Qian guo microsoft

Includes Address 1 Phone 5. Resides in Cary, NC. Also known as Qian Zhong. Includes Address 2 Phone 2. Also known as Quian Guo.

Includes Address 3. Resides in West Orange, NJ. Also known as Guo Qian, Qiana Guo. Includes Address 6 Phone 4 Email 1. Resides in Pomona, CA. Related To Zhengliang Guo. Includes Address 3 Phone 1. Resides in San Jose, CA. Includes Address 4 Email 2. Lived In Seattle WA. Lived In Hayward CA. Includes Address 2 Email 3. Resides in Aurora, IL. Also known as Guo Qian. It is implemented on the reference implementation of FrodoKEM, which is claimed to be secure against all timing attacks.

One important open question in side-channel analysis is to find out whether all the leakage samples in an implementation can be exploited by an adversary, as suggested by masking security proofs.

They represent the target implementation and its leakages as a code similar to a Low Density Parity Check code that is decoded thanks to belief propagation. Our study establishes interesting connections between this model and the erasure channel used in coding theory, leading to the following benefits. Second, we show that the LRPM is a tool of choice for the nearly worst-case analysis of masked implementations in the noisy leakage model, taking advantage of all the operations performed, and leading to new tradeoffs between their amount of randomness and physical noise level.

Third, we show that it can considerably speed up the evaluation of other countermeasures such as shuffling. It is a code-based scheme in the class of public key encryptions, with given sets of parameters spanning NIST security strength 1, 3 and 5, corresponding to , and bits of classic security.

In this paper we present an attack recovering the secret key of an HQC instance named hqc The attack requires a single precomputation performed once and then never again. In this phase, the secret key of the HQC instance is determined.

This is a setting relevant to practical security since the large precomputation needs to be done only once. In this paper we investigate the impact of decryption failures on the chosen-ciphertext security of lattice-based primitives. We discuss a generic framework for secret key recovery based on decryption failures and present an attack on the NIST Post-Quantum Proposal ss-ntru-pke.

Furthermore, a new generic weak-key multi-target model on lattice-based schemes, which can be viewed as a variant of the previous framework, is proposed. This model further takes into consideration the weak-key phenomenon that a small fraction of keys can have much larger decoding error probability for ciphertexts with certain key-related properties.

We apply this model and present an attack in detail on the NIST Post-Quantum Proposal — ss-ntru-pke — with complexity below the claimed security level. Cryptosystems based on Learning with Errors or related problems are central topics in recent cryptographic research. Many submitted proposals rely on problems related to Learning with Errors. Such schemes often include the possibility of decryption errors with some very small probability.

Some of them have a somewhat larger error probability in each coordinate, but use an error correcting code to get rid of errors. In this paper we propose and discuss an attack for secret key recovery based on generating decryption errors, for schemes using error correcting codes. In a standard setting with CCA security, the attack first consists of a precomputation of special messages and their corresponding error vectors. This set of messages are submitted for decryption and a few decryption errors are observed.

In a statistical analysis step, these vectors causing the decryption errors are processed and the result reveals the secret key. The attack only works for a fraction of the secret keys. This attack is verified via extensive simulation. We excluded retracted studies. After assessment, we resolved disagreements between the 2 authors through discussion with a third reviewer JC.

We also searched the reference lists of original reports, case reports, guidelines, letters to the editor, reviews, and meta-analyses retrieved through electronic searches for additional articles.

For studies that potentially fulfilled the inclusion criteria, we searched the full papers, which were assessed independently by the same 2 authors. The same 2 authors also used a predesigned data collection form Microsoft Office Excel , Microsoft, Redmond, WA to extract all the data independently.

The following information was collected: study design, study site, participant inclusion and exclusion criteria, cancer type, sample size the 2 groups and the total size , mean and standard deviation of the 2 groups, spiritual interventions method, frequency, durations of each session, and total interventions , control interventions, outcomes, and measures.

Information used to evaluate the risk of bias for each study was also collected, including methods used to generate the randomization, allocation concealment, blinding, incomplete outcome data, and selective reporting. We defined spiritual well-being and quality of life at post-treatment as our primary outcomes for any measure used. As associated symptoms of spiritual distress in patients with cancer, degree of depression, anxiety, and hopelessness at post-treatment were combined as secondary outcomes.

