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Introduction Addition of ovarian function suppression to conventional endocrine therapy alone in premenopausal women provides a survival benefit with moderate to high risk hormone-receptor positive breast cancer, especially who received chemotherapy Prediction of menstruation recovery after chemotherapy is important for deciding subsequent endocrine treatment and addressing fertility issues. Methods In the adding OFS after chemotherapy trial (ASTRRA), patients who resumed ovarian function up to 2 years after chemotherapy were randomized to receive either 5 years of tamoxifen or adding 2 years of OFS with tamoxifen. With these 1383 patients, we developed a model that predicts when patients recover menstruation within 3 years after chemotherapy using several variables including age, BMI, chemotherapy regimen and duration, serum E2 and FSH level. Results A total of 1017 patients data were used to develop prediction model and 366 patients data were used for external validation. In development group, 546 (53.6%) patients resumed menstruation during follow up period of 5 years. In multivariable analysis, younger age and AC based regimen without taxane were strong predictive factor for menstruation recovery. However predictive value of chemotherapy regimen was not constant over time. Therefore, we conducted another model with patients (n= 624) who did not recover menstruation within one year. In this patient group, predictive factors for menstruation recovery was age and serum E2 level at 6 months after chemotherapy. We also conducted a simplified scoring system to estimate change of recovery by using risk factors mentioned above. Conclusion Younger age is an important persisting factor predicting menstrual recovery after chemotherapy. Although chemotherapy regimen predicts shor-term menstrual recovery, over time, patient factors have more predictive influence on recovery. Recovery of serum E2 level would be important to predict subsequent menstruation recovery. Citation Format: Young Joo Lee, Woo C Noh, Seok J Nam, Byeong-Woo Park, Eun S Lee, Seock A Im, Yong S Jung, Jung H Yoon, Sung S Kang, Kyong H Park, Soo-Jung Lee, Min H Lee, Joon Jeong, Sung Y Kim, Hyun-Ah Kim, Se-Hwan Han, Wonshik Han, Min H Hur, Seonok Kim, Sei-hyun Ahn, Hee J Kim. Prediction of menstruation recovery timing in premenopausal breast cancer patients taking tamoxifen after chemotherapy: An ASTRRA substudy [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-10-07.

Background: With recent technological advancement, new and improved endoscopic instruments and laser devices have catapulted flexible ureteroscopy (fURS) to the forefront, hence making retrograde i...

Discrete subaortic stenosis (DSS) is a pediatric condition in which a fibrotic membrane forms within the left ventricular outflow track. The fibrotic membrane is removed surgically; however, there is a high rate of reoccurrence which requires a second surgery. There are currently no tools available to predict the risk of reoccurrence in DSS patients, a limitation addressed by this study. In this study, we analyzed resected fibrotic membranes for DSS patients at the time of first surgery for non-recurrent and recurrent patients, and at the time of second surgery for recurrent patients. RNA-sequencing was conducted to obtain a global screen of changes in RNA expression while mass spectrometry was used to obtain a global screen of changes in protein expression. The results from the RNA-sequencing and mass spectrometry provide valuable insight into genes and the proteins that are differentially regulated in recurrent vs non-recurrent DSS patients.

Importance There is great concern about the impact of COVID-19 in pregnancy due to the high morbidity and mortality associated with prior coronavirus infections. Objective The objective of this review is to summarize the current literature on the impact of COVID-19 on pregnant women and their newborns. Evidence acquisition The search terms COVID-19 and pregnancy were used in Medline and Clinical Key databases. Only articles written in English with outcome data on both mothers and their newborns were incorporated. Results Pregnant women generally experience COVID-19 as a mild-moderate illness. However, approximately 5% become critically ill. Women with underlying comorbidities seem more likely to experience severe morbidity. Newborns also generally have a favorable course. Vertical transmission in the intrauterine period is possible but rare. Infection control measures need to be taken to prevent transmission during the peripartum period. There is a paucity of data on infections in the first and second trimesters, but research from those infected in the third trimester indicates a possible link with preterm birth. There is a significant percentage of asymptomatic cases. Racial disparities are also being noted with disproportionate numbers of racial/ethnic minorities being affected. Conclusions COVID-19 is generally experienced by pregnant women and their newborns as a mild to moderate illness, although a minority become critically ill and mortality does occur. This is more likely among those with underlying comorbidities, as in the general population. Asymptomatic cases heighten the need for increased testing and infection control measures. Racial disparities highlight underlying vulnerabilities and the need for increased research and policy changes.

