the incidence of Scorpionism.Keywords: Scorpion sting; Epidemiology; Bagh-E Malek; Ira

Petrology, geochemistry and tectonomagmatic evolution of Hezar Igneous Complex (Rayen - south of Kerman - Iran): the first description of an arc remnant of the Neotethyan subduction zone

The Hezar Igneous Complex (HIC) in the south-eastern part of Urumieh-Dokhtar magmatic arc, is the most prominent magmatic feature in the Kerman Porphyry Copper Belt, that understanding magmatic evolution of which may shed light on the tectonomagmatic development of this less-studied part of an important magmatic arc in the Neotethys realm. The HIC has been developed in the the intersection of the N-S striking Sabzevaran fault and the NW-SE striking Rafsanjan-Rayen fault. It is indicated that the possible place of the conduit and vent is in Jalas Mountain which has been splitted later by the Sabzevaran fault into Minor and Major Jalas. The current summit had been constructed by ascending magma chamber under the HIC that constitutes the Kamali Mountain at the south of the summit. Some plutonic rocks of the HIC are exposed at Kamali Mountain. The subalkaline rocks of this complex mainly are composed of different pyroclastic and lava flow rocks, acidic to basic in composition, showing the evidences of fractional crystallization and mineral segregation. Sequential explosive and effusive eruptions with Strombolian to Vulcanian types are evident in the successive volcanic layers. The compositional trend shows the melting of spinel lherzolite, not garnet lherzolite. The subduction-related mechanism of the magma genesis has been indicated by IAB nature of the magma formation in geochemical diagrams.publishe

Quantum phase transitions in the Kondo-necklace model: Perturbative continuous unitary transformation approach

The Kondo-necklace model can describe magnetic low-energy limit of strongly correlated heavy fermion materials. There exist multiple energy scales in this model corresponding to each phase of the system. Here, we study quantum phase transition between the Kondo-singlet phase and the antiferromagnetic long-range ordered phase, and show the effect of anisotropies in terms of quantum information properties and vanishing energy gap. We employ the "perturbative continuous unitary transformations" approach to calculate the energy gap and spin-spin correlations for the model in the thermodynamic limit of one, two, and three spatial dimensions as well as for spin ladders. In particular, we show that the method, although being perturbative, can predict the expected quantum critical point, where the gap of low-energy spectrum vanishes, which is in good agreement with results of other numerical and Green's function analyses. In addition, we employ concurrence, a bipartite entanglement measure, to study the criticality of the model. Absence of singularities in the derivative of concurrence in two and three dimensions in the Kondo-necklace model shows that this model features multipartite entanglement. We also discuss crossover from the one-dimensional to the two-dimensional model via the ladder structure.Comment: 12 pages, 6 figure

Determining a piston's top dead center (TDC) in an automobile using installed piezoelectric on a vibrating beam

Smart structures and MEMS are considered important field recently, due to the importance and high capabilities in measurement and the power of reaction and response to changes of the surroundings. This research concerns two fields of practical vision in the automotive industry and discuss the energy recycled industrial vibrations. The goal is to use the PVDF piezoelectric elements in car flywheel for energy harvesting, and compare and replace it with the revolution sensor. This research is totally based on empirical tests data and the result that the use of piezoelectric polymer sensors can harvest energy, was find performing far better than inductive sensors.Keywords: Piezoelectric element; Vibration energy harvesting; smart structures; Revolution sensor; Flywhee

Pegylation of Nanoliposomal Paclitaxel Enhances its Efficacy in Breast Cancer

Purpose: To encapsulate paclitaxel into nanoliposomes, followed by  pegylatation, in order to improve its therapeutic index and reduce side effects in breast cancer.Methods: In order to prepare nanoliposomal paclitaxel, varying ratios of phosphatidylcholine, cholesterol and paclitaxel were mixed and the formulations pegylated with poly-ethylene glycol 2000 (PEG 2000) to  enhance stability, efficiency, as well as solubility. The mean diameter of nanoliposomal paclitaxel and pegylated nanoliposomal paclitaxel were measured by Zeta sizer device and release of paclitaxel from both  formulations was determined within 28 h by dialysis method. The  cytotoxicity of nanoliposomal and pegylated nanoliposomal paclitaxel was evaluated using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay.Results: The mean diameter of nanoliposomal paclitaxel and pegylated nanoliposomal paclitaxel was 421.4 and 369.1 nm, respectively, while encapsulation efficiency was 91.3 ± 5.7 and 95.2 ± 6.3 %, respectively. Paclitaxel released from both formulations in 28 h was 5.53 and 5.02 %, respectively. The cytotoxicity of pegylated nanoliposomal paclitaxel was significantly (p . 0.05) greater than that of nanoliposomal paclitaxel (their IC50 = 79.8±2.9 and 86.25±3.4 µg/ml, respectively).Conclusion: The release pattern and cytotoxicity of pegylated  nanoliposomal paclitaxel show that the formulation is superior to  nanoliposomal paclitaxel. Furthermore, the mean particle size of pegylatednanoliposome is smaller than that of the non-pegylated preparation.Keywords: Paclitaxel, Nanoliposome, Breast cancer, Pegylation, Drug delivery, Cytotoxicit