After extraction, all data were checked by another author JC , and discrepancies were resolved by discussion. We sent letters to the authors of the studies retrieved to clarify missing or unclear data. The risk of bias assessment was conducted independently by 2 authors LX and JQ , and disagreements were discussed with a third author JC.

The Cochrane risk of bias tool was used for the assessment of random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other bias. Each domain was rated as low unlikely to seriously alter the results , unclear, or high seriously weakens confidence in the results. The possibility of bias is minimal when all the criteria are met grade A , and grade B has a medium possibility of bias occurring.

If the criteria are not met at all, the possibility of bias is high and the grade is C. For RCTs, heterogeneity was analyzed by conducting the chi-squared test P of. The higher the percentage was, the higher the level of heterogeneity. We used forest plots and funnel plots. The funnel plots can indicate possible publication bias, evidence of asymmetry, and other small study effects. Because some included studies examined patients with all kinds of cancer and some studies recruited patients with a specific kind of cancer, we used subgroup analysis to check whether spiritual interventions are beneficial to patients with different kinds of cancer.

We identified records and ultimately recruited 10 studies Fig. All 10 studies were RCTs involving a total of patients with cancer for quantitative synthesis, and all were reviewed by an institutional ethics committee before implementation.

Among the patients, and patients were allocated into the intervention and control groups, respectively, after randomization. The participants in the 10 RCTs were all patients with cancer. Of these, 7 [ 24 , 25 , 31 — 35 ] and 5 [ 31 — 34 , 36 ] studies identified spiritual well-being and quality of life, respectively, as the main outcome.

Of the 10 studies, 6 adopted five types of spiritual interventions, including meaning-centered psychotherapy, [ 31 , 32 ] mindfulness-based intervention, [ 35 ] imagination, [ 33 ] meditation, [ 37 ] and prayer; [ 34 ] the other 4 [ 7 , 24 , 25 , 36 ] did not focus on a specific spiritual intervention method; rather, they included a specifically designed integrated intervention called a spiritual care program or a spirituality-based intervention.

No matter what spiritual interventions were used, these methods had a large degree of overlap. All studies described their control methods. Among them, 2 trials used wait-list control, [ 33 , 35 ] 2 trials used other psychotherapy methods, [ 31 , 32 ] and another trial used no treatment [ 36 ] as a control. Standard care was performed in the other 5 trials, which was described as routine treatment and education [ 25 ] and usual care [ 7 , 24 , 34 , 37 ] in the original studies.

For quality of life, the McGill Quality of Life Questionnaire and the Functional Assessment of Cancer Therapy were used in 2 [ 31 , 32 ] and 3 [ 33 , 34 , 36 ] trials, respectively. Regarding the types of spiritual interventions, there were various frequencies and durations of interventions. We used the Cochrane risk of bias tool to assess the risk of bias of each study. In addition, 5 of the studies did not describe the allocation concealment in detail Thus, the generalization of results may have been influenced.

Furthermore, because of the nature and method of the implementation of spiritual interventions, it was difficult to perform blinding, especially the blinding of participants and personnel. This lack of blinding may have induced performance bias in the original articles.

Except for the study by Jafari et al, [ 25 ] the other 9 studies described the dropouts and the reasons for these dropouts, which could help to prevent attrition bias to some extent, and all of them used intent-to-treat analysis to analyze the data except for Rausch.

Funnel plot of comparison: spiritual intervention versus control condition, outcome: spiritual well-being at post-treatment. Funnel plot of comparison: spiritual intervention versus control condition, outcome: quality of life at post-treatment. Seven studies [ 24 , 25 , 31 — 35 ] involving patients in the intervention group and in the control group reported the effect of spiritual interventions on the spiritual well-being of patients with cancer at post-treatment, indicating a statistically significant difference between the effects of the spiritual intervention and the control SMD 0.

However, the estimate was associated with a high level of uncertainty due to severe heterogeneity after a random-effects model was adopted. Forest plot of comparison: spiritual intervention versus control condition, outcome: standardized mean difference for spiritual well-being at post-treatment.