Background Brain metastases frequently occur in patients with non‐small cell lung cancer (NSCLC) resulting in a poor prognosis. Here, we investigated the association between PD‐L1 expression and brain metastasis in patients with NSCLC and its clinical significance. Methods A total of 270 patients diagnosed with metastatic NSCLC who underwent PD‐L1 testing on their tumor tissue between January 2017 and March 2019 were retrospectively reviewed. The VENTANA PD‐L1 (SP263) assay was used, and positive PD‐L1 expression was defined as staining in ≥1% of tumor cells. Results Positive PD‐L1 expression was observed in 181 (67.0%) patients, and 74 (27.4%) patients had brain metastasis at diagnosis. Synchronous brain metastases were more frequently observed in PD‐L1‐positive compared with PD‐L1‐negative patients (31.5% vs. 19.1%, p = 0.045). Multiple logistic regression analysis identified positive PD‐L1 expression (odds ratio [OR]: 2.24, p = 0.012) as an independent factor associated with synchronous brain metastasis, along with the histological subtype of nonsquamous cell carcinoma (OR: 2.84, p = 0.003). However, the incidence of central nervous system (CNS) progression was not associated with PD‐L1 positivity, with a two‐year cumulative CNS progression rate of 26.3% and 28.4% in PD‐L1‐positive and PD‐L1‐negative patients, respectively (log rank p = 0.944). Furthermore, positive PD‐L1 expression did not affect CNS progression or overall survival in patients with synchronous brain metastasis (long rank p = 0.513 and 0.592, respectively). Conclusions Initial brain metastases are common in NSCLC patients with positive PD‐L1 expression. Further studies are necessary to understand the relationship between early brain metastasis and cancer immunity., We investigated the association between PD‐L1 expression and brain metastasis in patients with non‐small cell lung cancer (NSCLC) and its clinical significance. Patients with tumors exhibiting positive PD‐L1 expression (TPS ≥ 1%) were found to have a higher frequency and risk of synchronous brain metastasis when diagnosed with advanced NSCLC. No prognostic impact of PD‐L1 expression was observed on either CNS progression in the entire cohort of patients or OS in patients presenting with synchronous brain metastasis.

Traumatic brain injury (TBI) leads to lasting brain dysfunction with chronic neuroinflammation typified by nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome activation in microglia. This study probed whether a single intranasal (IN) administration of human mesenchymal stem cell-derived extracellular vesicles (hMSC-EVs) naturally enriched with activated microglia-modulating miRNAs can avert chronic adverse outcomes of TBI. Small RNA sequencing confirmed the enrichment of miRNAs capable of modulating activated microglia in hMSC-EV cargo. IN administration of hMSC-EVs into adult mice ninety minutes after the induction of a unilateral controlled cortical impact injury resulted in their incorporation into neurons and microglia in both injured and contralateral hemispheres. A single higher dose hMSC-EV treatment also inhibited NLRP3 inflammasome activation after TBI, evidenced by reduced NLRP3, apoptosis-associated speck-like protein containing a CARD, activated caspase-1, interleukin-1 beta, and IL-18 levels in the injured brain. Such inhibition in the acute phase of TBI endured in the chronic phase, which could also be gleaned from diminished NLRP3 inflammasome activation in microglia of TBI mice receiving hMSC-EVs. Proteomic analysis and validation revealed that higher dose hMSC-EV treatment thwarted the chronic activation of the p38 mitogen-activated protein kinase (MAPK) signaling pathway by IL-18, which decreased the release of proinflammatory cytokines. Inhibition of the chronic activation of NLRP3-p38/MAPK signaling after TBI also prevented long-term cognitive and mood impairments. Notably, the animals receiving higher doses of hMSC-EVs after TBI displayed better cognitive and mood function in all behavioral tests than animals receiving the vehicle after TBI. A lower dose of hMSC-EV treatment also partially improved cognitive and mood function. Thus, an optimal IN dose of hMSC-EVs naturally enriched with activated microglia-modulating miRNAs can inhibit the chronic activation of NLRP3-p38/MAPK signaling after TBI and prevent lasting brain dysfunction.

This study uses the Vietnam Access to Resources Household Survey (VARHS) data from 2008 to 2014 to analyse the relationship between socio-political capital and household income in rural Vietnam. We...

This study compares the performance of graph convolutional neural network (GCN) models with conventional natural language processing (NLP) models for classifying scientific literature related to radio frequency electromagnetic field (RF-EMF). Specifically, the study examines two GCN models: BertGCN and the citation-based GCN. The study concludes that the model achieves consistently good performance when the input text is long enough, based on the attention mechanism of BERT. When the input sequence is short, the composition parameterλ, which combines output values of the two subnetworks of BertGCN, plays a crucial role in achieving high classification accuracy. As the value ofλincreases, the classification accuracy also increases. The study also proposes and tests a simplified variant of BertGCN, revealing performance differences among the models under two different data conditions by the existence of keywords. This study has two main contributions: (1) the implementation and testing of a variant of BertGCN and citation-based GCN for document classification tasks related to radio frequency electromagnetic fields publications, and (2) the confirmation of the impact of model conditions, such as the existence of keywords and input sequence length, in the original BertGCN. Although this study focused on a specific domain, our approaches have broader implications that extend beyond scientific publications to general text classification.

A primary goal of acute stroke rehabilitation is to maximize functional recovery and help patients reintegrate safely in the home and community. However, not all patients have the same potential for recovery, making it difficult to set realistic therapy goals and to anticipate future needs for short- or long-term care. The objective of this study was to test the value of high-resolution data from wireless, wearable motion sensors to predict post-stroke ambulation function following inpatient stroke rehabilitation.Supervised machine learning algorithms were trained to classify patients as either household or community ambulators at discharge based on information collected upon admission to the inpatient facility (N=33-35). Inertial measurement unit (IMU) sensor data recorded from the ankles and the pelvis during a brief walking bout at admission (10 meters, or 60 seconds walking) improved the prediction of discharge ambulation ability over a traditional prediction model based on patient demographics, clinical information, and performance on standardized clinical assessments.Models incorporating IMU data were more sensitive to patients who changed ambulation category, improving the recall of community ambulators at discharge from 85% to 89-93%.This approach demonstrates significant potential for the early prediction of post-rehabilitation walking outcomes in patients with stroke using small amounts of data from three wearable motion sensors.Accurately predicting a patient's functional recovery early in the rehabilitation process would transform our ability to design personalized care strategies in the clinic and beyond. This work contributes to the development of low-cost, clinically-implementable prognostic tools for data-driven stroke treatment.

This study revisits the time-varying Okun’s law, using US data over the period 1948Q2–2015Q3. The estimated Okun’s coefficients are negative over most of the time horizon and the absolute values of the time-varying Okun’s coefficient is getting smaller. The short- and long-term fluctuations of the time-varying Okun’s law are reconstituted using the ensemble empirical mode decomposition (EEMD) method, and their determinants are analyzed. The empirical results show that the number of working hours and utilization are important factors affecting the long- and short-term fluctuations of the time-varying Okun’s coefficients. More specifically, the short-term fluctuations of the working hours and utilization have significant positive and negative effects, respectively, on the magnitude of short-term fluctuations of the time-varying Okun’s coefficients. It is also found that the long-term fluctuation of the estimated time-varying Okun’s coefficient has a very similar pattern to the detrended real GDP series. We also show the estimated regression estimates are very stable with respect to the considered EEMD method using a simple simulation.

Background and objectives Combined sequential treatments with multiple modalities such as lasers and soft-tissue fillers are commonly required for the treatment of atrophic acne scars. Recently, fractional treatment with picosecond-domain lasers has proven to be effective for skin rejuvenation and scar treatment. However, little is known about the effects of picosecond-domain fractional laser treatment over hyaluronic acid fillers (HAFs). We aimed to evaluate the in vivo tissue responses to 1064 nm picosecond-domain fractional neodymium:yttrium-aluminum-garnet (Nd:YAG) laser treatments using microlens array (MLA) applied over pre-injected HAF in rats. In addition, we evaluated the efficacy and safety of this combined same-day treatment for atrophic acne scars in patients. Study design/materials and methods Sprague-Dawley rats were subjected to 1064 nm picosecond-domain fractional Nd:YAG laser treatment immediately after HAF dermal injection. Skin specimens were histologically evaluated on days 0, 7, and 21. In a clinical study, 36 patients with acne scars were treated concurrently with 1064 nm MLA-type picosecond lasers and HAFs. The patients were scheduled to receive two consecutive treatments at 4-week intervals, with a follow-up visit at 12 weeks after the final treatment. Acne scar photographs were graded using the Goodman and Baron's qualitative and quantitative scales at baseline and 12 weeks post-procedure. Results Picosecond-domain fractional laser treatment immediately after the dermal injection of HAF into rats did not cause any histological changes in the filler or surrounding skin. In a clinical study, treated subjects (n = 36) achieved significant improvement in acne scars and patient satisfaction. No serious adverse events were observed. Conclusions Combined picosecond laser and HAF treatment were proven to be safe and effective based on in vivo and clinical study results. Facial rejuvenation and scar treatment using a picosecond-domain fractional laser may be performed immediately after HAF injection. Lasers Surg. Med. © 2020 Wiley Periodicals, Inc.