Because the included studies recruited patients with different kinds of cancer, including breast cancer, [ 25 , 33 ] leukemia, [ 24 ] and other kinds of cancer, [ 31 , 32 , 34 , 35 ] we used subgroup analysis to check whether spiritual interventions can improve spiritual well-being for different cancer patients.

We found that there was a significant difference between the 2 groups only in patients with breast cancer SMD 0. Forest plot of comparison: spiritual intervention versus control condition, outcome: standardized mean difference for spiritual well-being at post-treatment by subgroup analysis.

Five studies [ 31 — 34 , 36 ] involving patients in the intervention group and in the control group reported the effect of spiritual interventions on quality of life at post-treatment in patients with cancer. As shown in Fig. Forest plot of comparison: spiritual intervention versus control condition, outcome: standardized mean difference for quality of life at post-treatment.

Forest plot of comparison: spiritual intervention versus control condition, outcome: standardized mean difference for degree of depression at post-treatment. Forest plot of comparison: spiritual intervention versus control condition, outcome: standardized mean difference for degree of anxiety at post-treatment. Forest plot of comparison: spiritual intervention versus control condition, outcome: standardized mean difference for degree of hopelessness at post-treatment.

GRADE was used to evaluate the quality of evidence. The evidence grades for degree of depression, anxiety, quality of life were low, and the evidence quality for degree of hopelessness was very low. This study, which synthesized data from RCTs, is an update of a previous published meta-analysis verifying the effects of spiritual interventions on physical and psychological outcomes in patients with cancer. This meta-analysis provides evidence for doctors and nurses to potentially improve spiritual well-being and quality of life, and to reduce degree of depression, anxiety, and hopelessness via spiritual interventions with these patients.

In addition to using spiritual well-being and quality of life as primary outcomes, we defined other psychological problems that cancer patients often have as secondary outcomes, including degree of depression, anxiety, and hopelessness, which made our meta-analysis more comprehensive. However, due to the methodological limitations of the included studies and the subjectivity of the assessment scales used, we failed to obtain much high-quality evidence in the present meta-analysis, as the majority of the accumulated evidence ranged from low to moderate quality.

With the extensive application of holistic nursing, mental health and quality of life have received increasing attention from nurses and have become active research fields. Patients with cancer are subject to spiritual distress and low quality of life, so it is extremely important to keep their spiritual well-being and quality of life satisfactory. First, due to the quality of spiritual intervention, the fact that 5 of the 7 included studies did not blind the participants, personnel, and outcome assessors may induce performance bias and detection bias.

Second, in the study of Jafari et al, [ 25 ] the outcome data were incomplete, which may lead to some attrition bias. Third, components of the spiritual interventions used in these 7 studies differed, such as the duration, methods, and control groups, which may lead to differences in the combination of results. For example, 2 studies used supportive psychotherapy [ 32 ] and therapeutic massage [ 31 ] as the control groups, which was different from the other 5 studies usual care or wait-list control.

Finally, the scales used in these studies provide a subjective assessment of spiritual well-being, and all the studies allowed patients to complete the scale independently, which may have resulted in large differences. And an interesting finding of our meta-analysis is that in the subgroup analysis, spiritual interventions were shown to improve spiritual well-being only in patients with breast cancer.

This finding indicates that spiritual interventions can confer quick benefits in the spiritual well-being of patients with breast cancer but not other kinds of cancer, and emphasizes the need for individualization when adopting spiritual interventions. In other words, for patients with breast cancer, it may be appropriate to adopt spiritual intervention methods to improve their spiritual well-being, but for patients with other kinds of cancer, these methods are not as suitable, thus, other psychological interventions should be used to effectively improve their spiritual well-being.

Regarding quality of life, the combined results also showed a statistically significant difference between the intervention and control groups at post-treatment, indicating that spiritual interventions might improve quality of life in patients with cancer. Depression, anxiety, and hopelessness are common mental problems in patients with cancer, and sometimes, they can cause severe outcomes. Currently, antidepressants are still the main therapy for depression.

The National Institute for Health and Clinical Excellence recommends treatment for at least 6 months and even for at least 2 years if patients have a risk of relapse. Many patients cannot maintain drug therapy because of its chronicity and side effects, such as drowsiness, dry mouth, tachycardia, and dependence.