Poland's syndrome (PS; OMIM 173800) is a rare congenital syndrome which consists of absence or hypoplasia of the pectoralis muscle. Other features can be variably associated, including rib defects. On the affected side other features (such as of breast and nipple anomalies, lack of subcutaneous tissue and skin annexes, hand anomalies, visceral, and vertebral malformation) have been variably documented. To date, association of PS with central nervous system malformation has been rarely reported remaining poorly understood and characterized. We report a left-sided PS patient carrying a de novo 1.5 Mb Xp22.31 duplication diagnosed in addiction to strabismus, optic nerves and chiasm hypoplasia, corpus callosum abnormalities, ectopic neurohypophysis, pyelic ectasia, and neurodevelopmental delay. Since, to our knowledge, this features' association has not been previously reported, we argue that this case may contribute to further widening of the variability of PS phenotype.

Springs are efficient in storing and returning elastic potential energy but are unable to hold the energy they store in the absence of an external load. Lockable springs use clutches to hold elastic potential energy in the absence of an external load, but have not yet been widely adopted in applications, partly because clutches introduce design complexity, reduce energy efficiency, and typically do not afford high fidelity control over the energy stored by the spring. Here, we present the design of a novel lockable compression spring that uses a small capstan clutch to passively lock a mechanical spring. The capstan clutch can lock over 1000 N force at any arbitrary deflection, unlock the spring in less than 10 ms with a control force less than 1 % of the maximal spring force, and provide an 80 % energy storage and return efficiency (comparable to a highly efficient electric motor operated at constant nominal speed). By retaining the form factor of a regular spring while providing high-fidelity locking capability even under large spring forces, the proposed design could facilitate the development of energy-efficient spring-based actuators and robots., Comment: Accepted for presentation at the 2023 IEEE International Conference on Robotics and Automation

A graphene oxide (GO)-based cortisol biosensor was developed to accurately detect cortisol concentrations from sweat samples at point-of-care (POC) sites. A reference electrode, counter electrode, and working electrode make up the biosensor, and the working electrode was functionalized using multiple layers consisting of GO and antibodies, including Protein A, IgG, and anti-Cab. Sweat samples contact the anti-Cab antibodies to transport electrons to the electrode, resulting in an electrochemical current response. The sensor was tested at each additional functionalization layer and at cortisol concentrations between 0.1 and 150 ng/mL to determine how the current response differed. A potentiostat galvanostat device was used to measure and quantify the electrochemical response in the GO-based biosensor. In both tests, the electrochemical responses were reduced in magnitude with the addition of antibody layers and with increased cortisol concentrations. The proposed cortisol biosensor has increased accuracy with each additional functionalization layer, and the proposed device has the capability to accurately measure cortisol concentrations for diagnostic purposes.

This study aimed to determine how the muscle mass of the lower leg affects the preservation of the lower extremities in patients with diabetic foot ulcer. This study analyzed patients with diabetic foot ulcer between January 2014 and June 2018 with a follow-up of at least 2 years. Of these 181 patients whose ulcer is located distal to the metatarsophalangeal joint, which was categorized as grade ≤2 by the Wagner classification were classified into 4 grades: grade 0 (treated without amputation), grade 1 (amputation distal to the metatarsophalangeal joint), grade 2 (Ray, transmetatarsal, Lisfranc, and Chopart amputation), and grade 3 (Syme, below-knee, and above-knee amputation) according to the final amputation degree. The muscles of the lower leg were classified into 4 compartments: anterior, lateral, deep posterior, and superficial posterior. The cross-sectional area and attenuation to estimate the muscle volume and density were measured at the axial image of computed tomography (CT) angiography. No significant differences were observed in the sex ratio and mean age among the grades ( P = .966 and .962). The cross-sectional area of the anterior, lateral, and posterior compartments demonstrated no significant differences, but that of the superficial posterior compartment exhibited significant differences among the grades ( P

Background Hyperphosphorylation of the calcium release channel/ryanodine receptor type 2 (RyR2) at serine 2814 (S2814) is associated with multiple cardiac diseases including atrial fibrillation and heart failure. Despite recent advances, the molecular mechanisms driving pathological changes associated with RyR2 S2814 phosphorylation are still not well understood. Methods: Using affinity-purification coupled to mass spectrometry (AP-MS), we investigated the RyR2 interactome in ventricles from wild-type (WT) mice and two S2814 knock-in mutants: the unphosphorylated alanine mutant (S2814A) and hyperphosphorylated mimic aspartic acid mutant (S2814D). Western blots were used for validation. Results: In WT mouse ventricular lysates, we identified 22 proteins which were enriched with RyR2 pull-down relative to both IgG control and no antibody (beads-only) pull-downs. Parallel AP-MS using WT, S2814A, and S2814D mouse ventricles identified 72 proteins, with 20 being high confidence RyR2 interactors. Of these, 14 had an increase in their binding to RyR2 S2814A but a decrease in their binding to RyR2 S2814D. We independently validated three protein hits, Idh3b, Aifm1, and Cpt1b, as RyR2 interactors by western blots and showed that Aifm1 and Idh3b had significantly decreased binding to RyR2 S2814D compared to WT and S2814A, consistent with MS findings. Conclusion: By applying state-of-the-art proteomic approaches, we discovered a number of novel RyR2 interactors in the mouse heart. In addition, we found and defined specific alterations in the RyR2 interactome that were dependent on the phosphorylation status of RyR2 at S2814. These findings yield mechanistic insights into RyR2 regulation which may guide future drug designs.

SUMMARYDNA double strand break (DSB) repair by Homologous recombination (HR) is initiated by the end resection, a process during which 3’ ssDNA overhangs are generated by the nucleolytic degradation. The extent of DNA end resection determines the choice of the DSB repair pathway. The role of several proteins including nucleases for end resection has been studied in detail. However, it is still unclear how the initial, nicked DNA generated by MRE11-RAD50-NBS1 is recognized and how subsequent proteins including EXO1 are recruited to DSB sites to facilitate extensive end resection. We found that the MutSβ (MSH2-MSH3) mismatch repair (MMR) complex is recruited to DSB sites by recognizing the initial nicked DNA at DSB sites through the interaction with the chromatin remodeling protein SMARCAD1. MSH2-MSH3 at DSB sites helps to recruit EXO1 for long-range resection and enhances its enzymatic activity. MSH2-MSH3 furthermore inhibits the access of DNA polymerase θ (POLQ), which promotes polymerase theta-mediated end-joining (TMEJ) of DSB. Collectively, our data show a direct role for MSH2-MSH3 in the initial stages of DSB repair by promoting end resection and influencing DSB repair pathway by favoring HR over TMEJ. Our findings extend the importance of MMR in DSB repair beyond established role in rejecting the invasion of sequences not perfectly homologous to template DNA during late-stage HR.

A Wireless Sensor Network (WSN) is a wireless network that monitors physical environment conditions through resource-constrained sensor nodes and delivers data to a sink node through the network. One of the most important constraints on sensor nodes is their limited power source, which consists of small and irreplaceable batteries. Energy conservation is thus a dominant factor in WSN. Therefore, when designing a routing protocol for WSNs, it is necessary to consider the energy constraint of sensor nodes. In this paper, we consider the energy constraint of sensor nodes and propose an Energy Balancing Routing Protocol using reinforcement learning. The performance of the proposed protocol is compared to other existing energy-efficient routing protocols and the results show that the proposed protocol performs better with regards to energy saving and network lifetime.

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10−72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10−4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10−5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions. © Copyright.

Adding ovarian function suppression (OFS) after chemotherapy improves survival in young women with moderate- and high-risk breast cancer. Assessment of ovarian function restoration after chemotherapy becomes critical for subsequent endocrine treatment and addressing fertility issues.In the adding OFS after chemotherapy trial, patients who resumed ovarian function up to 2 years after chemotherapy were randomised to receive either 5 years of tamoxifen or adding 2 years of OFS with tamoxifen. Ovarian function was evaluated from enrolment to randomisation, and patients who did not randomise because of amenorrhoea for 2 years received tamoxifen and were followed up for 5 years. Prospectively collected consecutive hormone levels (proportion of patients with premenopausal follicle-stimulating hormone [FSH] levels 30 mIU/mL and oestradiol [E2] levels ≥40 pg/mL) and history of menstruation were available for 1067 patients with breast cancer.Over 5 years of tamoxifen treatment, 69% of patients resumed menstruation and 98% and 74% of patients satisfied predefined ovarian function restoration as per serum FSH and E2 levels, respectively. Menstruation was restored in 91% of patients younger than 35 years at baseline, but in only 33% of 45-year-old patients over 5 years. Among these patients, 41% experienced menstruation restoration within 2 years after chemotherapy and 28% slowly restored menstruation after 2-5 years. Younger age (35 years) at baseline, anthracycline without taxanes and ≤90 days of chemotherapy were predictors of menstruation restoration.During 5 years of tamoxifen treatment after chemotherapy, two-thirds of the patients experienced menstruation restoration, especially patients younger than 35 years. Young age, Adriamycin without taxanes and short duration of chemotherapy appeared to have a positive effect on ovarian reserves in the long term.ClinicalTrials.gov identifier: NCT00912548.

Since Markowitz [13] propose the mean-variance efficient portfolio selection method it has been one of the frequently used approach to the portfolio optimization problem. However, as we know, this approach has critical draw backs such as unstable assets weights and poor forecasting performance due to the estimation error. In this study, we propose an improved portfolio selection rules using various distortion functions. Our approach can make up for the pessimism of economic agents which is important for decision making. We illustrate the procedure by four well-known datasets. We also evaluate the performance of proposed and many other portfolio strategies to compare the in- and out-of-sample value at risk, conditional value at risk and Sharpe ratio. Empirical studies show that the proposed portfolio strategy outperforms many other strategies for most of evaluation measures.

Lysosomal enzymes are synthesized in the endoplasmic reticulum (ER) and transferred to the Golgi complex by interaction with the Batten disease protein CLN8 (ceroid lipofuscinosis, neuronal, 8). Here we investigated the relationship of this pathway with CLN6, an ER-associated protein of unknown function that is defective in a different Batten disease subtype. Experiments focused on protein interaction and trafficking identified CLN6 as an obligate component of a CLN6-CLN8 complex (herein referred to as EGRESS: ER-to-Golgi relaying of enzymes of the lysosomal system), which recruits lysosomal enzymes at the ER to promote their Golgi transfer. Mutagenesis experiments showed that the second luminal loop of CLN6 is required for the interaction of CLN6 with the enzymes but dispensable for interaction with CLN8. In vitro and in vivo studies showed that CLN6 deficiency results in inefficient ER export of lysosomal enzymes and diminished levels of the enzymes at the lysosome. Mice lacking both CLN6 and CLN8 did not display aggravated pathology compared with the single deficiencies, indicating that the EGRESS complex works as a functional unit. These results identify CLN6 and the EGRESS complex as key players in lysosome biogenesis and shed light on the molecular etiology of Batten disease caused by defects in CLN6.

Theory suggests an inverse relation between the stiffness and the energy storage capacity for linear helical springs: reducing the active length of the spring by 50% increases its stiffness by 100%, but reduces its energy storage capacity by 50%. State-of-the-art variable stiffness actuators used to drive robots are characterized by a similar inverse relation, implying reduced energy storage capacity for increased spring stiffness. This relation limits the potential of the variable stiffness actuation technology when it comes to human performance augmentation in natural tasks, e.g., jumping, weight-bearing and running, which may necessitate a spring exoskeleton with large stiffness range and high energy storage capacity. In this paper, we theoretically show that the trade-off between stiffness range and energy storage capacity is not fundamental; it is possible to develop variable stiffness springs with simultaneously increasing stiffness and energy storage capacity. Consistent with the theory, we experimentally show that a controllable volume air spring, has a direct relation between its stiffness range and energy storage capacity. The mathematical conditions presented in this paper may be used to develop actuators that could bypass the limited energy storage capacity of current variable stiffness spring technology.

License plate recognition is the most promising application in IoT camera. The existing recognition algorithm shows good performance when it is used in the constrained situation such as at the entrance to the parking lot. The number plate images taken from the cameras of the parking lot system have a constant size and brightness. The accuracy of the license plate recognition system installed at the entrance to the parking lot is more than 98%. However, the recognition accuracy of license plate number may drop by about 50% to 70% in video stream taken on roads, where the size and the brightness of number plate images in video stream are not constant. They are very different to each other due to the camera angle, the distance to the vehicles and the light. This situation makes some objects to be recognized as license plates compared to the constrained situation. A major cause of this low recognition accuracy is the inability to filter out noise like an outlier that has a similar pattern to license plates. More deeper and wider CNN technique can be useful to increase the accuracy in these situation. But, the IoT camera generally has a restricted resource and is unable to use too large deep CNN, which requires a lot of computation power and memory. This paper suppresses outliers, non-license plate objects and increases the recognition accuracy through time series analysis. We use the time series analysis as the statistical methods to solve this problem of the outlier occurrence. Experimental results show that the recognition accuracy in video stream taken on ordinary roads is 77% in the case of the absence of outlier filters, but 85% in the case of including the filters proposed in the paper.

This study investigates the time‐varying Okun's law for different age and gender cohorts in South Korea over the 1980–2014 period. We found that the absolute value of the estimated Okun coefficients for all age cohorts and both genders become larger in a recession than in an expansion. We also found that the youth cohort (15–24 years old) for both genders is more sensitive to a negative economic impact than are older cohorts. These differences imply that when policymakers try to find a way of reducing the unemployment rate, they should consider differences in behaviour among these groups. Furthermore, the policies should be combined with age‐specific policies.

This study examines the dynamic conditional correlations between the US and Korean financial markets and identifies the determinants of those correlations using the VAR-DCC-MGARCH model. We find that the Global Financial Crisis (GFC) affects both countries. Although the shocks to the Korean market before the GFC are not shared by the US market, those to the US market after the GFC are shared by the Korean market. We also examine the determinants of the dynamic conditional relations between the US and Korean markets using domestic macroeconomic variables and US/Korean financial variables. The results indicate that the US financial variables are more significant than domestic macroeconomic variables and that they have become increasingly important over time.

It is well known that many of the standard specification tests may not be robust when the alternative is misspecified. This study analyzes a robust specification test for generalized empirical likelihood (GEL) estimators in a weakly dependent time series setting. We show that the usual score test statistic asymptotically follows a non-central chi-square distribution under the local misspecification in the GEL framework. Thus, it spuriously rejects the null hypothesis too frequently. We propose a robust score specification test that asymptotically follows a central chi-square distribution under the local misspecification. A Monte Carlo simulation verifies the usefulness of the proposed tests.

The size distribution of income is the basis of income inequality measures which in turn are needed for evaluation of social welfare. Therefore, proper specification of the income density function is of special importance. In this paper, using information theoretic approach, first, we provide a maximum entropy (ME) characterization of some well-known income distributions. Then, we suggest a class of flexible parametric densities which satisfy certain economic constraints and stylized facts of personal income data such as the weak Pareto law and a decline of the income-share elasticities. Our empirical results using the U.S. family income data show that the ME principle provides economically meaningful and a very parsimonious and, at the same time, flexible specification of the income density function.

Machine-to-machine (M2M) communications and applications are expected to be a significant part of the Internet of Things (IoT). However, conventional network gateways reported in the literature are unable to provide sustainable solutions to the challenges posted by the massive amounts of M2M communications requests, especially in the context of the IoT for smart cities. In this paper, we present an admission control model for M2M communications. The model differentiates all M2M requests into delay-sensitive and delay-tolerant first, and then aggregates all delay-tolerant requests by routing them into one low-priority queue, aiming to reduce the number of requests from various devices to the access point in the IoT for smart cities. Also, an admission control algorithm is devised on the basis of this model to prevent access collision and to improve the quality of service. Performance evaluations by network calculus, numerical experiments, and simulations show that the proposed model is feasible and effective.

In the field of risk management, it is of great importance to obtain an efficient portfolio when market participants invest in a variety of assets. In this study, we propose a simple double-shrinkage portfolio selection rule to improve the out-of-sample performance of the portfolio. The double-shrinkage portfolio is obtained by a convex combination between highly structured covariance matrices and sample covariance matrix. Using various real datasets we show that the proposed portfolio strategy is found to be comparatively stable and yields higher values of Sharpe-ratio and lower values of conditional value at risk. Thus, the double-shrinkage selection rule improves the performances of the portfolios significantly.

This study uses a Granger non-causality test in quantiles to extend the investigation of the causality among cryptocurrencies. The empirical results reveal that (i) no quantile uncorrelated cryptocurrency is found by the Granger non-causality test in quantiles. (ii) Statistically strong bi-directional causal relationships exist only between Ripple and other cryptocurrencies over the quantile level [0.05, 0.95]. (iii) There are strong causal relationships between cryptocurrencies’ returns over high quantile levels, such as, [0.6, 0.8] and [0.8, 0.95]. (iv) The largest cryptocurrencies, that is, Bitcoin (BTC) and Ethereum (ETH), have stronger causality to smaller ones in high quantiles. The results of the non-causality test suggest a significant causal relationship in the tail quantile, which makes it hard for investors to hedge the risk in the cryptocurrency market.

This study investigates the effects of oil price volatility on stock markets. We consider the stock returns of ten major oil-importing countries: China, France, Germany, India, Italy, Japan, Korea, the Netherlands, Spain, and the U.S. from May 2001 to December 2019. To obtain a complete picture of the relationship between oil price volatility and stock returns, we apply both quantile regression and quantile-on-quantile regression approaches. Our empirical results indicate that oil price uncertainty has asymmetrical effects on stock returns; moreover, these asymmetric behaviors vary depending on not only the level of stock returns but also oil market conditions. The results show that increasing oil price volatility has a negative effect on stock returns when both oil price volatility and stock returns are low. However, when stock returns are high and oil price volatility is low, rising oil price volatility causes an increase in stock returns.

We develop several new time‐varying coefficient regression models to investigate herding behavior in Chinese stock markets. We find evidence that herding behavior occurs during turbulent periods rather than periods of relative tranquility, which does not appear when using a conventional fixed‐coefficient regression model. Moreover, the US return dispersion had a significant influence on Chinese stock markets before 2015 but not in 2015. Finally, the herding shows significant asymmetry.

Using the dynamic conditional correlation multivariate generalized autoregressive conditional heteroskedasticity (DCC-MGARCH) model, we empirically examine the dynamic relationship between stock market returns (KOSPI200 returns) and implied volatility (VKOSPI), as well as their statistical mechanics, in the Korean market, a representative and leading emerging market. We consider four macroeconomic variables (exchange rates, risk-free rates, term spreads, and credit spreads) as potential determinants of the dynamic conditional correlation between returns and volatility. Of these macroeconomic variables, the change in exchange rates has a significant impact on the dynamic correlation between KOSPI200 returns and the VKOSPI, especially during the recent financial crisis. We also find that the risk-free rate has a marginal effect on this dynamic conditional relationship.

Many empirical studies have investigated the existence of a causal relationship between a country's tourism growth and economic growth. However, the findings from these studies have been inconclusive. Some studies have found evidence of a unidirectional causal relationship, whereas others have found a bidirectional causal relationship. This inconsistency may be due to the usage of different frequencies of data or an incomplete description of the causal relationship. This study examines the causal relationship between economic growth and tourism growth in Korea using three types of Granger noncausality tests: the classical Granger noncausality test, a robust Granger noncausality test, and a Granger noncausality test in quantiles. Our empirical results provide evidence of what appears to be a bidirectional causal relationship between tourism growth and economic growth in overall quantile intervals. There is strong support that tourism growth leads to overall economic growth in Korea. However, in the reverse relationship, economic growth only has a significant effect on tourism at low quantile levels of tourism growth. These findings suggest that the causal relationship is heterogeneous and depends on different levels of tourism growth and economic growth.

This paper develops empirical tests for the purchasing power parity (PPP) hypothesis for China, Japan and South Korea by using the quantile unit root and quantile cointegrating regression method. Unlike the conventional unit root and cointegration methods, we test for the validity of the PPP hypothesis at both the quantile interval and the single quantile level. While conventional nonlinear models could also capture the regime switching behaviour, the quantile approach enables us to avoid choosing the appropriate form of nonlinearity, and therefore, avoid the misspecification risk. When conventional methods are used, the PPP hypothesis is not strongly supported for all three countries. However, when the quantile-based approach is used, the PPP hypothesis holds for China at some quantile levels when producer price index (PPI) is used as price variable, and it also holds for Japan over the lower and upper quantile levels. Interestingly, the PPP hypothesis for South Korea holds over all quantile levels when the consumer price index (CPI) is used as the price variable.

This study investigates the causal relationship between investor sentiment and stock returns in the USA by conducting a quantile Granger non-causality test. Employing two proxies for investor sentiment – the sentiment index developed by Baker and Wurgler in 2007 and the University of Michigan Consumer Survey, a consumer confidence index – we find that the causal relationship between investor sentiment and stock returns strengthens when a tail quantile interval is considered. This finding implies that the investor sentiment could provide the incremental predictability for the stock returns under the extreme market situation, which cannot be found using a traditional Granger causality test. Interestingly, the findings can be explained by investors' loss aversion and herding behavior.